DOA-Estimation Method Based on Improved Spatial-Smoothing Technique

Yujun Hou, Xuhu Wang (), Lei Ding, Xu Jin and Qunfei Zhang
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Yujun Hou: College of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
Xuhu Wang: College of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
Lei Ding: College of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
Xu Jin: College of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
Qunfei Zhang: School of Marine Science and Technology, Northwest Polytechnical University, Xi’an 710129, China

Mathematics, 2023, vol. 12, issue 1, 1-13

Abstract: To improve the data utilization of the sensor array and direction-of-arrival-(DOA)-estimation performance for coherent signals, a DOA-estimation method with a modified spatial-smoothing technique is proposed. The covariance matrix of the received data of the sensor array is decomposed to obtain the signal subspace vectors, and the obtained vectors are smoothed in the proposed method. Then, a new data covariance matrix is constructed by using the autocorrelation covariance matrix of the intra-subarrays and the cross-correlation covariance matrix of the inter-subarrays. Finally, the DOA of the incident signal is estimated, using the new data covariance matrix with the multiple-signal-classification-(MUSIC) algorithm. The data-processing results of the simulation and lake test show that the modified method has stronger decoherence ability, as it utilizes more comprehensive coherent signal information. It also has better azimuth-estimation performance and robustness in the case of a low signal-to-noise ratio (SNR), few snapshots, and small incident-angle intervals when compared to the traditional method. Therefore, the modified method has great engineering application value.

Keywords: direction-of-arrival estimation; sensor array; spatial smoothing; coherent signal; lake test (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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