Coprime sparse circular array with little angular dependence and reduced mutual coupling

2020 
Abstract Sparse circular arrays (SCAs) have many advantages, e.g., providing 360 ∘ azimuthal coverage and reducing mutual coupling. This paper presents a novel coprime sparse circular array (CSCA) for significantly improving underdetermined direction of arrival (DOA) estimation performance compared to the existing SCAs, e.g., nested sparse circular array (NSCA) and super nested sparse circular array (S-NSCA). The CSCA is obtained by connecting two sparse subarrays concircularly with two displacements, and the sensor positions are determined by a systematic procedure. The array geometry has closed-form expressions and the inter-sensor spacings of the two sparse subarrays are coprime. The CSCA contains all the good properties of the SCAs. Simultaneously, the CSCA has less angular dependence due to its nearly uniform sensor distribution and has much smaller mutual coupling effect by enlarging its minimum inter-sensor spacing, when compared to the NSCA and S-NSCA. Due to its merits, it can be applied to sonar, communication, and navigation, to name a few. Then an l 1 -based method is used for underdetermined DOA estimation. Theoretical analysis and simulation results show the superiority of the CSCA.
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