Merge pull request 'RTPC-dev' (#9) from RTPC-dev into Release
Reviewed-on: http://123.153.4.249:22779/LAMPSARToolSoftware/RasterProcessTool/pulls/9Release
chenzenghui
commit
c55953aa7c
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@ -148,6 +148,11 @@ struct Vector3 {
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};
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struct Vector3_single {
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float x, y, z;
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};
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/*********************************************** FEKO仿真参数 ********************************************************************/
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struct SatellitePos {
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double time;
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@ -21,9 +21,9 @@
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#include "GPUBPTool.cuh"
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#include "BPBasic0_CUDA.cuh"
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#include "GPUBpSimulation.cuh"
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#include "GPURFPC_single.cuh"
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#include "GPURFPC.cuh"
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double* getFreqPoints_mallocHost(double startFreq, double endFreq, long freqpoints)
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{
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@ -68,7 +68,7 @@ __global__ void kernel_RFPCProcess(
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// ÈëÉä½Ç
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Vector3 TS = vec_sub(S, T);//T-->S
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double localIncAngle = angleBetweenVectors(TS, slp, false);// ÈëÉä½Ç
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double sigma0 = GPU_getSigma0dB(p1, p2, p3, p4, p5, p6, localIncAngle);// 后向散射系数
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double sigma0 = GPU_getSigma0dB_params(p1, p2, p3, p4, p5, p6, localIncAngle);// 后向散射系数
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sigma0 = powf(10.0, sigma0 / 10.0);
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// ¾àÀë
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@ -95,8 +95,6 @@ void RFPCProcess(double Tx, double Ty, double Tz,
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double p1, double p2, double p3, double p4, double p5, double p6,
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GPUDATA& d_data)
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{
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double* AntX = (double*)mallocCUDADevice(sizeof(double) * d_data.Np);
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double* AntY = (double*)mallocCUDADevice(sizeof(double) * d_data.Np);
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double* AntZ = (double*)mallocCUDADevice(sizeof(double) * d_data.Np);
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@ -128,3 +126,125 @@ void RFPCProcess(double Tx, double Ty, double Tz,
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/** 单精度成像测试 *****************************************************************************************************************************************/
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__global__ void kernel_RFPCProcess_single(
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float* Sx, float* Sy, float* Sz,
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float Tx, float Ty, float Tz,
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float Tslx, float Tsly, float Tslz, // 目标的坡面向量
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float p1, float p2, float p3, float p4, float p5, float p6,
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long Np, long Nf,
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float minF, float dFreq, float RefRange,
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cuComplex* phdata
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) {
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long prfid = blockIdx.x * blockDim.x + threadIdx.x; // 获取当前的线程编码
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if (prfid >= Np || prfid < 0) { return; }
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else {}
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// 距离
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Vector3_single S{ Sx[prfid],Sy[prfid],Sz[prfid] };
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Vector3_single T{ Tx,Ty,Tz };
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Vector3_single slp{ Tslx,Tsly,Tslz };
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//printf("S=(%e,%e,%e)\n", S.x, S.y, S.z);
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// 入射角
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Vector3_single TS = vec_sub_single(S, T);//T-->S
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float localIncAngle = angleBetweenVectors_single(TS, slp, false);// 入射角
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float sigma0 = GPU_getSigma0dB_single(p1, p2, p3, p4, p5, p6, localIncAngle);// 后向散射系数
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sigma0 = powf(10.0, sigma0 / 10.0);
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// 距离
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float R = sqrtf(vec_dot_single(TS, TS));
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// 计算增益
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float amp_echo = sigma0 / (powf(4 * LAMP_CUDA_PI, 2) * powf(R, 4)); // 反射强度
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float phi = 0;
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for (long fid = 0; fid < Nf; fid++) {
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phi = -4.0 * PI / LIGHTSPEED * (minF + dFreq * fid) * (R - RefRange);
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phdata[prfid * Nf + fid].x += amp_echo * cosf(phi);
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phdata[prfid * Nf + fid].y += amp_echo * sinf(phi);
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//printf("phdata(%d,%d)=complex(%e,%e)\n", prfid, fid, phdata[prfid * Nf + fid].x, phdata[prfid * Nf + fid].y);
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}
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//printf("Nf:%d\n", Nf);
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//printf("amp_echo:%f\n", amp_echo);
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//printf("sigma0:%f\n", sigma0);
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//printf("R:%e\n", R);
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}
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float* getFreqPoints_mallocHost_single(float startFreq, float endFreq, long freqpoints)
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{
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float dfreq = (endFreq - startFreq) / (freqpoints - 1);
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float* freqlist = (float*)mallocCUDAHost(sizeof(float) * freqpoints);
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for (long i = 0; i < freqpoints; i++) {
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freqlist[i] = startFreq + dfreq * i;
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}
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return freqlist;
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}
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void RFPCProcess_single(
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float Tx, float Ty, float Tz,
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float Tslx, float Tsly, float Tslz,
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float p1, float p2, float p3, float p4, float p5, float p6,
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GPUDATA_single& d_data)
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{
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float* AntX = (float*)mallocCUDADevice(sizeof(float) * d_data.Np);
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float* AntY = (float*)mallocCUDADevice(sizeof(float) * d_data.Np);
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float* AntZ = (float*)mallocCUDADevice(sizeof(float) * d_data.Np);
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HostToDevice(d_data.AntX, AntX, sizeof(float) * d_data.Np); printf("antX host to device finished!!\n");
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HostToDevice(d_data.AntY, AntY, sizeof(float) * d_data.Np); printf("antY host to device finished!!\n");
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HostToDevice(d_data.AntZ, AntZ, sizeof(float) * d_data.Np); printf("antZ host to device finished!!\n");
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float minF = d_data.minF[0];
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long grid_size = (d_data.Np + BLOCK_SIZE - 1) / BLOCK_SIZE;
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float dfreq = d_data.deltaF;
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float R0 = d_data.R0;
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kernel_RFPCProcess_single << <grid_size, BLOCK_SIZE >> > (
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AntX, AntY, AntZ,
