An Anti-cross-eye Method Based on Label Probability HypothesisDensity Filter
Received date: 2017-09-01
Online published: 2025-05-28
交叉眼干扰利用波前扭曲引起跟踪雷达瞄准点转向虚拟的强干扰方向,使得雷达的角度测量与跟踪失效。为对抗交叉眼干扰,文中在随机有限集理论(randomfiniteset,RFS)的基础上,引入标签概率假设密度(probabilityhypothesisdensity,PHD)滤波器用于判断目标的真实位置。将真实目标和干扰建模视为两个不同的信号,通过预测、校正、重采样、状态估计、航迹提取给目标和干扰分配不同的标签,实现对目标与干扰的正确区分。仿真表明标签PHD滤波器能够在交叉眼干扰存在的情况下正确识别估计出目标的状态信息且估计误差较小。
陈安娜 . 基于标签概率假设密度滤波器的抗交叉眼干扰方法[J]. 弹箭与制导学报, 2018 , 38(2) : 111 -115 . DOI: 10.15892/j.cnki.djzdxb.2018.02.025
Cross-eye jamming causes the tracking radar aiming towards the false direction of the stronger jamming by means of wave-front distortion, then makes the radar angle measurement and tracking failure. In this article, based on random finite set (RFS) a label Probability Hypothesis Density (PHD) filter is used as an anti-cross-eye method by determining the position of the real target. This method builds two different models for target and jamming, assigns different labels to them by prediction, correction, resampling, state estimation and track extraction, and uses the labels to distinguish between target and jamming. The simulation refers that the label PHD filter can recognize and estimate the state information of the target correctly in the presence of cross-eye jamming, and the estimation error is small.
Key words： label; PHD filter; cross-eye; anti-cross-eye; RFS
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