基于压缩感知的外辐射源雷达目标参数估计方法

Target Parameter Estimation Method for Passive Radar Based on Compressed Sensing

  • 摘要: 外辐射源雷达通过计算互模糊函数来估计目标的距离−多普勒信息,该方法存在弱目标被强目标高副瓣掩盖及分辨率低的问题. 为此提出了一种基于压缩感知的外辐射源雷达目标参数估计方法. 该方法提出了采用分布式压缩感知同步子空间追踪算法实现距离域稀疏重构,采用扩展正交匹配追踪算法实现多普勒域稀疏重构. 仿真和实测数据验证表明,所提方法减少了互模糊函数副瓣的影响并提高了分辨率,同时避免了字典尺寸过大和时间复杂度过高的问题.

     

    Abstract: Passive radar can estimate the range-Doppler information of the target by calculating the cross ambiguity function. But this method represents some problems, for example, the weak target can be masked by high sidelobes of strong target and low resolution. To solve these problems, a target parameter estimation method was proposed for passive radar based on compressed sensing. Firstly, a distributed compressed sensing simultaneous subspace pursuit algorithm was proposed to achieve the range domain sparse reconstruction. Then, taking an enlarged orthogonal matching pursuit algorithm, the Doppler domain sparse reconstruction was carried out. The results of simulation and measured data show that the proposed method can reduce the influence of the sidelobe generated by cross ambiguity function, improve the resolution, and avoid the problems of large dictionary size and high time complexity.

     

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