多传感器多目标无源定位跟踪算法研究

Multi-Sensor Multi-Target Passive Locating and Tracking

针对多站无源测向交叉定位在复杂环境下会产生大量虚假定位点问题,本文提出了一种对目标进行无源定位跟踪的新方法,即先通过数据聚类,确定目标数量;由此动态建立多模弹性神经网络,去除了大部份虚假点;再通过建立航迹树的方法来动态跟踪目标,去除弹性网络未去除的虚假点.该方法解决了大量虚假点存在的情况下,目标数量的确定难题、弹性网初始化难题及动态剔除虚假点难题,进而有效地解决了多干扰机目标相关、虚假点的剔除问题.仿真分析试验表明:该方法计算量低,弹性网络收敛速率快,目标正确锁定率及虚假点剔除率高.

The passive direction finding cross location method is widely adopted in the passive localization,therefore there will exist masses of false intersection points. Eliminating these false intersection points correctly and quickly is a key technique in passive localization. A new method is proposed for passive locating and tracking multi-jammer target. It not only solves the difficulty to determine the targets number under the existence of masses of false intersection points, but also solves the initialization problem of elastic network. Thus this method solves the multi-jammer target correlation and the elimination of static false intersection points. The method which dynamically establishes the multi-supposition track tree solves elimination of remaining false intersection points. Simulation results show that computation burden of the method is lower, the elastic net has more fast convergence velocity and more high rate of locking the true targets and the method can eliminate more false intersection points.