缓动单站纯方位目标运动分析算法

纯方位目标运动分析对于隐蔽状态下的态势评估具有重要意义。针对缓动单站平台对海上目标的探测问题,基于运动目标的方位历程图,提出一种纯方位目标运动分析（TMA）算法。在探测平台准静止、目标运动状态恒定且探测单目标的条件下,该算法可利用构建的运动模型精确拟合出目标的方位历程变化曲线,进而有效解算出目标的速度初距比、航向角、过正横时间及过正横方位角等目标要素。2020年5月在南海某海区利用搭载于3台低速无人航行器上的单矢量水听器进行了探测试验,将收集到的试验数据对算法进行了验证,结果表明,模型解算结果与参考值的速度初距比均方根误差小于1 h-1,目标航向角均方根误差为6.6°,过正横时间均方根误差为77.4 s。试验数据处理结果验证了算法的适用性。 

Quasi-stationary single station bearing-only target motion analysis algorithm

The bearings-only Target Motion Analysis（TMA） is of great significance to situation assessment in concealed state.Aiming at the problem of detecting maritime targets by slow-moving single-station platforms,a bearings-only target motion analysis algorithm is constructed based on the bearing-time recordings of a moving target.Under the conditions of quasi-stationary detection platform,unchanging target motion state and only one single target in the detectable area,the algorithm can accurately fit the target’s Direction-of-Arrival（DOA） curve through the motion model,and effectively calculate the ratio of the target speed to initial distance,the target heading,abeam time,abeam DOA and so on.A test was carried out at a certain area of the South China Sea in May 2020,and the algorithm is verified by the test data collected from single vector hydrophones which are integrated in 3 low-speed Unmanned Underwater Vehicles（UUV）.The Root Mean Square Error（RMSE） of the target speed to initial distance ratio between the calculation results and the reference values is less than 1 h-1.the RMSE of the target heading is 6.6° and the RMSE of abeam time is 77.4 s.The results show that the algorithm is effective.