基于压缩感知的雷达前视向稀疏目标分辨

A Sparse Target-scenario Determination Strategy Based on Compressive Sensing for Active Radar in the Line of Sight

主动雷达使用多普勒波束锐化(DBS)和合成孔径雷达技术只能提高在斜视和侧视向的横向距离分辨,而对前视向波束内相同距离但不同方位-俯仰角度上的多个目标难以分辨。该文提出一种基于压缩感知理论(CS)的单接收通道结构雷达前视向稀疏目标分辨方法。多个天线子阵接收信号经随机加权求和后通过单个接收通道输出,同一距离单元上不同脉冲重复周期的接收机输出建模为对同一稀疏信号场景的多次观测,根据观测进行压缩感知信号重构得到稀疏目标场景估计。仿真表明,该方法能够实现雷达对前视向波束内的稀疏目标分辨。

Active radar can improve the cross-range resolution in the squint and side-looking direction using Doppler Beam Sharpening（DBS） and Synthetic Aperture Radar（SAR） techniques, but can difficultly determine multiple targets in the forward-looking direction at the same range cell but different angel in one beam. A spare target-scenario determination strategy based on Compressive Sensing（CS） framework is addressed which can obtain the resolution in the line of sight for active radar and need only one receiver channel. The outputs of multiple sub-arrays are randomly weighted and then summarized in single receiver channel. The single-receiver outputs in the same one range cell belonging to multiple pulse repetition periods are modeled as multiple observations with respect to the same one spare target-scenario, and then the sparse-target scene is estimated using the recovery method of compressive sensing based on observations. Numerical experiments show that the proposed method can obtain the resolution of a spare target scenario in one beam in the line of sight for active radar.