599 lines
19 KiB
Plaintext
599 lines
19 KiB
Plaintext
#include <iostream>
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#include <memory>
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#include <cmath>
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#include <complex>
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#include <device_launch_parameters.h>
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#include <cuda_runtime.h>
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#include <cublas_v2.h>
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#include <cuComplex.h>
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#include "BaseConstVariable.h"
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#include "GPURFPC.cuh"
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#ifdef __CUDANVCC___
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__device__ float GPU_getSigma0dB(CUDASigmaParam param, float theta) {//线性值
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float sigma = param.p1 + param.p2 * exp(-param.p3 * theta) + param.p4 * cos(param.p5 * theta + param.p6);
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return sigma;
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}
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__device__ CUDAVectorEllipsoidal GPU_SatelliteAntDirectNormal(
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float RstX, float RstY, float RstZ,
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float antXaxisX, float antXaxisY, float antXaxisZ,
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float antYaxisX, float antYaxisY, float antYaxisZ,
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float antZaxisX, float antZaxisY, float antZaxisZ,
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float antDirectX, float antDirectY, float antDirectZ
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) {
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CUDAVectorEllipsoidal result{ 0,0,-1 };
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// 求解天线增益
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float Xst = -1 * RstX; // 卫星 --> 地面
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float Yst = -1 * RstY;
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float Zst = -1 * RstZ;
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float AntXaxisX = antXaxisX;
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float AntXaxisY = antXaxisY;
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float AntXaxisZ = antXaxisZ;
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float AntYaxisX = antYaxisX;
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float AntYaxisY = antYaxisY;
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float AntYaxisZ = antYaxisZ;
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float AntZaxisX = antZaxisX;
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float AntZaxisY = antZaxisY;
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float AntZaxisZ = antZaxisZ;
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// 归一化
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float RstNorm = sqrtf(Xst * Xst + Yst * Yst + Zst * Zst);
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float AntXaxisNorm = sqrtf(AntXaxisX * AntXaxisX + AntXaxisY * AntXaxisY + AntXaxisZ * AntXaxisZ);
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float AntYaxisNorm = sqrtf(AntYaxisX * AntYaxisX + AntYaxisY * AntYaxisY + AntYaxisZ * AntYaxisZ);
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float AntZaxisNorm = sqrtf(AntZaxisX * AntZaxisX + AntZaxisY * AntZaxisY + AntZaxisZ * AntZaxisZ);
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float Rx = Xst / RstNorm;
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float Ry = Yst / RstNorm;
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float Rz = Zst / RstNorm;
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float Xx = AntXaxisX / AntXaxisNorm;
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float Xy = AntXaxisY / AntXaxisNorm;
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float Xz = AntXaxisZ / AntXaxisNorm;
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float Yx = AntYaxisX / AntYaxisNorm;
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float Yy = AntYaxisY / AntYaxisNorm;
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float Yz = AntYaxisZ / AntYaxisNorm;
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float Zx = AntZaxisX / AntZaxisNorm;
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float Zy = AntZaxisY / AntZaxisNorm;
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float Zz = AntZaxisZ / AntZaxisNorm;
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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);
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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);
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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);
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// 计算theta 与 phi
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float Norm = sqrtf(Xant * Xant + Yant * Yant + Zant * Zant); // 计算 pho
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float ThetaAnt = acosf(Zant / Norm); // theta 与 Z轴的夹角
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float PhiAnt = atanf(Yant / Xant); // -pi/2 ~pi/2
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if (abs(Yant) < PRECISIONTOLERANCE) { // X轴上
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PhiAnt = 0;
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}
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else if (abs(Xant) < PRECISIONTOLERANCE) { // Y轴上，原点
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if (Yant > 0) {
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PhiAnt = PI / 2;
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}
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else {
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PhiAnt = -PI / 2;
