Broadband Aperture Extension of A Passive Sonar Array Using Multi-Dimension Autoregression Model

This paper presents a broadband aperture extension approach of a passive sonar array based on multi-dimension autoregression (AR) model, integrated with failure element compensation. The multi-dimension AR model is proposed to build relations between broadband complex signals of array elements in fr...

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Vydané v:2020 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD) s. 502 - 506
Hlavní autori: Qian, Yuning, Chen, Yawei, Cao, Xinrong, Sun, Jun
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 15.10.2020
Predmet:
Apertures
Array signal processing
broadband aperture extension
Broadband communication
Direction-of-arrival estimation
failure element compensation
Mathematical model
multi-dimension AR model
Predictive models
Sonar
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Shrnutí:This paper presents a broadband aperture extension approach of a passive sonar array based on multi-dimension autoregression (AR) model, integrated with failure element compensation. The multi-dimension AR model is proposed to build relations between broadband complex signals of array elements in frequency domain and predict the virtual element signals for wideband aperture extension, instead of the traditional time-domain AR model suitable for narrow-band aperture extension. In addition, the broken element compensation algorithm is designed to recover the failure array elements to ensure the feasibility and accuracy of AR modeling and virtual element prediction. Experimental studies verify the effectiveness of the presented approach for broadband array aperture extension.
DOI:10.1109/ICSMD50554.2020.9261652