阵元位置互质的线性阵列：阵列校正和波束形成

该文研究了阵元位置互质的线性阵列(CLA)的阵列校正和波束形成问题。在假设CLA天线单元部分校准的条件下，基于同时干扰定位与阵列校正(SILAC)技术，设计了一种适用于CLA的阵列校正和波束形成方法：CLA-SILAC-INCM算法。从理论上分析证明了，当CLA中包含有L_c≥3个完全校准的天线单元，使用SILAC技术可以高精度无模糊地实现干扰源角度和阵列天线幅相误差估计，并在此基础上完成干扰噪声协方差矩阵(INCM)重建和波束形成最优权向量构造。通过仿真实验验证了，提出的CLA-SILAC-INCM算法具有比其他常用算法更好的性能，尤其是信噪比接近干噪比时，CLA-SILAC-INCM算法的优势更为明显。

Linear Coprime Sensor Location Arrays: Array Calibration and Beamforming

Focusing on investigating the problems of array calibration and beamforming for Coprime Location Arrays (CLA), a new beamforming algorithm, which is called CLA-SILAC-INCM algorithm is proposed for the partly calibrated CLAs, by exploiting the Simultaneous Interference Localization and Array Calibration (SILAC) technique. Theoretical analysis shows that when the CLA contains not less than 3 fully calibrated antenna elements, highly accurate and unambiguous estimation for interference direction and array gain-phase error vector can be obtained using the SILAC technique. Afterward, the Interference plus Noise Covariance Matrix (INCM) is reconstructed and the optimal beamforming weighting vector is computed. Simulation results show that the proposed CLA-SILAC-INCM algorithm exhibits better performance compared with existing algorithms, especially when the signal-to-noise ratio is close to interference-to-noise ratio.