Spatial Domain Dedispersion Transform and Its Application to Source Localization

Abstract

Due to the multipath and dispersion effects inherent in low-frequency sound propagation within the shallow-water waveguide, localization algorithms that do not account for these underwater acoustic propagation phenomena exhibit significant estimation biases and gain degradation. Furthermore, the increasing complexity of the ocean environment due to human activities necessitates enhanced performance of localization algorithms, particularly under the condition of multiple target interference and low signal-to-noise ratio. To address these challenges and mitigate estimation biases, this article proposes a localization algorithm for a horizontal array that employs the spatial dedispersion transform combined with the frequency domain accumulation (SDDT-FDA) algorithm. The SDDT-FDA is applied to signals received by horizontal arrays under different assumed source locations. It is demonstrated that a distinct multipeak structure in the results emerges only when the assumed source location matches the actual source location, thereby enabling the inference of the source location. This article presents the theoretical proof, discusses the impact of various parameters on performance, and provides simulation analyses and validation results based on experiment data.