Abstract:

To solve the problem of large amounts of error in the extended Kalman filtering (EKF) decoupling algorithm caused by phased array radar seeker different control gain calibration scale of forward channel gain and beam control gain, an EKF decoupling algorithm based on the particle swarm optimization algorithm is proposed, which uses minimum mean square error as the fitness function. Two gain parameters are in optimum combination. Then through the establishment of the system model of EKF, the relationship between the line of sight rate and the gain parameters is deduced, so that the estimation after filtering is optimal posteriori estimation. Finally, the simulation result shows that the proposed algorithm is a good way to solve the problem of large amounts of error, and the algorithmic validity of decoupling and line of sight rate extraction in the phased array radar seeker is proved.