Abstract
In this paper, an algorithm of direction finding is proposed in the presence of unknown mutual coupling. The preliminary direction of arrival (DOA) is estimated using the whole array for high resolution. Further refinement can then be conducted by estimating the angularly dependent coefficients (ADCs) with the subspace theory. The mutual coupling coefficients are finally determined by solving the least squares problem with all of the ADCs utilized without discarding any. Simulation results show that the proposed method can achieve better performance at a low signal-to-noise ratio (SNR) with a small-sized array and is more robust, compared with the similar processes employing the initial DOA estimation and further improvement iteratively.
Highlights
Direction finding of multiple sources has received tremendous attention in the field of radar, sonar, mobile communication, and so on
We evaluate the performance of direction of arrival (DOA) estimation in Step (4) without mutual coupling compensation
This paper addresses the DOA estimation in the presence of unknown mutual coupling
Summary
Direction finding of multiple sources has received tremendous attention in the field of radar, sonar, mobile communication, and so on. Friedlander and Weiss proposed to use an iterative process to acquire the parameters and DOA [12,13] Svantesson formulized it as an optimization problem and solved the problem iteratively to estimate the mutual coupling coefficients for coupling compensation in the linear array of dipoles [14]. In order to increase the performance of DOA estimation, another method [19] proposed recently takes advantage of the special structure of MCM to parameterize the steering vector. It achieves the estimation of DOA using the whole array and improves the result by mutual coupling compensation.
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