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Target identity recognition method based on RCS distribution and spatial location

机译:基于RCS分布和空间位置的目标身份识别方法

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In order to solve the problem of difficult target recognition caused by target tracking discontinuity in complex battlefield environment, We propose a target identity recognition method based on the combination of RCS distribution and spatial position. First select a certain spatial position rule of the target to be identified, predict of the target trajectory using the Runge-Kutta equation, get ballistic data covering the target tracking all time period, match the predicted full trajectory with the ballistic data of the remaining time period of the target to be identified, Obtain identity recognition result. At the same time, the probability density distribution is obtained for the smoothed target RCS sequence, calculate the K-L distance between the probability density distributions to obtain the identity recognition result. Finally, the above two identity recognition results are fused to obtain the final identity recognition result. The method is simple and fast, and the similarity recognition effect can be achieved when the multi-target flight trajectory is close. The correctness of the method is verified by simulation data.
机译:为了解决复杂战场环境下目标跟踪不连续引起的目标识别困难的问题,提出了一种结合RCS分布和空间位置的目标身份识别方法。首先选择要识别的目标的某个空间位置规则,使用Runge-Kutta方程预测目标轨迹,获得覆盖目标跟踪所有时间段的弹道数据,将预测的完整轨迹与剩余时间的弹道数据进行匹配确定目标的时间段,获得身份识别结果。同时,针对平滑后的目标RCS序列获得概率密度分布,计算概率密度分布之间的K-L距离,以获得身份识别结果。最后,将上述两个身份识别结果融合在一起,以获得最终的身份识别结果。该方法简便快捷,当多目标飞行轨迹接近时,可以达到相似度识别的效果。仿真数据验证了该方法的正确性。

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