DOA Estimation of Noncircular Signals with Combined ESPRIT for Coprime Linear Array

Abstract

Abstract. Direction of arrival (DOA) estimation of noncircular signals for coprime linear array is investigated, and a combined estimation of signal parameters via rotational invariance technique (ESPRIT) based algorithm is proposed. The coprime linear array can be de-composed into two uniform linear arrays, so ESPRIT is firstly used to obtain ambiguous DOA estimations, then unique DOA estimation is achieved by finding the coincide results from the two decomposed subarrays based on the coprimeness. The proposed algorithm increase the degree of freedom, enhance the performance of angle estimation, and identifies more targets than conventional methods. Numerical simulations are conducted to demonstrate the improvement of the proposed algorithm.

DOA Estimation for Coprime Linear Array Based on MI-ESPRIT and Lookup Table

“…The first part obtains the estimated values, which include covariance matrix estimation, eigenvalue decomposition, and solving estimated values, so the computational burden of the four algorithms is different. The second part is the solving ambiguity; the computational complexities in the previously formulated algorithms [ 23 , 25 , 28 ] are the same, i.e., , which is larger than the complexity in our method. In the proposed algorithm, by simply indexing in the LUT, the real DOA can be obtained.…”

“…Compared to both CLA and ULA, the DOA estimation precision of MI-ESPRIT was better than ESPRIT. This is because the MI-ESPRIT algorithm makes full use of the subarray elements, so the angle measurement precision of the proposed algorithm is better than that of the reference [ 28 ], which was based on the ESPRIT algorithm. The DOA estimation precision of the reference [ 25 ] was between that of the reference [ 28 ] and the proposed algorithm.…”

“…This is because the MI-ESPRIT algorithm makes full use of the subarray elements, so the angle measurement precision of the proposed algorithm is better than that of the reference [ 28 ], which was based on the ESPRIT algorithm. The DOA estimation precision of the reference [ 25 ] was between that of the reference [ 28 ] and the proposed algorithm. It can be seen from Figure 5 that the DOA estimation precision of the algorithm introduced by the reference [ 23 ] is basically consistent with our proposed method when SNR is low.…”

“…Two signals imping on the CLA from −20°, 20°. In order to verify the performance of the proposed algorithm, we performed comparison simulations between the previously proposed methods [ 23 , 25 , 28 ] and our method. In the reference [ 23 ], the rough step was d S 1 = 0.1° and the fine step was d S 2 = 0.2°.…”

“…In order to ease the limitations of the existing algorithms, this paper proposes a novel DOA estimation method for CLA based on the MI-ESPRIT and lookup table (LUT). MI-ESPRIT fully uses elements of every subarray, so the angle measurement precision is improved compared with the algorithm proposed by the reference [ 28 ], which was based on the ESPRIT algorithm. In addition, the computational complexity is reduced because the proposed method avoids spectral peak search.…”