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Tx, Ty, Tz,
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Tslx, Tsly, Tslz, // 目标的坡面向量
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p1, p2, p3, p4, p5, p6,
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d_data.Np, d_data.Nfft,
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minF, dfreq, R0,
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d_data.phdata
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);
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PrintLasterError("RFPCProcess");
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FreeCUDADevice(AntX);
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FreeCUDADevice(AntY);
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FreeCUDADevice(AntZ);
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return;
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}
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@ -30,6 +30,17 @@ extern "C" void RFPCProcess(
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GPUDATA& d_data
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);
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extern "C" float* getFreqPoints_mallocHost_single(float startFreq, float endFreq, long freqpoints);
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extern "C" void RFPCProcess_single(
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float Tx, float Ty, float Tz, // 目标点坐标
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float Tslx, float Tsly, float Tslz, // 目标的坡面向量
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float p1, float p2, float p3, float p4, float p5, float p6,// 地面目标后向散射系数与入射角关系 系数
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GPUDATA_single& d_data
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);
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#endif
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@ -13,19 +13,19 @@
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#include "LookTableSimulationComputer.cuh"
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extern __device__ __host__ double getNumberDopplerCenterRate(double R, double r0, double r1, double r2, double r3, double r4, double reftime)
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extern __device__ double getNumberDopplerCenterRate(double R, double r0, double r1, double r2, double r3, double r4, double reftime)
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{
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double t=R / LIGHTSPEED - reftime;
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double dopplerCenterRate = r0 + r1*t + r2*t*t + r3*t*t*t + r4*t*t*t*t;
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return dopplerCenterRate;
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}
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__device__ __host__ double getDopplerCenterRate(double Rx, double Ry, double Rz, double Vx, double Vy, double Vz, double fact_lamda)
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__device__ double getDopplerCenterRate(double Rx, double Ry, double Rz, double Vx, double Vy, double Vz, double fact_lamda)
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{
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return -2*(Rx*Vx+Ry*Vy+Rz*Vz)* fact_lamda;
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}
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__device__ __host__ double getPolyfitNumber(double x, double a0, double a1, double a2, double a3, double a4, double a5)
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__device__ double getPolyfitNumber(double x, double a0, double a1, double a2, double a3, double a4, double a5)
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{
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return a0 + a1 * x + a2 * x * x + a3 * x * x * x + a4 * x * x * x * x + a5 * x * x * x * x * x;
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}
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@ -8,11 +8,11 @@
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extern __device__ __host__ double getNumberDopplerCenterRate(double R, double r0, double r1, double r2, double r3, double r4,double reftime);
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extern __device__ double getNumberDopplerCenterRate(double R, double r0, double r1, double r2, double r3, double r4,double reftime);
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extern __device__ __host__ double getDopplerCenterRate(double Rx,double Ry,double Rz,double Vx,double Vy,double Vz,double fact_lamda); //fact_lamda lamda ľÄľšĘý
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extern __device__ double getDopplerCenterRate(double Rx,double Ry,double Rz,double Vx,double Vy,double Vz,double fact_lamda); //fact_lamda lamda ľÄľšĘý
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extern __device__ __host__ double getPolyfitNumber(double x, double a0, double a1, double a2, double a3, double a4,double a5);
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extern __device__ double getPolyfitNumber(double x, double a0, double a1, double a2, double a3, double a4,double a5);
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@ -185,9 +185,8 @@ void bpBasic0CUDA(GPUDATA& data, int flag,double* h_R) {
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data.im_final
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//,d_R
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);
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PrintLasterError("processPulseKernel");
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if (ii % 1000==0) {
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printfinfo("\rPRF(%f %) %d / %d\t\t\t\t",(ii*100.0/data.Np), ii,data.Np);
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if (ii % 10000 == 0) {
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printfinfo("PRF[%f]: %d / %d", ii * 100.0 / data.Np, ii, data.Np);
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}
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}
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//FreeCUDADevice(d_R);
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@ -276,6 +275,10 @@ void BPBasic0(GPUDATA& h_data)
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freeGPUData(d_data);
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}
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//int main() {
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// GPUDATA h_data, d_data;
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//
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@ -30,6 +30,21 @@ struct GPUDATA {
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double deltaF; // 频点范围
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};
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struct GPUDATA_single {
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long Nfft, K, Np, nx, ny; // 傅里叶点数、频点数、脉冲数、图像列、图像行
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float* AntX, * AntY, * AntZ, * minF; // 天线坐标、起始频率
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float* x_mat, * y_mat, * z_mat;// 地面坐标
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float* r_vec; // 坐标范围
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float* Freq;// 频率
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cuComplex* phdata;// 回波
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cuComplex* im_final;// 图像
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float R0; // 参考斜距
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float deltaF; // 频点范围
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};
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extern "C" {
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void bpBasic0CUDA(GPUDATA& data, int flag,double* h_R=nullptr);
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void initGPUData(GPUDATA& h_data, GPUDATA& d_data);
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@ -38,4 +53,15 @@ extern "C" {
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void BPBasic0(GPUDATA& h_data);
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};
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extern "C" {
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// 函数废弃，因为这个成像精度不够
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//void bpBasic0CUDA_single(GPUDATA_single& data, int flag, float* h_R = nullptr);
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//void initGPUData_single(GPUDATA_single& h_data, GPUDATA_single& d_data);
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//void freeGPUData_single(GPUDATA_single& d_data);
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//void freeHostData_single(GPUDATA_single& d_data);
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//void BPBasic0_single(GPUDATA_single& h_data);
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};
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#endif
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@ -22,13 +22,13 @@
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#define M_PI 3.14159265358979323846
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#endif
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__device__ __host__ double angleBetweenVectors(Vector3 a, Vector3 b, bool returnDegrees ) {
