主被动雷达复合导引头信息融合技术研究

针对主被动雷达复合导引头,研究了基于序贯扩展Kalman滤波的信息融合算法。利用主被动雷达复合导引头对目标角误差进行观测,将匹配后的测量角度进行最优加权,进而以角度信息作为量测,估计目标的运动信息。通过试验验证,基于主被动雷达信息融合状态估计比仅依赖主动雷达观测量的状态估计稳态误差小,且滤波器收敛速度更快。

Research on Information Fusion Technology for Active-Passive Radar Composite Seeker

In the present work,an information fusion algorithm based on sequential extended Kalman filtering（SEKF） for the active-passive radar composite seeker is proposed. First,the angle error is achieved from the activepassive radar composite seeker,and then an optimization strategy is used to weight the matched angle errors,which can be used to estimate the dynamic information of the targets. The experiments show that the steady-state error of state estimation based on active-passive radar information fusion is smaller than that relies on active radar measurement only. Meanwhile,the former filter has a faster convergence.