2020/10/28 by Amir Weiss, Weiss, Amir, Arie Yeredor +1
Computer Science · #Speech and Audio Processing #Direction-of-Arrival Estimation Techniques #Blind Source Separation Techniques
paper · pdf · doi:10.48550/arxiv.2010.14799
Blind calibration of sensors arrays (without using calibration signals) is an\nimportant, yet challenging problem in array processing. While many methods have\nbeen proposed for "classical" array structures, such as uniform linear arrays,\nnot as many are found in the context of the more "modern" sparse arrays. In\nthis paper, we present a novel blind calibration method for 2-level nested\narrays. Specifically, and despite recent contradicting claims in the\nliterature, we show that the Least-Squares (LS) approach can in fact be used\nfor this purpose with such arrays. Moreover, the LS approach gives rise to\noptimally-weighted LS joint estimation of the sensors' gains and phases\noffsets, which leads to more accurate calibration, and in turn, to higher\naccuracy in subsequent estimation tasks (e.g., direction-of-arrival). Our\nmethod, which can be extended to K-level arrays (K>2), is superior to the\ncurrent state of the art both in terms of accuracy and computational\nefficiency, as we demonstrate in simulation.\n