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}
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}
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else if (Xant < 0) {
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if (Yant > 0) {
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PhiAnt = PI + PhiAnt;
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}
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else {
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PhiAnt = -PI + PhiAnt;
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}
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}
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else { // Xant>0 X 正轴
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}
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if (isnan(PhiAnt)) {
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printf("V=[%f,%f,%f];norm=%f;thetaAnt=%f;phiAnt=%f;\n", Xant, Yant, Zant, Norm, ThetaAnt, PhiAnt);
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}
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result.theta = ThetaAnt;
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result.phi = PhiAnt;
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result.Rho = Norm;
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return result;
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}
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__device__ float GPU_BillerInterpAntPattern(float* antpattern,
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float starttheta, float startphi, float dtheta, float dphi,
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long thetapoints, long phipoints,
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float searththeta, float searchphi) {
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float stheta = searththeta;
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float sphi = searchphi;
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if (stheta > 90) {
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return 0;
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}
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else {}
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float pthetaid = (stheta - starttheta) / dtheta;//
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float pphiid = (sphi - startphi) / dphi;
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long lasttheta = floorf(pthetaid);
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long nextTheta = lasttheta + 1;
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long lastphi = floorf(pphiid);
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long nextPhi = lastphi + 1;
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if (lasttheta < 0 || nextTheta < 0 || lastphi < 0 || nextPhi < 0 ||
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lasttheta >= thetapoints || nextTheta >= thetapoints || lastphi >= phipoints || nextPhi >= phipoints)
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{
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return 0;
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}
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else {
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float x = stheta;
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float y = sphi;
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float x1 = lasttheta * dtheta + starttheta;
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float x2 = nextTheta * dtheta + starttheta;
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float y1 = lastphi * dphi + startphi;
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float y2 = nextPhi * dphi + startphi;
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float z11 = antpattern[lasttheta * phipoints + lastphi];
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float z12 = antpattern[lasttheta * phipoints + nextPhi];
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float z21 = antpattern[nextTheta * phipoints + lastphi];
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float z22 = antpattern[nextTheta * phipoints + nextPhi];
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//z11 = powf(10, z11 / 10); // dB-> 线性
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//z12 = powf(10, z12 / 10);
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//z21 = powf(10, z21 / 10);
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//z22 = powf(10, z22 / 10);
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float GainValue = (z11 * (x2 - x) * (y2 - y)
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+ z21 * (x - x1) * (y2 - y)
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+ z12 * (x2 - x) * (y - y1)
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+ z22 * (x - x1) * (y - y1));
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GainValue = GainValue / ((x2 - x1) * (y2 - y1));
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return GainValue;
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}
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}
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__device__ cuComplex GPU_calculationEcho(float sigma0, float TransAnt, float ReciveAnt,
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float localangle, float R, float slopeangle, float Pt, float lamda) {
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float amp = Pt * TransAnt * ReciveAnt;
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amp = amp * sigma0;
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amp = amp / (powf(4 * LAMP_CUDA_PI, 2) * powf(R, 4)); // 反射强度
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float phi = (-4 * LAMP_CUDA_PI / lamda) * R;
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cuComplex echophi = make_cuComplex(0, phi);
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cuComplex echophiexp = cuCexpf(echophi);
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cuComplex echo = make_cuComplex(echophiexp.x * amp, echophiexp.y * amp);
