Signal Fusion-Based Algorithms to Discriminate Between Radar Targets and Deception Jamming in Distributed Multiple-Radar Architectures
Signal Fusion-Based Algorithms to Discriminate Between Radar Targets and Deception Jamming in Distributed Multiple-Radar Architectures
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DOI：
10.1109/jsen.2015.2440769
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发表时间：
2015-06
影响因子：
4.3
通讯作者：
Shanshan Zhao;Linrang Zhang;Yu Zhou;Nan Liu
中科院分区：
文献类型：
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作者：
Shanshan Zhao;Linrang Zhang;Yu Zhou;Nan Liu
基于目标回波与欺骗干扰在空间散射特性上的差异，分析了分布式多雷达体系结构在电子对抗中的潜在能力。不同接收机接收到的欺骗信号是完全相关的，而目标回波的相关性随视角间隔的变化而逐渐变化。针对这一差异，首次采用信号融合的思想，提出了一种在Neyman-Pearson意义下区分欺骗干扰和雷达目标的算法。该算法通过对任意两个目标在不同接收机上的复包络进行相关性检验来识别有源假目标。为了评估其鉴别性能，推导了假目标拒止概率的理论表达式。仿真结果验证了新算法的可行性，并与现有的基于数据融合的方法进行了比较。该方法的优点在于可以区分任意调制方式下的欺骗信号，并可与基于数据融合的方法串联使用，进一步提高鉴别性能。
The potential abilities of distributed multiple-radar architectures in the electronic counter-countermeasure are analyzed based on the difference between target echoes and deception jamming in spatial scattering properties. The deception signals received by different receivers are fully correlated, while the correlation of target echoes varies gradually with the interval of view angles. According to this difference, the thought of signal fusion is first adopted and a corresponding algorithm is proposed to discriminate the deception jamming from radar targets in the Neyman-Pearson sense. In this algorithm, active false targets are identified by correlation tests between arbitrary two targets' complex envelopes in different receivers. To evaluate its discrimination performance, the theoretical expression for the rejection probability of false targets is derived. Simulations verify the feasibility of the new algorithm and its performance improvement over the existing data fusion-based methods. The merit of the method lies in that it can discriminate deception signals generated by arbitrary modulation and can be used in series with data fusion-based methods to improve discrimination performance further.