多视角穿墙雷达联合稀疏成像算法

多视角穿墙雷达成像系统利用多个视角的目标回波数据,可以有效提高目标成像重建结果的质量。在建立多视角穿墙雷达联合稀疏信号模型的基础上,提出了一种基于交叉验证技术的删失同时正交匹配追踪成像算法。该算法将每个观测视角雷达单元的测量数据分成重建数据和交叉验证数据两部分,通过进行多次删失同时正交匹配追踪迭代计算实现测量噪声水平估计和成像重建,既减小了各个视角雷达站间的数据通信开销,也摆脱了成像算法对测量噪声水平和场景稀疏度先验信息的依赖。仿真实验结果验证了所提成像算法的有效性和准确性。

A joint sparsity imaging algorithm for multi-view through-the-wall radars

Multi-view through-the-wall radar imaging system can improve the quality of target reconstruction results by utilizing information from multiple views.Based on the establishment of joint sparsity signal model for the multi-view through-the-wall radar,this paper proposes a cross validation(CV) based censored simultaneous orthogonal matching pursuit(CSOMP) imaging algorithm.The total measurements are divided into reconstruction measurements and CV measurements.The proposed algorithm can simultaneously accomplish the imaging reconstruction and estimate the measurement noise level through iterative calculation,thus reducing the communication costs among radar units and avoiding the requirement of the prior knowledge of the measurement noise level and sparsity level of the observed scene.The simulation experiment results verifies the effectiveness and validity of the proposed imaging algorithm.