Synthetic adaptive matched field processing for moving source with a horizontal line array
Fenghua Li, Feilong Zhu, Yanjun Zhang, Bo Zhang, Wen Li, Wenyu Luo
Abstract
Using adaptive matched field processing (AMFP) to search for targets in shallow water is challenged by source motion. For AMFP, a relatively large number of samples is required to minimize the variance of the covariance matrix. For a fast moving target, direct integrating over a large number of data snapshots will blur the sound interference structure and, hence, degrade the ability of AMFP to produce a sharp main peak. This paper presents a source motion mitigation technique for broadband moving targets. By applying the waveguide invariant theory, the covariance matrix can be reformulated by frequency and phase shifting according to a single scalar parameter hypothesis. When the hypothesis parameter is in accordance with the true value, the moving target can be considered stationary. The technique is applied to experimental data acquired by a bottom mounted horizontal line array and demonstrates an increase in detection ranges.