#include #include "kalman_filter.h" int main() { KAL_VEC(xhat_k_km1); /* OUTPUT: (S) Predicted state at time 'k' */ KAL_MAT(P_k_km1); /* OUTPUT: (S x S) Predicted covariance at time 'k' */ KAL_MAT(P_km1_km1); /* INPUT: (S x S) Updated covariance from time 'k-1' */ KAL_VEC(xhat_km1_km1); /* INPUT: (S) Updated state from time 'k-1' */ KAL_MAT(F_k); /* INPUT: (S x S) State transition model */ KAL_MAT(B_k); /* INPUT: (S x U) Control input model */ KAL_VEC(u_k); /* INPUT: (U) Control vector */ KAL_MAT(Q_k); /* INPUT: (S x S) Covariance of process noise */ KalmanPredict( xhat_k_km1, /* OUTPUT: (S) Predicted state at time 'k' */ P_k_km1, /* OUTPUT: (S x S) Predicted covariance at time 'k' */ P_km1_km1, /* INPUT: (S x S) Updated covariance from time 'k-1' */ xhat_km1_km1, /* INPUT: (S) Updated state from time 'k-1' */ F_k, /* INPUT: (S x S) State transition model */ B_k, /* INPUT: (S x U) Control input model */ u_k, /* INPUT: (U) Control vector */ Q_k, /* INPUT: (S x S) Covariance of process noise */ 36, /* INPUT: Number of dimensions in state vector */ 36); /* INPUT: Size of control input vector */ return 0; }