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__device__ double angleBetweenVectors(Vector3 a, Vector3 b, bool returnDegrees ) {
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// 计算点积
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double dotProduct = a.x * b.x + a.y * b.y + a.z * b.z;
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// 计算模长
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double magA = std::sqrt(a.x * a.x + a.y * a.y + a.z * a.z);
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double magB = std::sqrt(b.x * b.x + b.y * b.y + b.z * b.z);
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double magA = sqrt(a.x * a.x + a.y * a.y + a.z * a.z);
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double magB = sqrt(b.x * b.x + b.y * b.y + b.z * b.z);
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// 处理零向量异常
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if (magA == 0.0 || magB == 0.0) {
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@ -37,33 +37,33 @@ __device__ __host__ double angleBetweenVectors(Vector3 a, Vector3 b, bool retur
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double cosTheta = dotProduct / (magA * magB);
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cosTheta = cosTheta < -1 ? -1 : cosTheta>1 ? 1 : cosTheta; // 截断到[-1, 1]
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double angleRad = std::acos(cosTheta);
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double angleRad = acos(cosTheta);
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return returnDegrees ? angleRad * 180.0 / M_PI : angleRad;
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}
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// 向量运算
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__device__ __host__ Vector3 vec_sub(Vector3 a, Vector3 b) {
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__device__ Vector3 vec_sub(Vector3 a, Vector3 b) {
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return { a.x - b.x, a.y - b.y, a.z - b.z };
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}
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__device__ __host__ double vec_dot(Vector3 a, Vector3 b) {
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__device__ double vec_dot(Vector3 a, Vector3 b) {
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return a.x * b.x + a.y * b.y + a.z * b.z;
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}
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__device__ __host__ Vector3 vec_cross(Vector3 a, Vector3 b) {
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__device__ Vector3 vec_cross(Vector3 a, Vector3 b) {
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return { a.y * b.z - a.z * b.y,
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a.z * b.x - a.x * b.z,
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a.x * b.y - a.y * b.x };
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}
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__device__ __host__ Vector3 vec_normalize(Vector3 v) {
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__device__ Vector3 vec_normalize(Vector3 v) {
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double len = sqrt(vec_dot(v, v));
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return (len > 1e-12) ? Vector3{ v.x / len, v.y / len, v.z / len } : v;
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}
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// 标准正交基底坐标计算
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__device__ __host__ Vector3 coordinates_orthonormal_basis(Vector3& A,
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__device__ Vector3 coordinates_orthonormal_basis(Vector3& A,
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Vector3& e1,
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Vector3& e2,
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Vector3& e3) {
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@ -87,7 +87,7 @@ __device__ __host__ Vector3 coordinates_orthonormal_basis(Vector3& A,
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// 计算视线交点T
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extern __device__ __host__ Vector3 compute_T(Vector3 S, Vector3 ray, double H) {
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extern __device__ Vector3 compute_T(Vector3 S, Vector3 ray, double H) {
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Vector3 dir = vec_normalize(ray);
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double a_h = WGS84_A + H;
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@ -105,7 +105,7 @@ extern __device__ __host__ Vector3 compute_T(Vector3 S, Vector3 ray, double H) {
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}
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// 主计算函数A
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extern __device__ __host__ Vector3 compute_P(Vector3 S, Vector3 T, double R, double H) {
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extern __device__ Vector3 compute_P(Vector3 S, Vector3 T, double R, double H) {
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Vector3 ex, ey, ez; // 平面基函数
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Vector3 ST = vec_normalize(vec_sub(T, S));// S->T
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Vector3 SO = vec_normalize(vec_sub(Vector3{ 0, 0, 0 }, S)); // S->O
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@ -203,7 +203,44 @@ extern __device__ __host__ Vector3 compute_P(Vector3 S, Vector3 T, double R, dou
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return P;
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}
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__device__ double angleBetweenVectors_single(Vector3_single a, Vector3_single b, bool returnDegrees)
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{
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// 计算点积
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float dotProduct = a.x * b.x + a.y * b.y + a.z * b.z;
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// 计算模长
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float magA = sqrtf(a.x * a.x + a.y * a.y + a.z * a.z);
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float magB = sqrtf(b.x * b.x + b.y * b.y + b.z * b.z);
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// 处理零向量异常
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if (magA == 0.0 || magB == 0.0) {
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return NAN;
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}
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float cosTheta = dotProduct / (magA * magB);
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cosTheta = cosTheta < -1 ? -1 : cosTheta>1 ? 1 : cosTheta; // 截断到[-1, 1]
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float angleRad = acosf(cosTheta);
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return returnDegrees ? angleRad * 180.0 / M_PI : angleRad;
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}
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__device__ Vector3_single vec_sub_single(Vector3_single a, Vector3_single b)
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{
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return { a.x - b.x, a.y - b.y, a.z - b.z };
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}
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|
||||
__device__ float vec_dot_single(Vector3_single a, Vector3_single b)
|
||||
{
|
||||
return a.x * b.x + a.y * b.y + a.z * b.z;
|
||||
}
|
||||
|
||||
__device__ Vector3_single vec_cross_single(Vector3_single a, Vector3_single b)
|
||||
{
|
||||
return Vector3_single{ a.y * b.z - a.z * b.y,
|
||||
a.z * b.x - a.x * b.z,
|
||||
a.x * b.y - a.y * b.x };
|
||||
}
|
||||
|
||||
|
||||
|
||||
//// 参数校验与主函数
|
||||
//int main() {
|
||||
|
|
|
|||
|
|
@ -8,12 +8,16 @@
|
|||
|
||||
|
||||
|
||||
extern __device__ __host__ double angleBetweenVectors(Vector3 a, Vector3 b, bool returnDegrees = false);
|
||||
extern __device__ __host__ Vector3 vec_sub(Vector3 a, Vector3 b);
|
||||
extern __device__ __host__ double vec_dot(Vector3 a, Vector3 b);
|
||||
extern __device__ __host__ Vector3 vec_cross(Vector3 a, Vector3 b);
|
||||
extern __device__ __host__ Vector3 vec_normalize(Vector3 v);
|
||||
extern __device__ __host__ Vector3 compute_T(Vector3 S, Vector3 ray_dir, double H);
|
||||
//
|
||||
extern __device__ __host__ Vector3 compute_P(Vector3 S, Vector3 T, double R, double H );
|
||||
extern __device__ double angleBetweenVectors(Vector3 a, Vector3 b, bool returnDegrees = false);
|
||||
extern __device__ Vector3 vec_sub(Vector3 a, Vector3 b);
|
||||
extern __device__ double vec_dot(Vector3 a, Vector3 b);
|
||||
extern __device__ Vector3 vec_cross(Vector3 a, Vector3 b);
|
||||
extern __device__ Vector3 vec_normalize(Vector3 v);
|
||||
extern __device__ Vector3 compute_T(Vector3 S, Vector3 ray_dir, double H);
|
||||
extern __device__ Vector3 compute_P(Vector3 S, Vector3 T, double R, double H );
|
||||
|
||||
|
||||
extern __device__ double angleBetweenVectors_single(Vector3_single a, Vector3_single b, bool returnDegrees = false);
|
||||
extern __device__ Vector3_single vec_sub_single(Vector3_single a, Vector3_single b);
|
||||
extern __device__ float vec_dot_single(Vector3_single a, Vector3_single b);
|
||||
extern __device__ Vector3_single vec_cross_single(Vector3_single a, Vector3_single b);
|
||||
|
|
