Improved Modified MUSIC Algorithm Based on Virtual Sensor Array Elements

Sun, BaoLiang; Song, Yang; Xue, Kaiping; Chen, Chao; Zhao, Jun

doi:10.1007/978-981-19-6613-2_408

Cited by 1 publication

(1 citation statement)

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“…[11], a method combining beamforming and matrix reconstruction was proposed, to eliminate the phase perturbation caused by the interaction of coherent signals. Another method is the spatial-smoothing method [12][13][14]. The earliest decoherence method was the forward-spatial-smoothing-(FSS) method, which reduced the array aperture and the azimuth-estimation performance [15].…”

Section: Introductionmentioning

confidence: 99%

DOA-Estimation Method Based on Improved Spatial-Smoothing Technique

Hou,

Wang,

Ding

et al. 2023

Mathematics

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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.

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