OpenCVKalman濾波的结构和函数定义.doc

首先来看一下OpenCV中关于Kalman滤波的结构和函数定义 CvKalman Kalman 滤波器状态 typedef struct CvKalman { int MP; /* 测量向量维数 */ int DP; /* 状态向量维数 */ int CP; /* 控制向量维数 */ /* 向后兼容字段 */ #if 1 float* PosterState; /* =state_pre-data.fl */ float* PriorState; /* =state_post-data.fl */ float* DynamMatr; /* =transition_matrix-data.fl */ float* MeasurementMatr; /* =measurement_matrix-data.fl */ float* MNCovariance; /* =measurement_noise_cov-data.fl */ float* PNCovariance; /* =process_noise_cov-data.fl */ float* KalmGainMatr; /* =gain-data.fl */ float* PriorErrorCovariance;/* =error_cov_pre-data.fl */ float* PosterErrorCovariance;/* =error_cov_post-data.fl */ float* Temp1; /* temp1-data.fl */ float* Temp2; /* temp2-data.fl */ #endif CvMat* state_pre; /* 预测状态 (x(k)): x(k)=A*x(k-1)+B*u(k) */ CvMat* state_post; /* 矫正状态 (x(k)): x(k)=x(k)+K(k)*(z(k)-H*x(k)) */ CvMat* transition_matrix; /* 状态传递矩阵 state transition matrix (A) */ CvMat* control_matrix; /* 控制矩阵 control matrix (B) (如果没有控制，则不使用它)*/ CvMat* measurement_matrix; /* 测量矩阵 measurement matrix (H) */ CvMat* process_noise_cov; /* 过程噪声协方差矩阵 process noise covariance matrix (Q) */ CvMat* measurement_noise_cov; /* 测量噪声协方差矩阵 measurement noise covariance matrix (R) */ CvMat* error_cov_pre; /* 先验误差计协方差矩阵 priori error estimate covariance matrix (P(k)): P(k)=A*P(k-1)*At + Q)*/ CvMat* gain; /* Kalman 增益矩阵 gain matrix (K(k)): K(k)=P(k)*Ht*inv(H*P(k)*Ht+R)*/ CvMat* error_cov_post;