|
|||
|
|
@ -1,9 +1,4 @@
|
|||
|
||||
#include <time.h>
|
||||
#include <iostream>
|
||||
#include <memory>
|
||||
#include <cmath>
|
||||
#include <complex>
|
||||
#include <cuda.h>
|
||||
#include <device_launch_parameters.h>
|
||||
#include <cuda_runtime.h>
|
||||
#include <cublas_v2.h>
|
||||
|
|
@ -19,12 +14,13 @@
|
|||
/* »úÆ÷º¯Êý ****************************************************************************************************************************/
|
||||
|
||||
|
||||
extern __host__ __device__ double GPU_getSigma0dB(CUDASigmaParam param, double theta) {//ÏßÐÔÖµ
|
||||
extern __device__ double GPU_getSigma0dB(CUDASigmaParam param, double theta) {//ÏßÐÔÖµ
|
||||
double sigma = param.p1 + param.p2 * exp(-param.p3 * theta) + param.p4 * cos(param.p5 * theta + param.p6);
|
||||
return sigma;
|
||||
}
|
||||
|
||||
extern __host__ __device__ double GPU_getSigma0dB(
|
||||
|
||||
__device__ double GPU_getSigma0dB_params(
|
||||
const double p1, const double p2, const double p3, const double p4, const double p5, const double p6,
|
||||
double theta) {//ÏßÐÔÖµ
|
||||
return p1 + p2 * exp(-p3 * theta) + p4 * cos(p5 * theta + p6);
|
||||
|
|
@ -32,7 +28,7 @@ extern __host__ __device__ double GPU_getSigma0dB(
|
|||
|
||||
|
||||
|
||||
extern __host__ __device__ CUDAVectorEllipsoidal GPU_SatelliteAntDirectNormal(
|
||||
extern __device__ CUDAVectorEllipsoidal GPU_SatelliteAntDirectNormal(
|
||||
double RstX, double RstY, double RstZ,
|
||||
double AntXaxisX, double AntXaxisY, double AntXaxisZ,
|
||||
double AntYaxisX, double AntYaxisY, double AntYaxisZ,
|
||||
|
|
@ -111,7 +107,7 @@ extern __host__ __device__ CUDAVectorEllipsoidal GPU_SatelliteAntDirectNormal(
|
|||
return result;
|
||||
}
|
||||
|
||||
extern __host__ __device__ double GPU_BillerInterpAntPattern(double* antpattern,
|
||||
extern __device__ double GPU_BillerInterpAntPattern(double* antpattern,
|
||||
double starttheta, double startphi, double dtheta, double dphi,
|
||||
long thetapoints, long phipoints,
|
||||
double searththeta, double searchphi) {
|
||||
|
|
|
|||
|
|
@ -20,15 +20,15 @@ extern "C" struct CUDASigmaParam {
|
|||
double p6;
|
||||
};
|
||||
|
||||
|
||||
|
||||
|
||||
extern __host__ __device__ double GPU_getSigma0dB(
|
||||
extern __device__ double GPU_getSigma0dB_params(
|
||||
const double p1, const double p2, const double p3, const double p4, const double p5, const double p6,
|
||||
double theta);
|
||||
|
||||
extern __host__ __device__ double GPU_getSigma0dB(CUDASigmaParam param, double theta);
|
||||
extern __device__ double GPU_getSigma0dB(CUDASigmaParam param, double theta);
|
||||
|
||||
extern __host__ __device__ CUDAVectorEllipsoidal GPU_SatelliteAntDirectNormal(
|
||||
extern __device__ CUDAVectorEllipsoidal GPU_SatelliteAntDirectNormal(
|
||||
double RstX, double RstY, double RstZ,
|
||||
double AntXaxisX, double AntXaxisY, double AntXaxisZ,
|
||||
double AntYaxisX, double AntYaxisY, double AntYaxisZ,
|
||||
|
|
@ -36,7 +36,7 @@ extern __host__ __device__ CUDAVectorEllipsoidal GPU_SatelliteAntDirectNormal(
|
|||
double AntDirectX, double AntDirectY, double AntDirectZ
|
||||
);
|
||||
|
||||
extern __host__ __device__ double GPU_BillerInterpAntPattern(double* antpattern,
|
||||
extern __device__ double GPU_BillerInterpAntPattern(double* antpattern,
|
||||
double starttheta, double startphi, double dtheta, double dphi,
|
||||
long thetapoints, long phipoints,
|
||||
double searththeta, double searchphi);
|
||||
|
|
|
|||
|
|
@ -0,0 +1,468 @@
|
|||
#include <cuda.h>
|
||||
#include <device_launch_parameters.h>
|
||||
#include <cuda_runtime.h>
|
||||
#include <cublas_v2.h>
|
||||
#include <cuComplex.h>
|
||||
|
||||
#include "BaseConstVariable.h"
|
||||
#include "GPURFPC_single.cuh"
|
||||
|
||||
|
||||
#ifdef __CUDANVCC___
|
||||
|
||||
|
||||
/* 机器函数 ****************************************************************************************************************************/
|
||||
|
||||
|
||||
extern __device__ float GPU_getSigma0dB_single(CUDASigmaParam_single param, float theta) {//线性值
|
||||
float sigma = param.p1 + param.p2 * exp(-param.p3 * theta) + param.p4 * cos(param.p5 * theta + param.p6);
|
||||
return sigma;
|
||||
}
|
||||
|
||||
|
||||
extern __device__ float GPU_getSigma0dB_single(const float p1, const float p2, const float p3, const float p4, const float p5, const float p6, float theta)
|
||||
{
|
||||
return p1 + p2 * expf(-p3 * theta) + p4 * cosf(p5 * theta + p6);
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
extern __device__ CUDAVectorEllipsoidal GPU_SatelliteAntDirectNormal_single(
|
||||
float RstX, float RstY, float RstZ,
|
||||
float AntXaxisX, float AntXaxisY, float AntXaxisZ,
|
||||
float AntYaxisX, float AntYaxisY, float AntYaxisZ,
|
||||
float AntZaxisX, float AntZaxisY, float AntZaxisZ,
|
||||
float AntDirectX, float AntDirectY, float AntDirectZ
|
||||
) {
|
||||
CUDAVectorEllipsoidal result{ 0,0,-1 };
|
||||
|
||||
// 求解天线增益
|
||||
float Xst = -1 * RstX; // 卫星 --> 地面
|
||||
float Yst = -1 * RstY;
|
||||
float Zst = -1 * RstZ;
|
||||
|
||||
// 归一化
|
||||
float RstNorm = sqrtf(Xst * Xst + Yst * Yst + Zst * Zst);
|
||||
float AntXaxisNorm = sqrtf(AntXaxisX * AntXaxisX + AntXaxisY * AntXaxisY + AntXaxisZ * AntXaxisZ);
|
||||
float AntYaxisNorm = sqrtf(AntYaxisX * AntYaxisX + AntYaxisY * AntYaxisY + AntYaxisZ * AntYaxisZ);
|
||||
float AntZaxisNorm = sqrtf(AntZaxisX * AntZaxisX + AntZaxisY * AntZaxisY + AntZaxisZ * AntZaxisZ);
|
||||
|
||||
|
||||
float Rx = Xst / RstNorm;
|
||||
float Ry = Yst / RstNorm;
|
||||
float Rz = Zst / RstNorm;
|
||||
float Xx = AntXaxisX / AntXaxisNorm;
|
||||
float Xy = AntXaxisY / AntXaxisNorm;
|
||||
float Xz = AntXaxisZ / AntXaxisNorm;
|
||||
float Yx = AntYaxisX / AntYaxisNorm;
|
||||
float Yy = AntYaxisY / AntYaxisNorm;
|
||||
float Yz = AntYaxisZ / AntYaxisNorm;
|
||||
float Zx = AntZaxisX / AntZaxisNorm;
|
||||
float Zy = AntZaxisY / AntZaxisNorm;
|
||||
float Zz = AntZaxisZ / AntZaxisNorm;
|
||||
|
||||
float Xant = (Rx * Yy * Zz - Rx * Yz * Zy - Ry * Yx * Zz + Ry * Yz * Zx + Rz * Yx * Zy - Rz * Yy * Zx) / (Xx * Yy * Zz - Xx * Yz * Zy - Xy * Yx * Zz + Xy * Yz * Zx + Xz * Yx * Zy - Xz * Yy * Zx);
|
||||
float Yant = -(Rx * Xy * Zz - Rx * Xz * Zy - Ry * Xx * Zz + Ry * Xz * Zx + Rz * Xx * Zy - Rz * Xy * Zx) / (Xx * Yy * Zz - Xx * Yz * Zy - Xy * Yx * Zz + Xy * Yz * Zx + Xz * Yx * Zy - Xz * Yy * Zx);
|
||||
float Zant = (Rx * Xy * Yz - Rx * Xz * Yy - Ry * Xx * Yz + Ry * Xz * Yx + Rz * Xx * Yy - Rz * Xy * Yx) / (Xx * Yy * Zz - Xx * Yz * Zy - Xy * Yx * Zz + Xy * Yz * Zx + Xz * Yx * Zy - Xz * Yy * Zx);
|
||||
|
||||
|
||||
|
||||
// 计算theta 与 phi
|
||||
float Norm = sqrtf(Xant * Xant + Yant * Yant + Zant * Zant); // 计算 pho
|
||||
float Zn = Zant / Norm;
|
||||
float ThetaAnt = ( - 1 > Zn) ? PI : (Zn > 1 ? 0 : acos(Zn));// acosf(Zant / Norm); // theta 与 Z轴的夹角
|
||||
float PhiAnt = abs(Xant)<PRECISIONTOLERANCE ?0: atanf(Yant / Xant); // -pi/2 ~pi/2
|
||||
|
||||
if (abs(Yant) < PRECISIONTOLERANCE) { // X轴上
|
||||
PhiAnt = 0;
|
||||
}
|
||||
else if (abs(Xant) < PRECISIONTOLERANCE) { // Y轴上，原点
|
||||
if (Yant > 0) {
|
||||
PhiAnt = PI / 2;
|
||||
}
|
||||
else {
|
||||
PhiAnt = -PI / 2;
|
||||
}
|
||||
}
|
||||
else if (Xant < 0) {
|
||||
if (Yant > 0) {
|
||||
PhiAnt = PI + PhiAnt;
|
||||
}
|
||||
else {
|
||||
PhiAnt = -PI + PhiAnt;
|
||||
}
|
||||
}
|
||||
else { // Xant>0 X 正轴
|
||||
|
||||
}
|
||||
|
||||
if (isnan(PhiAnt)) {
|
||||
printf("V=[%f,%f,%f];norm=%f;thetaAnt=%f;phiAnt=%f;\n", Xant, Yant, Zant, Norm, ThetaAnt, PhiAnt);
|
||||
}
|
||||
|
||||
result.theta = ThetaAnt;
|
||||
result.phi = PhiAnt;
|
||||
result.Rho = Norm;
|
||||
return result;
|
||||
}
|
||||
|
||||
extern __device__ float GPU_BillerInterpAntPattern_single(float* antpattern,
|
||||
float starttheta, float startphi, float dtheta, float dphi,
|
||||
long thetapoints, long phipoints,
|
||||
float searththeta, float searchphi) {
|
||||
float stheta = searththeta;
|
||||
float sphi = searchphi;
|
||||
if (stheta > 90) {
|
||||
return 0;
|
||||
}
|
||||
else {}
|
||||
|
||||
|
||||
float pthetaid = (stheta - starttheta) / dtheta;//
|
||||
float pphiid = (sphi - startphi) / dphi;
|
||||
|
||||
long lasttheta = floorf(pthetaid);
|
||||
long nextTheta = lasttheta + 1;
|
||||
long lastphi = floorf(pphiid);
|
||||
long nextPhi = lastphi + 1;
|
||||
|
||||
|
||||
if (lasttheta < 0 || nextTheta < 0 || lastphi < 0 || nextPhi < 0 ||
|
||||
lasttheta >= thetapoints || nextTheta >= thetapoints || lastphi >= phipoints || nextPhi >= phipoints)
|
||||
{
|
||||
return 0;
|
||||
}
|
||||
else {
|
||||
float x = stheta;
|
||||
float y = sphi;
|
||||
|
||||
float x1 = lasttheta * dtheta + starttheta;
|
||||
float x2 = nextTheta * dtheta + starttheta;
|
||||
float y1 = lastphi * dphi + startphi;
|
||||
float y2 = nextPhi * dphi + startphi;
|
||||
|
||||
float z11 = antpattern[lasttheta * phipoints + lastphi];
|
||||
float z12 = antpattern[lasttheta * phipoints + nextPhi];
|
||||
float z21 = antpattern[nextTheta * phipoints + lastphi];
|
||||
float z22 = antpattern[nextTheta * phipoints + nextPhi];
|
||||
|
||||
|
||||
//z11 = powf(10, z11 / 10); // dB-> 线性
|
||||
//z12 = powf(10, z12 / 10);
|
||||
//z21 = powf(10, z21 / 10);
|
||||
//z22 = powf(10, z22 / 10);
|
||||
|
||||
float GainValue = (z11 * (x2 - x) * (y2 - y)
|
||||
+ z21 * (x - x1) * (y2 - y)
|
||||
+ z12 * (x2 - x) * (y - y1)
|
||||
+ z22 * (x - x1) * (y - y1));
|
||||
GainValue = GainValue / ((x2 - x1) * (y2 - y1));
|
||||
