阵元位置误差自校正的累量域辅助阵元法

阵元位置误差会严重影响多重信号分类(multiple signal classification, MUSIC)算法的测向性能，为此给出了一种阵元位置误差自校正的累量域辅助阵元法。首先构造了一种最大非冗余四阶累积量矩阵，并基于该矩阵实现了信源方位和阵元位置误差的联合估计，其中信源方位的估计需要一维搜索，而阵元位置误差的估计需要求解一个线性最小二乘问题。在一定假设条件下，对新算法的参数估计一致性做了理论分析。仿真实验表明：新算法可以减少对辅助阵元个数的要求，并且减弱了高斯色噪声对算法参数估计性能的影响。

Cumulants-based instrumental sensors method for self-calibration of sensor position errors

The sensor position errors have great negative influence on the direction finding performance of the multiple signal classification (MUSIC) algorithm. Therefore, a cumulants based instrumental sensors method for self calibration of sensor position errors is presented. Firstly, a maximal set of non redundant fourth order cumulants matrix is constructed. Then, the joint estimation of direction of arrival (DOA) and the sensor position errors can be carried out based on the fourth order cumulants matrix constructed above, therein the DOA estimations are obtained by one dimension search, and the sensor position errors can be offset by solving a linear least squares problem. The theoretical analysis on the consistency of the novel algorithms is fulfilled under certain conditions. The results of computer simulations indicate that the novel algorithm can reduce requirement for the number of the instrumental sensors and restrain the negative impact of the Gauss colored noise.