基于多特征联合调制的雷达假目标生成方法

    Radar False Target Generation Method Based on Multi-Feature Joint Modulation

    • 摘要: 随着极化雷达干扰鉴别技术的发展,传统欺骗性假目标干扰易被识别和抑制。为了应对上述挑战,面向舰船防护背景,本文提出了一种基于多特征联合调制的假目标干扰方法。首先,建立极化雷达的拓展目标回波信号模型,明确假目标干扰所需调制的参数;其次,分析了舰船目标在距离、速度、极化维度的典型特征,具体为距离上的非均匀特征、速度上的微动特征和极化上的多特征约束,并建立了对应的调制参数样本集;最后,结合实测舰船目标数据,与所提干扰方法开展了特征对比分析,并针对双极化体制、全极化体制两类雷达,在当前典型鉴别特征集下利用支持向量机对所提方法和传统多假目标干扰进行了对比验证,结果表明:相比于传统多假目标干扰,所提方法在时-频-极化联合特征集下可以使双极化雷达的干扰鉴别精确率下降46.19%;使全极化雷达的干扰鉴别精确率下降45.67%。

       

      Abstract: ith the development of polarimetric radar jamming identification techniques, traditional deceptive false target jamming has become increasingly susceptible to detection and suppression. To address the above challenges, this paper proposes a false target jamming method based on multi-feature joint modulation for ship protection scenarios. First, an extended target echo signal model for polarimetric radar is established to clarify the modulation parameters required for false target jamming. Second, the typical characteristics of ship targets across the range, velocity, and polarization dimensions are analyzed—specifically, the non-uniform features in range, micro-motion features in velocity, and multi-feature constraints in polarization—and a corresponding modulation parameter sample set is constructed. Finally, using measured ship target data, a comparative feature analysis is conducted with the proposed jamming method. Furthermore, for both dual-polarimetric and fully polarimetric radar systems, the proposed method and traditional multiple false target jamming are compared and validated under the current typical discrimination feature set using a support vector machine (SVM). The results demonstrate that, compared with traditional multiple false target jamming, the proposed method reduces the jamming discrimination precision rate for dual-polarimetric radar by 46.19% and for fully polarimetric radar by 45.67% under the joint time–frequency–polarization feature set.

       

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