return GainValue;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
/* 核函数 ****************************************************************************************************************************/
|
||||
// 计算每块
|
||||
__global__ void CUDA_Kernel_Computer_R_amp_single(
|
||||
float* antX, float* antY, float* antZ,
|
||||
float* antXaxisX, float* antXaxisY, float* antXaxisZ,
|
||||
float* antYaxisX, float* antYaxisY, float* antYaxisZ,
|
||||
float* antZaxisX, float* antZaxisY, float* antZaxisZ,
|
||||
float* antDirectX, float* antDirectY, float* antDirectZ,
|
||||
long PRFCount, // 整体的脉冲数，
|
||||
float* targetX, float* targetY, float* targetZ, long* demCls,
|
||||
float* demSlopeX, float* demSlopeY, float* demSlopeZ ,
|
||||
long startPosId, long pixelcount,
|
||||
CUDASigmaParam_single* sigma0Paramslist, long sigmaparamslistlen,
|
||||
float Pt,
|
||||
float refPhaseRange,
|
||||
float* TransAntpattern,
|
||||
float Transtarttheta, float Transstartphi, float Transdtheta, float Transdphi, int Transthetapoints, int Transphipoints,
|
||||
float* ReceiveAntpattern,
|
||||
float Receivestarttheta, float Receivestartphi, float Receivedtheta, float Receivedphi, int Receivethetapoints, int Receivephipoints,
|
||||
float maxTransAntPatternValue, float maxReceiveAntPatternValue,
|
||||
float NearR, float FarR,
|
||||
float* d_temp_R, float* d_temp_amps// 计算输出
|
||||
) {
|
||||
long idx = blockIdx.x * blockDim.x + threadIdx.x; // 获取当前的线程编码
|
||||
long prfId = idx / SHAREMEMORY_FLOAT_HALF;
|
||||
long posId = idx % SHAREMEMORY_FLOAT_HALF+ startPosId; // 当前线程对应的影像点
|
||||
|
||||
if (prfId < PRFCount && posId < pixelcount) {
|
||||
float RstX = antX[prfId] - targetX[posId]; // 计算坐标矢量
|
||||
float RstY = antY[prfId] - targetY[posId];
|
||||
float RstZ = antZ[prfId] - targetZ[posId];
|
||||
|
||||
float RstR = sqrt(RstX * RstX + RstY * RstY + RstZ * RstZ); // 矢量距离
|
||||
if (RstR<NearR || RstR>FarR) {
|
||||
d_temp_R[idx] = 0;
|
||||
d_temp_amps[idx] = 0;
|
||||
return;
|
||||
}
|
||||
else {
|
||||
float slopeX = demSlopeX[posId];
|
||||
float slopeY = demSlopeY[posId];
|
||||
float slopeZ = demSlopeZ[posId];
|
||||
|
||||
float slopR = sqrtf(slopeX * slopeX + slopeY * slopeY + slopeZ * slopeZ); //
|
||||
if (abs(slopR - 0) > 1e-3) {
|
||||
float dotAB = RstX * slopeX + RstY * slopeY + RstZ * slopeZ;
|
||||
float localangle = acos(dotAB / (RstR * slopR));
|
||||
|
||||
if (localangle < 0 || localangle >= LAMP_CUDA_PI / 2|| isnan(localangle)) {
|
||||
d_temp_R[idx] = 0;
|
||||
d_temp_amps[idx] = 0;
|
||||
return;
|
||||
}
|
||||
else {}
|
||||
|
||||
|
||||
float ampGain = 0;
|
||||
// 求解天线方向图指向
|
||||
CUDAVectorEllipsoidal antVector = GPU_SatelliteAntDirectNormal_single(
|
||||
RstX, RstY, RstZ,
|
||||
antXaxisX[prfId], antXaxisY[prfId], antXaxisZ[prfId],
|
||||
antYaxisX[prfId], antYaxisY[prfId], antYaxisZ[prfId],
|
||||
antZaxisX[prfId], antZaxisY[prfId], antZaxisZ[prfId],
|
||||
antDirectX[prfId], antDirectY[prfId], antDirectZ[prfId]
|
||||
);
|
||||
antVector.theta = antVector.theta * r2d;
|
||||
antVector.phi = antVector.phi * r2d;
|
||||
//printf("theta: %f , phi: %f \n", antVector.theta, antVector.phi);
|
||||
if (antVector.Rho > 0) {
|
||||
//float TansantPatternGain = GPU_BillerInterpAntPattern(
|
||||
// TransAntpattern,
|
||||
// Transtarttheta, Transstartphi, Transdtheta, Transdphi, Transthetapoints, Transphipoints,
|
||||
// antVector.theta, antVector.phi);
|
||||
//float antPatternGain = GPU_BillerInterpAntPattern(
|
||||
// ReceiveAntpattern,
|
||||
// Receivestarttheta, Receivestartphi, Receivedtheta, Receivedphi, Receivethetapoints, Receivephipoints,
|
||||
// antVector.theta, antVector.phi);
|
||||
|
||||
float sigma0 = 0;
|
||||
{
|
||||
long clsid = demCls[posId];
|
||||
//printf("clsid=%d\n", clsid);
|
||||
CUDASigmaParam_single tempsigma = sigma0Paramslist[clsid];
|
||||
|
||||
|
||||
if (abs(tempsigma.p1) < PRECISIONTOLERANCE &&
|
||||
abs(tempsigma.p2) < PRECISIONTOLERANCE &&
|
||||
abs(tempsigma.p3) < PRECISIONTOLERANCE &&
|
||||
abs(tempsigma.p4) < PRECISIONTOLERANCE &&
|
||||
abs(tempsigma.p5) < PRECISIONTOLERANCE &&
|
||||
abs(tempsigma.p6) < PRECISIONTOLERANCE
|
||||
) {
|
||||
sigma0 = 0;
|
||||
}
|
||||
else {
|
||||
float sigma = GPU_getSigma0dB_single(tempsigma, localangle);
|
||||
sigma0 = powf(10.0, sigma / 10.0);
|
||||
}
|
||||
}
|
||||
//ampGain = TansantPatternGain * antPatternGain;
|
||||
ampGain = 1;
|
||||
//if (10 * log10(ampGain / maxReceiveAntPatternValue / maxTransAntPatternValue) < -3) { // 小于-3dB
|
||||
// d_temp_R[idx] = 0;
|
||||
// d_temp_amps[idx] = 0;
|
||||
// return;
|
||||
//}
|
||||
//else {}
|
||||
|
||||
|
||||
|
||||
|
||||
ampGain = ampGain / (powf(4 * LAMP_CUDA_PI, 2) * powf(RstR, 4)); // 反射强度
|
||||
|
||||
float temp_amp = float(ampGain * Pt * sigma0);
|
||||
float temp_R = float(RstR - refPhaseRange);
|
||||
|
||||
if (isnan(temp_amp) || isnan(temp_R)|| isinf(temp_amp) || isinf(temp_R)) {
|
||||
printf("amp is nan or R is nan,amp=%f;R=%f; \n", temp_amp, temp_R);
|
||||
d_temp_R[idx] = 0;
|
||||
d_temp_amps[idx] = 0;
|
||||
return;
|
||||
}
|
||||
else {}
|
||||
|
||||
|
||||
d_temp_amps[idx] = temp_amp;
|
||||
d_temp_R[idx] = temp_R;
|
||||
return;
|
||||
}
|
||||
else {
|
||||
d_temp_R[idx] = 0;
|
||||
d_temp_amps[idx] = 0;
|
||||
return;
|
||||
}
|
||||
}
|
||||
else {
|
||||
d_temp_R[idx] = 0;
|
||||
d_temp_amps[idx] = 0;
|
||||
return;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
__global__ void CUDA_Kernel_Computer_echo_single(
|
||||
float* d_temp_R, float* d_temp_amps, long posNum,
|
||||
float f0, float dfreq,
|
||||
long FreqPoints, // 当前频率的分块
|
||||
long maxfreqnum, // 最大脉冲值
|
||||
float* d_temp_echo_real, float* d_temp_echo_imag,
|
||||
long temp_PRF_Count
|
||||
) {
|
||||
__shared__ float s_R[SHAREMEMORY_FLOAT_HALF]; // 注意一个完整的block_size 共享相同内存
|
||||
__shared__ float s_amp[SHAREMEMORY_FLOAT_HALF];
|
||||
|
||||
long tid = threadIdx.x;
|
||||
long bid = blockIdx.x;
|
||||
long idx = bid * blockDim.x + tid;
|
||||
long prfId = idx / FreqPoints; // 脉冲ID
|
||||
long fId = idx % FreqPoints;//频率ID
|
||||
|
||||
long psid = 0;
|
||||
long pixelId = 0;
|
||||
for (long ii = 0; ii < SHAREMEMORY_FLOAT_HALF_STEP; ii++) { // SHAREMEMORY_FLOAT_HALF_STEP * BLOCK_SIZE=SHAREMEMORY_FLOAT_HALF
|
||||
psid = tid * SHAREMEMORY_FLOAT_HALF_STEP + ii;
|
||||
pixelId = prfId * posNum + psid; //
|
||||
if (psid < posNum) {
|
||||
s_R[psid] = d_temp_R[pixelId];
|
||||
s_amp[psid] = d_temp_amps[pixelId];
|
||||
}
|
||||
else {
|
||||
s_R[psid] = 0;
|
||||
s_amp[psid] = 0;
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
__syncthreads(); // 确定所有待处理数据都已经进入程序中
|
||||
|
||||
|
||||
|
||||
if (fId < maxfreqnum && prfId < temp_PRF_Count) {
|
||||
|
||||
long echo_ID = prfId * maxfreqnum + fId; // 计算对应的回波位置
|
||||
float factorjTemp = RFPCPIDIVLIGHT * (f0 + fId * dfreq);
|
||||
float temp_real = 0;
|
||||
float temp_imag = 0;
|
||||
float temp_phi = 0;
|
||||
float temp_amp = 0;
|
||||
for (long dataid = 0; dataid < SHAREMEMORY_FLOAT_HALF; dataid++) {
|
||||
|
||||
temp_phi = s_R[dataid] * factorjTemp;
|
||||
temp_amp = s_amp[dataid];
|
||||
temp_real += (temp_amp * cosf(temp_phi));
|
||||
temp_imag += (temp_amp * sinf(temp_phi));
|
||||
//if (dataid > 5000) {
|
||||
// printf("echo_ID=%d; dataid=%d;ehodata=(%f,%f);R=%f;amp=%f;\n", echo_ID, dataid, temp_real, temp_imag, s_R[0], s_amp[0]);
|
||||
//}
|
||||
if (isnan(temp_phi) || isnan(temp_amp) || isnan(temp_real) || isnan(temp_imag)
|
||||
|| isinf(temp_phi) || isinf(temp_amp) || isinf(temp_real) || isinf(temp_imag)
|
||||
) {
|
||||
printf("[amp,phi,real,imag]=[%f,%f,%f,%f];\n",temp_amp,temp_phi,temp_real,temp_imag);
|
||||
}
|
||||
|
||||
}
|
||||
//printf("echo_ID=%d; ehodata=(%f,%f)\n", echo_ID, temp_real, temp_imag);
|
||||
//printf("(%f %f %f) ", factorjTemp, s_amp[0], s_R[0]);
|
||||
d_temp_echo_real[echo_ID] += /*d_temp_echo_real[echo_ID] + */temp_real;
|
||||
d_temp_echo_imag[echo_ID] += /*d_temp_echo_imag[echo_ID] +*/ temp_imag;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
/**
|
||||
* 分块计算主流程
|
||||
*/
|
||||
void CUDA_RFPC_MainProcess_single(
|
||||
float* antX, float* antY, float* antZ,
|
||||
float* antXaxisX, float* antXaxisY, float* antXaxisZ,
|
||||
float* antYaxisX, float* antYaxisY, float* antYaxisZ,
|
||||
float* antZaxisX, float* antZaxisY, float* antZaxisZ,
|
||||
float* antDirectX, float* antDirectY, float* antDirectZ,
|
||||
long PRFCount, long FreqNum,
|
||||
float f0, float dfreq,
|
||||
float Pt,
|
||||
float refPhaseRange,
|
||||
float* TransAntpattern,
|
||||
float Transtarttheta, float Transstartphi, float Transdtheta, float Transdphi, int Transthetapoints, int Transphipoints,
|
||||
float* ReceiveAntpattern,
|
||||
float Receivestarttheta, float Receivestartphi, float Receivedtheta, float Receivedphi, int Receivethetapoints, int Receivephipoints,
|
||||
float maxTransAntPatternValue, float maxReceiveAntPatternValue,
|
||||
float NearR, float FarR,
|
||||
float* targetX, float* targetY, float* targetZ, long* demCls, long TargetNumber,
|
||||
float* demSlopeX, float* demSlopeY, float* demSlopeZ,
|
||||
CUDASigmaParam_single* sigma0Paramslist, long sigmaparamslistlen,
|
||||
float* out_echoReal, float* out_echoImag,
|
||||
float* d_temp_R, float* d_temp_amp
|
||||
)
|
||||
{
|
||||
long BLOCK_FREQNUM = NextBlockPad(FreqNum, BLOCK_SIZE); // 256*freqBlockID
|
||||
long cudaBlocknum = 0;
|
||||
long freqpoints = BLOCK_FREQNUM;
|
||||
printf("freqpoints:%d\n", freqpoints);
|
||||
long process = 0;
|
||||
