An Array Extension Method Based on Combination of Sub-array Covariance Matrices

doi:10.12382/bgxb.2022.1076

Abstract

Abstract:

A linear array extension method based on combination of sub-array covariance matrices is proposed to solve the problem of performance deterioration of signal detection and azimuth estimation under low signal-to-noise ratio. The proposed method divides the array into odd and even sub-arrays, and the extended received data is constructed by using the cross-covariance and auto-covariance matrices of the two sub-arrays. Finally, the final extended signal is obtained by combining the extended received data. The proposed method breaks through the physical aperture of array, and avoids the problem of grating lobe when using the cross-covariance of odd and even sub-arrays only to reconstruct the received data. Simulated results show that the proposed method can be used to reduce the sidelobe of beam output, and has good weak target detection ability and azimuth resolution. Compared with the array extension algorithm based on the cross covariance of odd and even sub-arrays, the proposed method can provide higher azimuth estimation accuracy.

Key words: array extension, weak target detection, direction-of-arrival estimation, grating lobe, covariance matrix

CLC Number:

TN911.23

LIANG Guolong, LUO Junge, HAO Yu, FU Jin. An Array Extension Method Based on Combination of Sub-array Covariance Matrices[J]. Acta Armamentarii, 2024, 45(5): 1717-1724.

Figures/Tables 13

Fig.1 Linear array structure

Fig.2 Schematic diagram of array element expansion

Fig.3 Array element corresponding to the extended signal

Fig.4 Array element corresponding to the combined signal

Fig.5 Azimuth spectrum of different methods

Fig.6 Relationship between detection probability and SNR

Fig.7 Relationship between RMSE and SNR

Fig.8 Relationship between DOA estimation error and SNR

Fig.9 Relation between discrimination probability and SNR

Fig.10 Influence of array element position on detection probability

Fig.11 Detection probabilities under different extended signal combinations

Fig.12 Azimuth-time recording of the algorithm in Ref.[2]

Fig.13 Azimuth-time recording of the proposed method

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