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return echo;
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}
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__global__ void CUDA_SatelliteAntDirectNormal(float* RstX, float* RstY, float* RstZ,
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float antXaxisX, float antXaxisY, float antXaxisZ,
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float antYaxisX, float antYaxisY, float antYaxisZ,
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float antZaxisX, float antZaxisY, float antZaxisZ,
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float antDirectX, float antDirectY, float antDirectZ,
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float* thetaAnt, float* phiAnt
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, long len) {
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long idx = blockIdx.x * blockDim.x + threadIdx.x;
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if (idx < len) {
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float Xst = -1 * RstX[idx]; // 卫星 --> 地面
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float Yst = -1 * RstY[idx];
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float Zst = -1 * RstZ[idx];
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float AntXaxisX = antXaxisX;
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float AntXaxisY = antXaxisY;
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float AntXaxisZ = antXaxisZ;
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float AntYaxisX = antYaxisX;
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float AntYaxisY = antYaxisY;
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float AntYaxisZ = antYaxisZ;
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float AntZaxisX = antZaxisX;
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float AntZaxisY = antZaxisY;
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float AntZaxisZ = antZaxisZ;
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// 归一化
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float RstNorm = sqrtf(Xst * Xst + Yst * Yst + Zst * Zst);
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float AntXaxisNorm = sqrtf(AntXaxisX * AntXaxisX + AntXaxisY * AntXaxisY + AntXaxisZ * AntXaxisZ);
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float AntYaxisNorm = sqrtf(AntYaxisX * AntYaxisX + AntYaxisY * AntYaxisY + AntYaxisZ * AntYaxisZ);
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float AntZaxisNorm = sqrtf(AntZaxisX * AntZaxisX + AntZaxisY * AntZaxisY + AntZaxisZ * AntZaxisZ);
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float Rx = Xst / RstNorm;
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float Ry = Yst / RstNorm;
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float Rz = Zst / RstNorm;
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float Xx = AntXaxisX / AntXaxisNorm;
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float Xy = AntXaxisY / AntXaxisNorm;
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float Xz = AntXaxisZ / AntXaxisNorm;
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float Yx = AntYaxisX / AntYaxisNorm;
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float Yy = AntYaxisY / AntYaxisNorm;
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float Yz = AntYaxisZ / AntYaxisNorm;
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float Zx = AntZaxisX / AntZaxisNorm;
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float Zy = AntZaxisY / AntZaxisNorm;
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float Zz = AntZaxisZ / AntZaxisNorm;
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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);
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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);
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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);
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// 计算theta 与 phi
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float Norm = sqrtf(Xant * Xant + Yant * Yant + Zant * Zant); // 计算 pho
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float ThetaAnt = acosf(Zant / Norm); // theta 与 Z轴的夹角
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float PhiAnt = atanf(Yant / Xant); // -pi/2 ~pi/2
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if (abs(Yant) < PRECISIONTOLERANCE) { // X轴上
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PhiAnt = 0;
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}
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else if (abs(Xant) < PRECISIONTOLERANCE) { // Y轴上，原点
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if (Yant > 0) {
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PhiAnt = PI / 2;
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}
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else {
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PhiAnt = -PI / 2;
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}
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}
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else if (Xant < 0) {
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if (Yant > 0) {
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PhiAnt = PI + PhiAnt;
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}
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else {
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PhiAnt = -PI + PhiAnt;
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}
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}
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else { // Xant>0 X 正轴
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}
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if (isnan(PhiAnt)) {
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printf("V=[%f,%f,%f];norm=%f;thetaAnt=%f;phiAnt=%f;\n", Xant, Yant, Zant, Norm, ThetaAnt, PhiAnt);
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}
