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- 2017
一种考虑站址误差的抗欺骗式假目标方法
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Abstract:
针对现有数据融合算法中,组网雷达各节点雷达忽略自身站址误差而导致抗干扰性能降低的问题,提出一种考虑站址误差的抗欺骗式假目标方法。首先,通过增加量测过程中可能产生的各节点雷达的站址误差变量,改进融合算法的误差协方差矩阵;然后,利用改进后的算法计算各节点雷达对应量测目标之间的马氏距离,判断目标的空间相关性;最后,利用空间相关性的差异,对真假目标进行有效鉴别。仿真结果表明:该方法能够将组网雷达对真目标检测概率稳定在99％以上;在站址误差为60 m的条件下,组网雷达对假目标的虚警概率可降低10％以上。
A method against deception？？false？？target jamming based on position errors is proposed to solve the problem that the anti？？jamming performance of the existing data fusing algorithm is decreased by ignoring the position error of each radar node in the netted system. Firstly, the method improves the error covariance matrix by increasing variables of position error for each radar node. Then, an updated algorithm is applied to calculate the Markov distance between targets to judge the spatial correlation. Finally, the differences between spatial correlations are utilized to discriminate targets. Simulation results show that the identification rate of the proposed method is stable and is over 99％ for true targets. When the position error is more than 60 m, the false？？alarm probability of the netted system decreases by over 10％ for false targets
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