for (long sTi = 0; sTi < TargetNumber; sTi = sTi + SHAREMEMORY_FLOAT_HALF) {
|
||||
cudaBlocknum = (PRFCount * SHAREMEMORY_FLOAT_HALF + BLOCK_SIZE - 1) / BLOCK_SIZE;
|
||||
CUDA_Kernel_Computer_R_amp_single << <cudaBlocknum, BLOCK_SIZE >> > (
|
||||
antX, antY, antZ,
|
||||
antXaxisX, antXaxisY, antXaxisZ,
|
||||
antYaxisX, antYaxisY, antYaxisZ,
|
||||
antZaxisX, antZaxisY, antZaxisZ,
|
||||
antDirectX, antDirectY, antDirectZ,
|
||||
PRFCount,
|
||||
targetX, targetY, targetZ, demCls,
|
||||
demSlopeX, demSlopeY, demSlopeZ,
|
||||
sTi, TargetNumber,
|
||||
sigma0Paramslist, sigmaparamslistlen,
|
||||
Pt,
|
||||
refPhaseRange,
|
||||
TransAntpattern,
|
||||
Transtarttheta, Transstartphi, Transdtheta, Transdphi, Transthetapoints, Transphipoints,
|
||||
ReceiveAntpattern,
|
||||
Receivestarttheta, Receivestartphi, Receivedtheta, Receivedphi, Receivethetapoints, Receivephipoints,
|
||||
maxTransAntPatternValue, maxReceiveAntPatternValue,
|
||||
NearR, FarR,
|
||||
d_temp_R, d_temp_amp// 计算输出
|
||||
);
|
||||
|
||||
PrintLasterError("CUDA_Kernel_Computer_R_amp");
|
||||
|
||||
|
||||
cudaBlocknum = (PRFCount * BLOCK_FREQNUM + BLOCK_SIZE - 1) / BLOCK_SIZE;
|
||||
CUDA_Kernel_Computer_echo_single << <cudaBlocknum, BLOCK_SIZE >> > (
|
||||
d_temp_R, d_temp_amp, SHAREMEMORY_FLOAT_HALF,
|
||||
f0, dfreq,
|
||||
freqpoints, FreqNum,
|
||||
out_echoReal, out_echoImag,
|
||||
PRFCount
|
||||
);
|
||||
PrintLasterError("CUDA_Kernel_Computer_echo");
|
||||
|
||||
if ((sTi * 100.0 / TargetNumber ) - process >= 1) {
|
||||
process = sTi * 100.0 / TargetNumber;
|
||||
PRINT("TargetID [%f]: %d / %d finished\n", sTi*100.0/ TargetNumber,sTi, TargetNumber);
|
||||
}
|
||||
|
||||
|
||||
|
||||
}
|
||||
|
||||
|
||||
cudaDeviceSynchronize();
|
||||
}
|
||||
|
||||
|
||||
#endif
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,85 @@
|
|||
#ifndef _GPURFPC_SINGLE_H_
|
||||
#define _GPURFPC_SINGLE_H_
|
||||
|
||||
#include "BaseConstVariable.h"
|
||||
#include "GPUTool.cuh"
|
||||
#include <cuda_runtime.h>
|
||||
#include <device_launch_parameters.h>
|
||||
#include <cublas_v2.h>
|
||||
#include <cuComplex.h>
|
||||
|
||||
#define RFPCPIDIVLIGHT -4*PI/(LIGHTSPEED/1e9)
|
||||
|
||||
|
||||
extern "C" struct CUDASigmaParam_single {
|
||||
float p1;
|
||||
float p2;
|
||||
float p3;
|
||||
float p4;
|
||||
float p5;
|
||||
float p6;
|
||||
};
|
||||
|
||||
extern __device__ float GPU_getSigma0dB_single(const float p1, const float p2, const float p3, const float p4, const float p5, const float p6, float theta)
|
||||
;
|
||||
|
||||
extern __device__ float GPU_getSigma0dB_single(CUDASigmaParam_single param, float theta);
|
||||
|
||||
extern __device__ CUDAVectorEllipsoidal GPU_SatelliteAntDirectNormal_single(
|
||||
float RstX, float RstY, float RstZ,
|
||||
float AntXaxisX, float AntXaxisY, float AntXaxisZ,
|
||||
float AntYaxisX, float AntYaxisY, float AntYaxisZ,
|
||||
float AntZaxisX, float AntZaxisY, float AntZaxisZ,
|
||||
float AntDirectX, float AntDirectY, float AntDirectZ
|
||||
);
|
||||
|
||||
extern __device__ float GPU_BillerInterpAntPattern_single(float* antpattern,
|
||||
float starttheta, float startphi, float dtheta, float dphi,
|
||||
long thetapoints, long phipoints,
|
||||
float searththeta, float searchphi);
|
||||
|
||||
|
||||
|
||||
extern "C" void CUDA_RFPC_MainProcess_single(
|
||||
// 天线
|
||||
float* antX, float* antY, float* antZ, // 天线坐标
|
||||
float* antXaxisX, float* antXaxisY, float* antXaxisZ, // 天线坐标系的X轴
|
||||
float* antYaxisX, float* antYaxisY, float* antYaxisZ,// 天线坐标系的Y轴
|
||||
float* antZaxisX, float* antZaxisY, float* antZaxisZ,// 天线坐标系的Z轴
|
||||
float* antDirectX, float* antDirectY, float* antDirectZ,// 天线的指向
|
||||
long PRFCount, long FreqNum, // 脉冲数量，频率数量
|
||||
float f0, float dfreq,// 起始频率，终止频率
|
||||
float Pt,// 发射能量
|
||||
float refPhaseRange,
|
||||
// 天线方向图
|
||||
float* TransAntpattern, float Transtarttheta, float Transstartphi, float Transdtheta, float Transdphi, int Transthetapoints, int Transphipoints, // 发射天线方向图
|
||||
float* ReceiveAntpattern, float Receivestarttheta, float Receivestartphi, float Receivedtheta, float Receivedphi, int Receivethetapoints, int Receivephipoints,//接收天线方向图
|
||||
float maxTransAntPatternValue,float maxReceiveAntPatternValue,
|
||||
float NearR, float FarR, // 距离范围
|
||||
|
||||
|
||||
// 地面
|
||||
float* targetX, float* targetY, float* targetZ, long* demCls, long TargetPixelNumber, // 地面坐标、地表覆盖类型，像素数
|
||||
float* demSlopeX, float* demSlopeY, float* demSlopeZ, // 地表坡度矢量
|
||||
CUDASigmaParam_single* sigma0Paramslist, long sigmaparamslistlen,// 插值图像
|
||||
|
||||
float* out_echoReal, float* out_echoImag,// 输出回波
|
||||
|
||||
float* d_temp_R, float* d_temp_amp
|
||||
);
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
#endif
|
||||
|
||||
|
||||
|
||||
|
||||
|
|
@ -222,6 +222,7 @@
|
|||
<ClCompile Include="SimulationSAR\TBPImageAlgCls.cpp" />
|
||||
<ClCompile Include="UnitTestMain.cpp" />
|
||||
<CudaCompile Include="GPUBpSimulation.cu" />
|
||||
<CudaCompile Include="SimulationSAR\GPURFPC_single.cu" />
|
||||
<CudaCompile Include="SimulationSAR\GPUTBPImage.cu" />
|
||||
<QtMoc Include="PowerSimulationIncoherent\QSimulationSARPolynomialOrbitModel.h" />
|
||||
<CudaCompile Include="PowerSimulationIncoherent\LookTableSimulationComputer.cuh" />
|
||||
|
|
@ -238,6 +239,7 @@
|
|||
<CudaCompile Include="SimulationSAR\BPBasic0_CUDA.cu" />
|
||||
<CudaCompile Include="SimulationSAR\GPUBPTool.cuh" />
|
||||
<ClInclude Include="SimulationSAR\BPBasic0_CUDA.cuh" />
|
||||
<ClInclude Include="SimulationSAR\GPURFPC_single.cuh" />
|
||||
<ClInclude Include="SimulationSAR\GPUTBPImage.cuh" />
|
||||
<ClInclude Include="SimulationSAR\RFPCProcessCls.h" />
|
||||
<ClInclude Include="SimulationSAR\SARSatelliteSimulationAbstractCls.h" />
|
||||
|
|
|
|||
|
|
@ -68,6 +68,9 @@
|
|||
<ClInclude Include="GPUBpSimulation.cuh">
|
||||
<Filter>SimulationSAR</Filter>
|
||||
</ClInclude>
|
||||
<ClInclude Include="SimulationSAR\GPURFPC_single.cuh">
|
||||
<Filter>SimulationSAR</Filter>
|
||||
</ClInclude>
|
||||
</ItemGroup>
|
||||
<ItemGroup>
|
||||
<ClCompile Include="SimulationSAR\QImageSARRFPC.cpp">
|
||||
|
|
@ -193,5 +196,8 @@
|
|||
<CudaCompile Include="GPUBpSimulation.cu">
|
||||
<Filter>SimulationSAR</Filter>
|
||||
</CudaCompile>
|
||||
<CudaCompile Include="SimulationSAR\GPURFPC_single.cu">
|
||||
<Filter>SimulationSAR</Filter>
|
||||
</CudaCompile>
|
||||
</ItemGroup>
|
||||
</Project>
|
||||
|
|
@ -44,7 +44,7 @@ void testSimualtionEchoPoint() {
|
|||
.arg(h_data.AntZ[gpspoints - 1]);
|
||||
/** 2. 成像网格 **************************************************************************************************/
|
||||
qDebug() << u8"轨道文件读取结束\n2.成像网格读取。。。";
|
||||
QString demxyzPath = u8"D:\\Programme\\vs2022\\RasterMergeTest\\simulationData\\demdataset\\demxyz.bin";
|
||||
QString demxyzPath = u8"C:\\Users\\30453\\Desktop\\script\\已修改GF3场景\\data\\demxyz.bin";
|
||||
gdalImage demgridimg(demxyzPath);
|
||||
long dem_rowCount = demgridimg.height;
|
||||
long dem_ColCount = demgridimg.width;
|
||||
|
|
@ -115,7 +115,7 @@ void testSimualtionEchoPoint() {
|
|||
/** 7. 目标 **************************************************************************************************/
|
||||
double Tx = -2029086.618142, Ty = 4139594.934504, Tz = 4392846.782027;
|
||||
double Tslx = -2029086.618142, Tsly = 4139594.934504, Tslz = 4392846.782027;
|
||||
double p1 = 33.3, p2 = 0, p3 = 0, p4 = 0, p5 = 0, p6 = 0;
|
||||
double p1 = 1, p2 = 0, p3 = 0, p4 = 0, p5 = 0, p6 = 0;
|
||||
|
||||
/** 7. 构建回波 **************************************************************************************************/
|
||||
GPUDATA d_data;
|
||||
|
|
@ -404,17 +404,405 @@ void testBpImage() {
|
|||
|
||||
}
|
||||
|
||||
//
|
||||
//
|
||||
//void testSimualtionEchoPoint_single() {
|
||||
// GPUDATA_single h_data{};
|
||||
// /** 1. 轨道 **************************************************************************************************/
|
||||
// qDebug() << u8"1.轨道文件读取中。。。";
|
||||
// QString inGPSPath = u8"C:\\Users\\30453\\Desktop\\script\\data\\GF3_Simulation.gpspos.data";
|
||||
// long gpspoints = gdalImage(inGPSPath).height;
|
||||
// std::shared_ptr<SatelliteAntPos> antpos = SatelliteAntPosOperator::readAntPosFile(inGPSPath, gpspoints);
|
||||
// h_data.AntX = (float*)mallocCUDAHost(sizeof(float) * gpspoints);
|
||||
// h_data.AntY = (float*)mallocCUDAHost(sizeof(float) * gpspoints);
|
||||
// h_data.AntZ = (float*)mallocCUDAHost(sizeof(float) * gpspoints);
|
||||
//
|
||||
// for (long i = 0; i < gpspoints; i = i + 1) {
|
||||
// h_data.AntX[i] = antpos.get()[i].Px;
|
||||
// h_data.AntY[i] = antpos.get()[i].Py;
|
||||
// h_data.AntZ[i] = antpos.get()[i].Pz;
|
||||
// }
|
||||
// //gpspoints = gpspoints / 2;
|
||||
// qDebug() << "GPS points Count:\t" << gpspoints;
|
||||
// qDebug() << "PRF 0:\t " << QString("%1,%2,%3").arg(h_data.AntX[0]).arg(h_data.AntY[0]).arg(h_data.AntZ[0]);
|
||||
// qDebug() << "PRF " << gpspoints - 1 << ":\t " << QString("%1,%2,%3")
|
||||
// .arg(h_data.AntX[gpspoints - 1])
|
||||
// .arg(h_data.AntY[gpspoints - 1])
|
||||
// .arg(h_data.AntZ[gpspoints - 1]);
|
||||
// /** 2. 成像网格 **************************************************************************************************/
|
||||
// qDebug() << u8"轨道文件读取结束\n2.成像网格读取。。。";
|
||||
// QString demxyzPath = u8"C:\\Users\\30453\\Desktop\\script\\已修改GF3场景\\data\\demxyz.bin";
|
||||
// gdalImage demgridimg(demxyzPath);
|
||||
// long dem_rowCount = demgridimg.height;
