基于动态规划和双变量容积卡尔曼滤波的空基外辐射源定位算法

Location Algorithm of Airborne External Transmitter Based on DP-BVCKF

针对空基外辐射源定位系统在杂波环境下的目标状态估计问题,提出一种基于动态规划和双变量容积卡尔曼滤波的空基外辐射源定位算法。基于误差传播理论,确定出目标的状态转移范围;选取回波信号幅度值作为动态规划的值函数进行递推积累;根据杂波的统计特性和极值理论解算出动态规划的目标量测提取阈值,逆向提取来自目标的量测序列;利用双变量容积卡尔曼滤波算法同时对目标和外辐射源进行状态估计。仿真结果表明:该算法不仅可以从杂波中有效地提取出目标量测序列,还能降低外辐射源状态不确定性对目标状态估计造成的影响,减少系统的计算量,具有良好的状态估计效果。

An location algorithm based on dynamic programming and bivariate cubature Kalman filter(DP-BVCKF)was proposed for the target state estimation of airborne external transmitter location system in clutter environment.The state transition range of target is determined based on the error propagation theory.The amplitude of echo signal is selected as the value function of dynamic programming for recursive accumulation.Based on the statistical characteristics of clutter and the extreme value theory,the extraction threshold of target measurement of dynamic programming is determined,and the measurement sequence from target is extracted reversely.The states of target and external transmitter are estimated simultaneously by using the bivariate cubature Kalman filter algorithm.Simulated results show that the proposed algorithm can be used to extract the measurement sequence of target from clutter effectively,and the state estimation uncertainty is also reduced.The proposed algorithm has lower calculation burden and better state estimation effect.