用旋转不变技术实现互耦和通道不一致的联合抑制

Joint calibration algorithm in the presence of mutual coupling and channel discord via rotational invariance techniques

阵元间的互耦和通道的不一致都会对阵列流型产生扰动,使得子空间类估计算法性能急剧下降甚至失效,而传统多误差联合自校正算法存在多维搜索、迭代寻优和计算量庞大等问题.针对上述问题,提出了一种新的利用旋转不变技术实现两种阵列误差联合抑制算法.该算法根据互耦系数矩阵特点,通过通道的切换和子阵的选取,使得两子阵的阵列流型矩阵在误差扰动下仍然保持旋转不变关系,将ESPRIT算法应用背景推广至互耦和通道不一致同时存在的情形.该算法无须谱峰搜索和估计误差参数,阵列误差的抑制无须任何额外计算量.仿真验证了这种算法能够抑制互耦和通道幅相误差,估计性能和无误差时的标准ESPRIT算法接近.

The performance of subspace estimation algorithms degrades substantially in the presence of mutual coupling and channel discord by the perturbance of the steering matrix. Classical self-calibration algorithms need multidimensional search, optimization and iteration, and large calculation quantity. In order to avoid these shortcomings, a novel ioint calibration algorithm using rotational invariance techniques is proposed in this paper. Two sub-arrays＇ steering matrix can maintain the rotational invariance property in the presence of array errors by switching channels and selecting sub-arrays according to the characteristic of the mutual coupling matrix. So, the estimation of signal parameters -~ia rotational invarianee techniques （ESPRIT） algorithm is applicable to mutual coupling and channel discord scenarios. The algorithm requires neither searching the spectrum peak nor estimating error parameters, and the calibration of array errors does not need an additional calculation quantity. Simulation results show that the proposed algorithm can restrain mutual coupling and channel discord. The performance of the algorithm is equivalent to the performance of the standard ESPRIT algorithm without errors.