Work

Synthetic adaptive matched field processing for moving source range estimation in deep water

Year: 2025

Type: article

Abstract: Adaptive matched field processing (AMFP) has proven effective for source localization in deep-water environments. However, when the target is in motion, the need for numerous snapshot samples can lead to distortion in covariance estimation, degrading AMFP performance. A synthetic AMFP method has been proposed to compensate for the phase of multi-snapshot signals, enhancing AMFP performance. Additionally, a rough estimation of target velocity is obtained. The efficacy of the method has been validated through numerical simulations and experimental data, with results showing that, within a 9 km range, the average localization error is reduced by 1.45 km compared to traditional AMFP.

Source: JASA Express Letters

DOI: 10.1121/10.0035772

Authors: Zhaokai Zhai, Fenghua Li, Feilong Zhu, Bo Zhang, Duo Zhai, Junjie Mao

Institutions: University of Chinese Academy of Sciences, State Key Laboratory of Acoustics, National University of Defense Technology

Language: English

Topic: Direction-of-Arrival Estimation Techniques

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: Youth Innovation Promotion Association of the Chinese Academy of Sciences

Award: G3612150188