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//if (abs(ThetaAnt - 0) < PRECISIONTOLERANCE) {
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// PhiAnt = 0;
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//}
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//else {}
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thetaAnt[idx] = ThetaAnt * r2d;
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phiAnt[idx] = PhiAnt * r2d;
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//printf("Rst=[%f,%f,%f];AntXaxis = [%f, %f, %f];AntYaxis=[%f,%f,%f];AntZaxis=[%f,%f,%f];phiAnt=%f;thetaAnt=%f;\n", Xst, Yst, Zst
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// , AntXaxisX, AntXaxisY, AntXaxisZ
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// , AntYaxisX, AntYaxisY, AntYaxisZ
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// , AntZaxisX, AntZaxisY, AntZaxisZ
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// , phiAnt[idx]
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// , thetaAnt[idx]
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//);
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}
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}
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__global__ void CUDA_BillerInterpAntPattern(float* antpattern,
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float starttheta, float startphi, float dtheta, float dphi,
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long thetapoints, long phipoints,
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float* searththeta, float* searchphi, float* searchantpattern,
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long len) {
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long idx = blockIdx.x * blockDim.x + threadIdx.x;
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if (idx < len) {
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float stheta = searththeta[idx];
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float sphi = searchphi[idx];
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float pthetaid = (stheta - starttheta) / dtheta;//
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float pphiid = (sphi - startphi) / dphi;
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long lasttheta = floorf(pthetaid);
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long nextTheta = lasttheta + 1;
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long lastphi = floorf(pphiid);
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long nextPhi = lastphi + 1;
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if (lasttheta < 0 || nextTheta < 0 || lastphi < 0 || nextPhi < 0 ||
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lasttheta >= thetapoints || nextTheta >= thetapoints || lastphi >= phipoints || nextPhi >= phipoints)
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{
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searchantpattern[idx] = 0;
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}
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else {
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float x = stheta;
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float y = sphi;
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float x1 = lasttheta * dtheta + starttheta;
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float x2 = nextTheta * dtheta + starttheta;
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float y1 = lastphi * dphi + startphi;
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float y2 = nextPhi * dphi + startphi;
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float z11 = antpattern[lasttheta * phipoints + lastphi];
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float z12 = antpattern[lasttheta * phipoints + nextPhi];
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float z21 = antpattern[nextTheta * phipoints + lastphi];
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float z22 = antpattern[nextTheta * phipoints + nextPhi];
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z11 = powf(10, z11 / 10);
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z12 = powf(10, z12 / 10);
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z21 = powf(10, z21 / 10);
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z22 = powf(10, z22 / 10);
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float GainValue = (z11 * (x2 - x) * (y2 - y)
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+ z21 * (x - x1) * (y2 - y)
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+ z12 * (x2 - x) * (y - y1)
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+ z22 * (x - x1) * (y - y1));
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GainValue = GainValue / ((x2 - x1) * (y2 - y1));
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searchantpattern[idx] = GainValue;
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}
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}
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}
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__global__ void CUDA_calculationEcho(float* sigma0, float* TransAnt, float* ReciveAnt,
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float* localangle, float* R, float* slopeangle,
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float nearRange, float Fs, float Pt, float lamda, long FreqIDmax,
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cuComplex* echoArr, long* FreqID,
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long len) {
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long idx = blockIdx.x * blockDim.x + threadIdx.x;
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if (idx < len) {
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float r = R[idx];
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float amp = Pt * TransAnt[idx] * ReciveAnt[idx];
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amp = amp * sigma0[idx];