|
||||
// long dem_ColCount = demgridimg.width;
|
||||
// std::shared_ptr<float> demX = readDataArr<float>(demgridimg, 0, 0, dem_rowCount, dem_ColCount, 1, GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
|
||||
// std::shared_ptr<float> demY = readDataArr<float>(demgridimg, 0, 0, dem_rowCount, dem_ColCount, 2, GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
|
||||
// std::shared_ptr<float> demZ = readDataArr<float>(demgridimg, 0, 0, dem_rowCount, dem_ColCount, 3, GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
|
||||
//
|
||||
// h_data.x_mat = (float*)mallocCUDAHost(sizeof(float) * dem_rowCount * dem_ColCount);
|
||||
// h_data.y_mat = (float*)mallocCUDAHost(sizeof(float) * dem_rowCount * dem_ColCount);
|
||||
// h_data.z_mat = (float*)mallocCUDAHost(sizeof(float) * dem_rowCount * dem_ColCount);
|
||||
//
|
||||
// for (long i = 0; i < dem_rowCount; i++) {
|
||||
// for (long j = 0; j < dem_ColCount; j++) {
|
||||
// h_data.x_mat[i * dem_ColCount + j] = demX.get()[i * dem_ColCount + j];
|
||||
// h_data.y_mat[i * dem_ColCount + j] = demY.get()[i * dem_ColCount + j];
|
||||
// h_data.z_mat[i * dem_ColCount + j] = demZ.get()[i * dem_ColCount + j];
|
||||
// }
|
||||
// }
|
||||
// qDebug() << "dem row Count:\t" << dem_rowCount;
|
||||
// qDebug() << "dem col Count:\t" << dem_ColCount;
|
||||
//
|
||||
// qDebug() << u8"成像网格读取结束";
|
||||
// /** 3. 频率网格 **************************************************************************************************/
|
||||
// qDebug() << u8"3.处理频率";
|
||||
// float centerFreq = 5.3e9;
|
||||
// float bandwidth = 40e6;
|
||||
// long freqpoints = 2048;
|
||||
// std::shared_ptr<float> freqlist(getFreqPoints_mallocHost_single(centerFreq - bandwidth / 2, centerFreq + bandwidth / 2, freqpoints), FreeCUDAHost);
|
||||
// std::shared_ptr<float> minF(new float[gpspoints], delArrPtr);
|
||||
// for (long i = 0; i < gpspoints; i++) {
|
||||
// minF.get()[i] = freqlist.get()[0];
|
||||
// }
|
||||
// h_data.deltaF = bandwidth / (freqpoints - 1);
|
||||
// qDebug() << "start Freq:\t" << centerFreq - bandwidth / 2;
|
||||
// qDebug() << "end Freq:\t" << centerFreq + bandwidth / 2;
|
||||
// qDebug() << "freq points:\t" << freqpoints;
|
||||
// qDebug() << "delta freq:\t" << freqlist.get()[1] - freqlist.get()[0];
|
||||
// qDebug() << u8"频率结束";
|
||||
// /** 4. 初始化回波 **************************************************************************************************/
|
||||
// qDebug() << u8"4.初始化回波";
|
||||
// std::shared_ptr<cuComplex> phdata(createEchoPhase_mallocHost(gpspoints, freqpoints), FreeCUDAHost);
|
||||
// qDebug() << "Azimuth Points:\t" << gpspoints;
|
||||
// qDebug() << "Range Points:\t" << freqpoints;
|
||||
// qDebug() << u8"初始化回波结束";
|
||||
// /** 5. 初始化图像 **************************************************************************************************/
|
||||
// qDebug() << u8"5.初始化图像";
|
||||
// h_data.im_final = (cuComplex*)mallocCUDAHost(sizeof(cuComplex) * dem_rowCount * dem_ColCount);
|
||||
// qDebug() << "Azimuth Points:\t" << gpspoints;
|
||||
// qDebug() << "Range Points:\t" << freqpoints;
|
||||
// qDebug() << u8"初始化图像结束";
|
||||
//
|
||||
// /** 6. 模型参数初始化 **************************************************************************************************/
|
||||
// qDebug() << u8"6.模型参数初始化";
|
||||
//
|
||||
// h_data.nx = dem_ColCount;
|
||||
// h_data.ny = dem_rowCount;
|
||||
//
|
||||
// h_data.Np = gpspoints;
|
||||
// h_data.Freq = freqlist.get();
|
||||
// h_data.minF = minF.get();
|
||||
// h_data.Nfft = freqpoints;
|
||||
// h_data.K = h_data.Nfft;
|
||||
// h_data.phdata = phdata.get();
|
||||
// h_data.R0 = 900000;
|
||||
// qDebug() << u8"模型参数结束";
|
||||
//
|
||||
//
|
||||
// /** 7. 目标 **************************************************************************************************/
|
||||
// float Tx = -2029086.618142, Ty = 4139594.934504, Tz = 4392846.782027;
|
||||
// float Tslx = -2029086.618142, Tsly = 4139594.934504, Tslz = 4392846.782027;
|
||||
// float p1 = 1, p2 = 0, p3 = 0, p4 = 0, p5 = 0, p6 = 0;
|
||||
//
|
||||
// /** 7. 构建回波 **************************************************************************************************/
|
||||
// GPUDATA_single d_data;
|
||||
// initGPUData_single(h_data, d_data);
|
||||
//
|
||||
// RFPCProcess_single(Tx, Ty, Tz,
|
||||
// Tslx, Tsly, Tslz, // 目标的坡面向量
|
||||
// p1, p2, p3, p4, p5, p6,
|
||||
// d_data);
|
||||
//
|
||||
//
|
||||
// /** 8. 展示回波 **************************************************************************************************/
|
||||
// {
|
||||
// DeviceToHost(h_data.phdata, d_data.phdata, sizeof(cuComplex) * d_data.Np * d_data.Nfft);
|
||||
// cuComplex* h_ifftphdata = (cuComplex*)mallocCUDAHost(sizeof(cuComplex) * d_data.Np * d_data.Nfft);
|
||||
// cuComplex* d_ifftphdata = (cuComplex*)mallocCUDADevice(sizeof(cuComplex) * d_data.Np * d_data.Nfft);
|
||||
// CUDAIFFT(d_data.phdata, d_ifftphdata, d_data.Np, d_data.Nfft, d_data.Nfft);
|
||||
// FFTShift1D(d_ifftphdata, d_data.Np, d_data.Nfft);
|
||||
// DeviceToHost(h_ifftphdata, d_ifftphdata, sizeof(cuComplex) * d_data.Np * d_data.Nfft);
|
||||
// std::shared_ptr<std::complex<double>> ifftdata(new std::complex<double>[d_data.Np * d_data.Nfft], delArrPtr);
|
||||
// {
|
||||
// for (long i = 0; i < d_data.Np; i++) {
|
||||
// for (long j = 0; j < d_data.Nfft; j++) {
|
||||
// ifftdata.get()[i * d_data.Nfft + j] =
|
||||
// std::complex<double>(
|
||||
// h_ifftphdata[i * d_data.Nfft + j].x,
|
||||
// h_ifftphdata[i * d_data.Nfft + j].y);
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
// testOutComplexDoubleArr(QString("echo_ifft_single.bin"), ifftdata.get(), d_data.Np, d_data.Nfft);
|
||||
//
|
||||
// FreeCUDADevice(d_ifftphdata);
|
||||
// FreeCUDAHost(h_ifftphdata);
|
||||
//
|
||||
// }
|
||||
// /** 9. 成像 **************************************************************************************************/
|
||||
//
|
||||
// // 计算maxWr（需要先计算deltaF）
|
||||
// float deltaF = h_data.deltaF; // 从输入参数获取
|
||||
// float maxWr = 299792458.0f / (2.0f * deltaF);
|
||||
// qDebug() << "maxWr :\t" << maxWr;
|
||||
// float* r_vec_host = (float*)mallocCUDAHost(sizeof(float) * h_data.Nfft);// new float[data.Nfft];
|
||||
// const float step = maxWr / h_data.Nfft;
|
||||
// const float start = -1 * h_data.Nfft / 2.0f * step;
|
||||
// printf("nfft=%d\n", h_data.Nfft);
|
||||
//
|
||||
// for (int i = 0; i < h_data.Nfft; ++i) {
|
||||
// r_vec_host[i] = start + i * step;
|
||||
// }
|
||||
//
|
||||
// h_data.r_vec = r_vec_host;
|
||||
// d_data.r_vec = h_data.r_vec;
|
||||
//
|
||||
// qDebug() << "r_vec [0]:\t" << h_data.r_vec[0];
|
||||
// qDebug() << "r_vec step:\t" << step;
|
||||
//
|
||||
// bpBasic0CUDA_single(d_data, 0);
|
||||
//
|
||||
// DeviceToHost(h_data.im_final, d_data.im_final, sizeof(cuComplex) * d_data.nx * d_data.ny);
|
||||
//
|
||||
// {
|
||||
// DeviceToHost(h_data.phdata, d_data.phdata, sizeof(cuComplex) * d_data.Np * d_data.Nfft);
|
||||
// std::shared_ptr<std::complex<double>> ifftdata(new std::complex<double>[d_data.Np * d_data.Nfft], delArrPtr);
|
||||
// {
|
||||
// for (long i = 0; i < d_data.Np; i++) {
|
||||
// for (long j = 0; j < d_data.Nfft; j++) {
|
||||
// ifftdata.get()[i * d_data.Nfft + j] =
|
||||
// std::complex<double>(
|
||||
// h_data.phdata[i * d_data.Nfft + j].x,
|
||||
// h_data.phdata[i * d_data.Nfft + j].y);
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
// testOutComplexDoubleArr(QString("echo_ifft_BPBasic_single.bin"), ifftdata.get(), d_data.Np, d_data.Nfft);
|
||||
//
|
||||
//
|
||||
//
|
||||
// std::shared_ptr<std::complex<double>> im_finals(new std::complex<double>[d_data.nx * d_data.ny], delArrPtr);
|
||||
// {
|
||||
// for (long i = 0; i < d_data.ny; i++) {
|
||||
// for (long j = 0; j < d_data.nx; j++) {
|
||||
// im_finals.get()[i * d_data.nx + j] = std::complex<double>(
|
||||
// h_data.im_final[i * d_data.nx + j].x,
|
||||
// h_data.im_final[i * d_data.nx + j].y);
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
// testOutComplexDoubleArr(QString("im_finals_single.bin"), im_finals.get(), d_data.ny, d_data.nx);
|
||||
// }
|
||||
//}
|
||||
//
|
||||
//
|
||||
//void testBpImage_single() {
|
||||
//
|
||||
// GPUDATA_single h_data{};
|
||||
// /** 0. 轨道 **************************************************************************************************/
|
||||
// QString echoPath = "D:\\Programme\\vs2022\\RasterMergeTest\\LAMPCAE_SCANE-all-scane\\GF3_Simulation.xml";
|
||||
// std::shared_ptr<EchoL0Dataset> echoL0ds(new EchoL0Dataset);
|
||||
// echoL0ds->Open(echoPath);
|
||||
// qDebug() << u8"加载回拨文件：\t" << echoPath;
|
||||
//
|
||||
// /** 1. 轨道 **************************************************************************************************/
|
||||
// qDebug() << u8"1.轨道文件读取中。。。";
|
||||
// QString inGPSPath = echoL0ds->getGPSPointFilePath();
|
||||
// long gpspoints = gdalImage(inGPSPath).height;
|
||||
// std::shared_ptr<SatelliteAntPos> antpos = SatelliteAntPosOperator::readAntPosFile(inGPSPath, gpspoints);
|
||||
// h_data.AntX = (float*)mallocCUDAHost(sizeof(float) * gpspoints);
|
||||
// h_data.AntY = (float*)mallocCUDAHost(sizeof(float) * gpspoints);
|
||||
// h_data.AntZ = (float*)mallocCUDAHost(sizeof(float) * gpspoints);
|
||||
//
|
||||
// for (long i = 0; i < gpspoints; i = i + 1) {
|
||||
// h_data.AntX[i] = antpos.get()[i].Px;
|
||||
// h_data.AntY[i] = antpos.get()[i].Py;
|
||||
// h_data.AntZ[i] = antpos.get()[i].Pz;
