Joint calibration algorithm in the presence of mutual coupling and channel discord via rotational invariance techniques
Lin Wang · Journal of Xidian University · 2014
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 joint 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 via rotational invariance 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.