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amp = amp / (powf(4 * LAMP_CUDA_PI, 2) * powf(r, 4)); // 反射强度
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// 处理相位
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float phi = (-4 * LAMP_CUDA_PI / lamda) * r;
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cuComplex echophi = make_cuComplex(0, phi);
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cuComplex echophiexp = cuCexpf(echophi);
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float timeR = 2 * (r - nearRange) / LIGHTSPEED * Fs;
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long timeID = floorf(timeR);
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//if (timeID < 0 || timeID >= FreqIDmax) {
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// timeID = 0;
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// amp = 0;
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//}
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cuComplex echo = make_cuComplex(echophiexp.x, echophiexp.y);
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echoArr[idx] = echo;
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FreqID[idx] = timeID;
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}
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}
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__global__ void CUDA_AntPatternInterpGain(float* anttheta, float* antphi, float* gain,
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float* antpattern, float starttheta, float startphi, float dtheta, float dphi, int thetapoints, int phipoints, long len) {
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int idx = blockIdx.x * blockDim.x + threadIdx.x;
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if (idx < len) {
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float temptheta = anttheta[idx];
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float tempphi = antphi[idx];
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float antPatternGain = GPU_BillerInterpAntPattern(antpattern,
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starttheta, startphi, dtheta, dphi, thetapoints, phipoints,
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temptheta, tempphi);
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gain[idx] = antPatternGain;
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}
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}
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__global__ void CUDA_InterpSigma(
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long* demcls, float* sigmaAmp, float* localanglearr, long len,
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CUDASigmaParam* sigma0Paramslist, long sigmaparamslistlen) {
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long idx = blockIdx.x * blockDim.x + threadIdx.x;
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if (idx < len) {
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long clsid = demcls[idx];
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float localangle = localanglearr[idx];
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CUDASigmaParam tempsigma = sigma0Paramslist[clsid];
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if (localangle < 0 || localangle >= LAMP_CUDA_PI / 2) {
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sigmaAmp[idx] = 0;
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}
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else {}
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if (abs(tempsigma.p1) < PRECISIONTOLERANCE &&
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abs(tempsigma.p2) < PRECISIONTOLERANCE &&
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abs(tempsigma.p3) < PRECISIONTOLERANCE &&
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abs(tempsigma.p4) < PRECISIONTOLERANCE &&
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abs(tempsigma.p5) < PRECISIONTOLERANCE &&
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abs(tempsigma.p6) < PRECISIONTOLERANCE
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) {
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sigmaAmp[idx] = 0;
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}
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else {
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float sigma = GPU_getSigma0dB(tempsigma, localangle);
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sigma = powf(10.0, sigma / 10.0);// 后向散射系数
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//printf("cls:%d;localangle=%f;sigma0=%f;\n", clsid, localangle, sigma);
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sigmaAmp[idx] = sigma;
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}
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}
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}
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__global__ void CUDAKernel_RFPC_Caluation_R_Gain(
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float antX, float antY, float antZ, // 天线的坐标
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float* targetX, float* targetY, float* targetZ, long len, // 地面坐标
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long* demCls,
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||
float* demSlopeX, float* demSlopeY, float* demSlopeZ, // 地表坡度矢量
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float antXaxisX, float antXaxisY, float antXaxisZ, // 天线坐标系的X轴
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float antYaxisX, float antYaxisY, float antYaxisZ,// 天线坐标系的Y轴
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float antZaxisX, float antZaxisY, float antZaxisZ,// 天线坐标系的Z轴
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||
float antDirectX, float antDirectY, float antDirectZ,// 天线的指向
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||
float Pt,// 发射能量
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||
double refPhaseRange,
|
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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 NearR, float FarR, // 距离范围