|
||||
// }
|
||||
// //gpspoints = gpspoints / 2;
|
||||
// qDebug() << "GPS points Count:\t" << gpspoints;
|
||||
// qDebug() << "PRF 0:\t " << QString("%1,%2,%3").arg(h_data.AntX[0]).arg(h_data.AntY[0]).arg(h_data.AntZ[0]);
|
||||
// qDebug() << "PRF " << gpspoints - 1 << ":\t " << QString("%1,%2,%3")
|
||||
// .arg(h_data.AntX[gpspoints - 1])
|
||||
// .arg(h_data.AntY[gpspoints - 1])
|
||||
// .arg(h_data.AntZ[gpspoints - 1]);
|
||||
// /** 2. 成像网格 **************************************************************************************************/
|
||||
// qDebug() << u8"轨道文件读取结束\n2.成像网格读取。。。";
|
||||
// QString demxyzPath = u8"D:\\Programme\\vs2022\\RasterMergeTest\\simulationData\\demdataset\\demxyz.bin";
|
||||
// gdalImage demgridimg(demxyzPath);
|
||||
// long dem_rowCount = demgridimg.height;
|
||||
// long dem_ColCount = demgridimg.width;
|
||||
// std::shared_ptr<double> demX = readDataArr<double>(demgridimg, 0, 0, dem_rowCount, dem_ColCount, 1, GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
|
||||
// std::shared_ptr<double> demY = readDataArr<double>(demgridimg, 0, 0, dem_rowCount, dem_ColCount, 2, GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
|
||||
// std::shared_ptr<double> demZ = readDataArr<double>(demgridimg, 0, 0, dem_rowCount, dem_ColCount, 3, GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
|
||||
//
|
||||
// h_data.x_mat = (float*)mallocCUDAHost(sizeof(float) * dem_rowCount * dem_ColCount);
|
||||
// h_data.y_mat = (float*)mallocCUDAHost(sizeof(float) * dem_rowCount * dem_ColCount);
|
||||
// h_data.z_mat = (float*)mallocCUDAHost(sizeof(float) * dem_rowCount * dem_ColCount);
|
||||
//
|
||||
// for (long i = 0; i < dem_rowCount; i++) {
|
||||
// for (long j = 0; j < dem_ColCount; j++) {
|
||||
// h_data.x_mat[i * dem_ColCount + j] = demX.get()[i * dem_ColCount + j];
|
||||
// h_data.y_mat[i * dem_ColCount + j] = demY.get()[i * dem_ColCount + j];
|
||||
// h_data.z_mat[i * dem_ColCount + j] = demZ.get()[i * dem_ColCount + j];
|
||||
// }
|
||||
// }
|
||||
// qDebug() << "dem row Count:\t" << dem_rowCount;
|
||||
// qDebug() << "dem col Count:\t" << dem_ColCount;
|
||||
//
|
||||
// qDebug() << u8"成像网格读取结束";
|
||||
// /** 3. 频率网格 **************************************************************************************************/
|
||||
// qDebug() << u8"3.处理频率";
|
||||
// float centerFreq = echoL0ds->getCenterFreq();
|
||||
// float bandwidth = echoL0ds->getBandwidth();
|
||||
// size_t freqpoints = echoL0ds->getPlusePoints();
|
||||
// std::shared_ptr<float> freqlist(getFreqPoints_mallocHost_single(centerFreq - bandwidth / 2, centerFreq + bandwidth / 2, freqpoints), FreeCUDAHost);
|
||||
// std::shared_ptr<float> minF(new float[gpspoints], delArrPtr);
|
||||
// for (long i = 0; i < gpspoints; i++) {
|
||||
// minF.get()[i] = freqlist.get()[0];
|
||||
// }
|
||||
// h_data.deltaF = bandwidth / (freqpoints - 1);
|
||||
// qDebug() << "start Freq:\t" << centerFreq - bandwidth / 2;
|
||||
// qDebug() << "end Freq:\t" << centerFreq + bandwidth / 2;
|
||||
// qDebug() << "freq points:\t" << freqpoints;
|
||||
// qDebug() << "delta freq:\t" << freqlist.get()[1] - freqlist.get()[0];
|
||||
// qDebug() << u8"频率结束";
|
||||
// /** 4. 初始化回波 **************************************************************************************************/
|
||||
// qDebug() << u8"4.初始化回波";
|
||||
// std::shared_ptr<std::complex<double>> echoData = echoL0ds->getEchoArr();
|
||||
// size_t echosize = sizeof(cuComplex) * gpspoints * freqpoints;
|
||||
// qDebug() << "echo data size (byte) :\t" << echosize;
|
||||
// h_data.phdata = (cuComplex*)mallocCUDAHost(echosize);
|
||||
// shared_complexPtrToHostCuComplex(echoData.get(), h_data.phdata, gpspoints * freqpoints);
|
||||
//
|
||||
// qDebug() << "Azimuth Points:\t" << gpspoints;
|
||||
// qDebug() << "Range Points:\t" << freqpoints;
|
||||
// qDebug() << u8"初始化回波结束";
|
||||
// /** 5. 初始化图像 **************************************************************************************************/
|
||||
// qDebug() << u8"5.初始化图像";
|
||||
// h_data.im_final = (cuComplex*)mallocCUDAHost(sizeof(cuComplex) * dem_rowCount * dem_ColCount);
|
||||
// qDebug() << "Azimuth Points:\t" << gpspoints;
|
||||
// qDebug() << "Range Points:\t" << freqpoints;
|
||||
// qDebug() << u8"初始化图像结束";
|
||||
//
|
||||
// /** 6. 模型参数初始化 **************************************************************************************************/
|
||||
// qDebug() << u8"6.模型参数初始化";
|
||||
//
|
||||
// h_data.nx = dem_ColCount;
|
||||
// h_data.ny = dem_rowCount;
|
||||
//
|
||||
// h_data.Np = gpspoints;
|
||||
// h_data.Freq = freqlist.get();
|
||||
// h_data.minF = minF.get();
|
||||
// h_data.Nfft = freqpoints;
|
||||
// h_data.K = h_data.Nfft;
|
||||
//
|
||||
// h_data.R0 = echoL0ds->getRefPhaseRange();
|
||||
// qDebug() << u8"模型参数结束";
|
||||
//
|
||||
//
|
||||
// /** 7. 目标 **************************************************************************************************/
|
||||
// double Tx = -2029086.618142, Ty = 4139594.934504, Tz = 4392846.782027;
|
||||
// double Tslx = -2029086.618142, Tsly = 4139594.934504, Tslz = 4392846.782027;
|
||||
// double p1 = 33.3, p2 = 0, p3 = 0, p4 = 0, p5 = 0, p6 = 0;
|
||||
//
|
||||
// /** 7. 构建回波 **************************************************************************************************/
|
||||
// GPUDATA_single d_data;
|
||||
// initGPUData_single(h_data, d_data);
|
||||
//
|
||||
// /** 8. 展示回波 **************************************************************************************************/
|
||||
// {
|
||||
// DeviceToHost(h_data.phdata, d_data.phdata, sizeof(cuComplex) * d_data.Np * d_data.Nfft);
|
||||
// cuComplex* h_ifftphdata = (cuComplex*)mallocCUDAHost(sizeof(cuComplex) * d_data.Np * d_data.Nfft);
|
||||
// cuComplex* d_ifftphdata = (cuComplex*)mallocCUDADevice(sizeof(cuComplex) * d_data.Np * d_data.Nfft);
|
||||
// CUDAIFFT(d_data.phdata, d_ifftphdata, d_data.Np, d_data.Nfft, d_data.Nfft);
|
||||
// FFTShift1D(d_ifftphdata, d_data.Np, d_data.Nfft);
|
||||
// DeviceToHost(h_ifftphdata, d_ifftphdata, sizeof(cuComplex) * d_data.Np * d_data.Nfft);
|
||||
// std::shared_ptr<std::complex<double>> ifftdata(new std::complex<double>[d_data.Np * d_data.Nfft], delArrPtr);
|
||||
// {
|
||||
// for (long i = 0; i < d_data.Np; i++) {
|
||||
// for (long j = 0; j < d_data.Nfft; j++) {
|
||||
// ifftdata.get()[i * d_data.Nfft + j] =
|
||||
// std::complex<double>(
|
||||
// h_ifftphdata[i * d_data.Nfft + j].x,
|
||||
// h_ifftphdata[i * d_data.Nfft + j].y);
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
// testOutComplexDoubleArr(QString("echo_ifft_single.bin"), ifftdata.get(), d_data.Np, d_data.Nfft);
|
||||
//
|
||||
// FreeCUDADevice(d_ifftphdata);
|
||||
// FreeCUDAHost(h_ifftphdata);
|
||||
//
|
||||
// }
|
||||
// /** 9. 成像 **************************************************************************************************/
|
||||
//
|
||||
// // 计算maxWr（需要先计算deltaF）
|
||||
// double deltaF = h_data.deltaF; // 从输入参数获取
|
||||
// double maxWr = 299792458.0f / (2.0f * deltaF);
|
||||
// qDebug() << "maxWr :\t" << maxWr;
|
||||
// float* r_vec_host = (float*)mallocCUDAHost(sizeof(float) * h_data.Nfft);// new double[data.Nfft];
|
||||
// const double step = maxWr / h_data.Nfft;
|
||||
// const double start = -1 * h_data.Nfft / 2.0f * step;
|
||||
// printf("nfft=%d\n", h_data.Nfft);
|
||||
//
|
||||
// for (int i = 0; i < h_data.Nfft; ++i) {
|
||||
// r_vec_host[i] = start + i * step;
|
||||
// }
|
||||
//
|
||||
// h_data.r_vec = r_vec_host;
|
||||
// d_data.r_vec = h_data.r_vec;
|
||||
//
|
||||
// qDebug() << "r_vec [0]:\t" << h_data.r_vec[0];
|
||||
// qDebug() << "r_vec step:\t" << step;
|
||||
//
|
||||
// bpBasic0CUDA_single(d_data, 0);
|
||||
//
|
||||
// DeviceToHost(h_data.im_final, d_data.im_final, sizeof(cuComplex) * d_data.nx * d_data.ny);
|
||||
// {
|
||||
// DeviceToHost(h_data.phdata, d_data.phdata, sizeof(cuComplex) * d_data.Np * d_data.Nfft);
|
||||
// std::shared_ptr<std::complex<double>> ifftdata(new std::complex<double>[d_data.Np * d_data.Nfft], delArrPtr);
|
||||
// {
|
||||
// for (long i = 0; i < d_data.Np; i++) {
|
||||
// for (long j = 0; j < d_data.Nfft; j++) {
|
||||
// ifftdata.get()[i * d_data.Nfft + j] =
|
||||
// std::complex<double>(
|
||||
// h_data.phdata[i * d_data.Nfft + j].x,
|
||||
// h_data.phdata[i * d_data.Nfft + j].y);
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
// testOutComplexDoubleArr(QString("echo_ifft_BPBasic_single.bin"), ifftdata.get(), d_data.Np, d_data.Nfft);
|
||||
//
|
||||
// std::shared_ptr<std::complex<double>> im_finals(new std::complex<double>[d_data.nx * d_data.ny], delArrPtr);
|
||||
// {
|
||||
// for (long i = 0; i < d_data.ny; i++) {
|
||||
// for (long j = 0; j < d_data.nx; j++) {
|
||||
// im_finals.get()[i * d_data.nx + j] = std::complex<double>(
|
||||
// h_data.im_final[i * d_data.nx + j].x,
|
||||
// h_data.im_final[i * d_data.nx + j].y);
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
// testOutComplexDoubleArr(QString("im_finals_single.bin"), im_finals.get(), d_data.ny, d_data.nx);
|
||||
// }
|
||||
//
|
||||
//
|
||||
//
|
||||
//}
|
||||
//
|
||||
|
||||
|
||||
|
||||
//
|
||||
//int main(int argc, char* argv[]) {
|
||||
//
|
||||
// QApplication a(argc, argv);
|
||||
//
|
||||
// testBpImage();
|
||||
//
|
||||
//
|
||||
// return 0;
|
||||
//}
|
||||
|
||||
|
||||
//
|
||||
//
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue