Coherent DOA Estimation Algorithm with Co-Prime Arrays for Low SNR Signals

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 23; p. 9320
• Main Authors: Zhang, Fan, Cao, Hui, Wang, Kehao
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 22.11.2023
• Subjects: Algorithms; Arrays; Codes; DOA estimation; Fourier transforms; Linear equations; low SNR; Music; Nondestructive testing; Parameter estimation; Signal processing; space-time correlation matrix; Spacetime; spatial smoothing; DOA estimation; spatial smoothing; low SNR; space-time correlation matrix
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23239320

The Direction of Arrival (DOA) estimation of coherent signals in co-prime arrays has become a popular research topic. However, traditional spatial smoothing and subspace algorithms fail to perform well under low signal-to-noise ratio (SNR) and small snapshots. To address this issue, we have introduced an Enhanced Spatial Smoothing (ESS) algorithm that utilizes a space-time correlation matrix for de-noising and decoherence. Finally, an Estimating Signal Parameter via Rotational Invariance Techniques (ESPRIT) algorithm is used for DOA estimation. In comparison to other decoherence methods, when the SNR is −8 dB and the number of snapshots is 150, the mean square error (MSE) of the proposed algorithm approaches the Cramér–Rao bound (CRB), the probability of resolution (PoR) can reach over 88%, and, when the angular resolution is greater than 4°, the estimation accuracy can reach over 90%.