Q3D-Calibration/include/GaussNewton.h

88 lines
1.8 KiB
C++

#pragma once
#ifndef GNM_h
#define GNM_h
#include <Eigen/Dense>
#include <iostream>
class GaussNewton {
public:
GaussNewton(int L_, double* parma_, double (*Func_)(double, double*),
double* (*Gunc_)(double, double*));
~GaussNewton();
public:
void addData(double x, double y);
double* solve();
public:
double eps = 1e-5;
double* parma;
double (*Func)(double, double*);
double* (*Gunc)(double, double*);
int L, maxIter = 10;
std::vector<Eigen::Vector2d> data;
private:
void calmJ_vF();
void calmH_vG();
private:
Eigen::MatrixXd mJ; // 雅克比矩阵
Eigen::MatrixXd mH; // H矩阵
Eigen::VectorXd vF; // 误差向量
Eigen::Vector3d vG; // 反馈向量
};
GaussNewton::GaussNewton(int L_, double* parma_, double (*Func_)(double, double*),
double* (*Gunc_)(double, double*)) {
L = L_;
parma = parma_;
Func = Func_;
Gunc = Gunc_;
}
GaussNewton::~GaussNewton() {}
void GaussNewton::addData(double x, double y) { data.push_back(Eigen::Vector2d(x, y)); }
void GaussNewton::calmJ_vF() {
double x, y;
double* resJ;
mJ.resize(data.size(), L);
vF.resize(data.size());
for (int i = 0; i < data.size(); i++) {
Eigen::Vector2d& point = data.at(i);
x = point(0), y = point(1);
resJ = (*Gunc)(x, parma);
for (int j = 0; j < L; j++) mJ(i, j) = resJ[j];
vF(i) = y - (*Func)(x, parma);
}
}
void GaussNewton::calmH_vG() {
mH = mJ.transpose() * mJ;
vG = -mJ.transpose() * vF;
}
double* GaussNewton::solve() {
Eigen::VectorXd vX(L);
for (int k = 0; k < maxIter; k++) {
calmJ_vF();
calmH_vG();
vX = mH.ldlt().solve(vG);
if (vX.norm() <= eps) return parma;
for (int i = 0; i < L; i++) parma[i] += vX[i];
}
return parma;
}
#endif