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CUDASigmaParam* sigma0Paramslist, long sigmaparamslistlen,// 插值图
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||
float* factorj, long freqnum,
|
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double* outR, // 输出距离
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float* outAmp // 输出增益
|
||
) {
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||
long idx = blockIdx.x * blockDim.x + threadIdx.x;
|
||
if (idx < len) {
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double tx = targetX[idx];
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double ty = targetY[idx];
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||
double tz = targetZ[idx];
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double RstX = antX - tx; // 计算坐标矢量
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||
double RstY = antY - ty;
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||
double RstZ = antZ - tz;
|
||
|
||
float slopeX = demSlopeX[idx];
|
||
float slopeY = demSlopeY[idx];
|
||
float slopeZ = demSlopeZ[idx];
|
||
|
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double RstR2 = RstX * RstX + RstY * RstY + RstZ * RstZ;
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double RstR = sqrt(RstR2); // 矢量距离
|
||
|
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//printf("antX=%f;antY=%f;antZ=%f;targetX=%f;targetY=%f;targetZ=%f;RstR=%.6f;diffR=%.6f;\n",antX,antY,antZ,targetX,targetY,targetZ,RstR, RstR - 9.010858499003178e+05);
|
||
|
||
if (RstR<NearR || RstR>FarR) {
|
||
outAmp[idx] = 0;
|
||
outR[idx] = 0;
|
||
}
|
||
else {
|
||
// 求解坡度
|
||
float slopR = sqrtf(slopeX * slopeX + slopeY * slopeY + slopeZ * slopeZ); //
|
||
float dotAB = RstX * slopeX + RstY * slopeY + RstZ * slopeZ;
|
||
float localangle = acosf(dotAB / (RstR * slopR)); // 局地入射角
|
||
float ampGain = 0;
|
||
// 求解天线方向图指向
|
||
CUDAVectorEllipsoidal antVector = GPU_SatelliteAntDirectNormal(
|
||
RstX, RstY, RstZ,
|
||
antXaxisX, antXaxisY, antXaxisZ,
|
||
antYaxisX, antYaxisY, antYaxisZ,
|
||
antZaxisX, antZaxisY, antZaxisZ,
|
||
antDirectX, antDirectY, antDirectZ
|
||
);
|
||
if (antVector.Rho > 0) {
|
||
// 发射方向图
|
||
float temptheta = antVector.theta * r2d;
|
||
float tempphi = antVector.phi * r2d;
|
||
float TansantPatternGain =
|
||
GPU_BillerInterpAntPattern(
|
||
TransAntpattern,
|
||
Transtarttheta, Transstartphi, Transdtheta, Transdphi, Transthetapoints, Transphipoints,
|
||
temptheta, tempphi);
|
||
|
||
// 接收方向图
|
||
float antPatternGain = GPU_BillerInterpAntPattern(
|
||
ReceiveAntpattern,
|
||
Receivestarttheta, Receivestartphi, Receivedtheta, Receivedphi, Receivethetapoints, Receivephipoints,
|
||
temptheta, tempphi);
|
||
|
||
// 计算
|
||
float sigma0 = 0;
|
||
{
|
||
long clsid = demCls[idx];
|
||
//printf("clsid=%d\n", clsid);
|
||
CUDASigmaParam tempsigma = sigma0Paramslist[clsid];
|
||
if (localangle < 0 || localangle >= LAMP_CUDA_PI / 2) {
|
||
sigma0 = 0;
|
||
}
|
||
else {}
|
||
|
||
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(tempsigma, localangle);
|
||
sigma0 = powf(10.0, sigma / 10.0);// 后向散射系数
|
||
}
|
||
}
|
||
|
||
ampGain = TansantPatternGain * antPatternGain;
|
||
ampGain = ampGain / (powf(4 * LAMP_CUDA_PI, 2) * powf(RstR, 4)); // 反射强度
|
||
outAmp[idx] = ampGain * Pt * sigma0;
|
||
outR[idx] = RstR - refPhaseRange;
|
||
}
|
||
else {
|
||
outAmp[idx] = 0;
|
||
outR[idx] = 0;
|
||
}
|
||
}
|
||
}
|
||
}
|
||
|
||
__global__ void CUDAKernel_PRF_CalFreqEcho(
|
||
double* Rarr, float* ampArr, long pixelcount,
|
||
float* factorj, long freqnum,
|
||
double dx, double nearR,
|
||
cuComplex* PRFEcho, long prfid) {
|
||
long idx = blockIdx.x * blockDim.x + threadIdx.x;
|
||
if (idx < freqnum) {
|
||
float fatorj = factorj[idx];
|
||
float phi = 0;
|
||
float amptemp = 0;
|
||
cuComplex tempfreqEcho = PRFEcho[prfid * freqnum + idx];
|
||
for (long i = 0; i < pixelcount; i++) { // 区域积分
|
||
//phi = (R = R - (floor(R / lamda) - 1) * lamda)* fatorj; // 相位
|
||
float phi = Rarr[i] * factorj[idx]; // 相位
|
||
amptemp = ampArr[i];
|
||
//printf("amp=%f\n", amptemp);
|
||
// Eular; exp(ix)=cos(x)+isin(x)
|
||
tempfreqEcho.x = tempfreqEcho.x + amptemp * cos(phi); // 实部
|
||
tempfreqEcho.y = tempfreqEcho.y + amptemp * sin(phi); // 虚部
|
||
//printf("freqid=%d;fatorj=%.12f;d_R=%.10f;phi=%.10f;echo=complex(%.5f,%.5f)\n", idx, fatorj, Rarr[i], phi, tempfreqEcho.x, tempfreqEcho.y);
|
||
}
|
||
PRFEcho[prfid * freqnum + idx] = tempfreqEcho;
|
||
}
|
||
}
|
||
|
||
|
||
|
||
__global__ void CUDAKernel_PRFSumEcho_Rows(
|
||
double* Rarr,float* ampArr,long Rows,long Cols,
|
||
long startRid,
|
||
float* factorj, long freqnum,
|
||
cuComplex* freqRowsbuffer, long tempRows
|
||
){
|
||
long idx = blockIdx.x * blockDim.x + threadIdx.x;
|
||
if (idx < Rows) { // 按行汇总
|
||
double R = 0;
|
||
double tempamp = 0;
|
||
float phi = 0;
|
||
long rid = idx + startRid;
|
||
float factor = 0;
|
||
|
||
for (long jj = 0; jj < freqnum; jj++) {
|
||
tempamp = ampArr[rid * Cols + jj];
|
||
R = Rarr[rid * Cols + jj];
|
||
for (long ii = 0; ii < freqnum; ii++) {
|
||
phi = R * factorj[ii];
|
||
freqRowsbuffer[idx * freqnum + ii].x = freqRowsbuffer[idx * freqnum + ii].x + tempamp * cos(phi); // 实部
|
||
freqRowsbuffer[idx * freqnum + ii].y = freqRowsbuffer[idx * freqnum + ii].y + tempamp * sin(phi); // 虚部
|
||
}
|
||
//freqRowsbuffer[idx * freqnum + ii] = tempfreqEcho;
|
||
}
|
||
}
|
||
}
|
||
|
||
|
||
__global__ void CUDAKernel_PRFSumEcho_Freq(
|
||
cuComplex* freqRowsbuffer, long tempRows,long freqnum,
|
||
cuComplex* PRFEcho, long prfid
|
||
) {
|
||
long idx = blockIdx.x * blockDim.x + threadIdx.x;
|
||
if (idx < freqnum) { // 按行汇总
|
||
cuComplex tempfreqEcho = freqRowsbuffer[prfid * freqnum + idx];
|
||
cuComplex temp = tempfreqEcho;
|
||
for (long ii = 0; ii < tempRows; ii++) { // 求和汇总
|
||
temp = freqRowsbuffer[ii * freqnum + idx];
|
||
tempfreqEcho.x = tempfreqEcho.x + temp.x;
|
||
tempfreqEcho.y = tempfreqEcho.y + temp.y;
|
||
}
|
||
freqRowsbuffer[prfid * freqnum + idx] = tempfreqEcho;
|
||
}
|
||
}
|
||
|
||
|
||
|
||
|
||
#endif |