一种基于贝叶斯估计的弹道导弹主动段融合算法

A fusion algorithm for ballistic missile boost phase based on Bayes estimation

针对天波超视距雷达在探测跟踪弹道导弹主动段时目标航迹不连续、虚假航迹多等问题,首先将天波超视距雷达和红外预警卫星预警情报相融合,构建了天波超视距雷达与红外预警卫星融合跟踪结构模型;然后根据该模型,结合Bayes理论,提出了一种天波超视距雷达与红外预警卫星的融合算法;最后进行了仿真.仿真结果表明,对于弹道导弹主动段中的融合跟踪问题,本文提出的融合算法与求均值融合方法相比,得到的位置RMS误差平均值降低了44.2%,有效提高了弹道导弹主动段跟踪精度,表现出较强的稳定性.

In order to solve the problems of discontinuous target tracks and multiple false tracks of skywave OTHR in detecting and tracking boost-phase ballistic missiles,this paper firstly combines the intelligence of skywave OTHR with that of infrared(IR)early-warning satellite,and builds the fusion tracking structure model of skywave OTHR and IR early-warning satellite.And then the paper proposes a fusion algorithm of skywave OTHR and IR early-warning satellite based on the model and Bayesian theory.Finally,the fusion algorithm is simulated.The results show that for the fusion tracking of boost-phase ballistic missiles,compared with the mean fusion method,the proposed algorithm in the paper reduces the average error of position RMS by 44.2%,which effectively improves the tracking accuracy of boost-phase ballistic missiles and shows strong stability as well.