A multi‐step method for passive broadband source localisation using a single vector sensor. Issue 10 (16th June 2022)

• Record Type: Journal Article
• Authors: Li, He; Wang, Tong; Su, Lin; Wang, Wenbo; Guo, Xinyi; Wang, Che; Ma, Li
• Is Part Of: IET radar, sonar & navigation. Volume 16:Issue 10(2022)
• Page Start: 1656
• Page End: 1669
• Publication Date: 2022-06-16
• Subjects: acoustic signal detection -- acoustic signal processing -- sonar detection -- underwater sound; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/rsn2.12287
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract: In the deep ocean, a vector sensor is deployed near the seabed to receive direct waves from the reliable acoustic path (RAP). In the space domain, the vector sensor can estimate the vertical arrival azimuth of the signal, which is sensitive to distance. In the frequency domain, the periodic interference pattern formed by the direct and surface‐reflected wave is decided by both the source depth and the vertical arrival azimuth. In this work, a multi‐step method for passive broadband source localisation using a single‐vector sensor (SVS) is proposed. At first, the depth is estimated by the interference pattern in the frequency domain. Then the ranging problem is solved based on the depth estimated result. The impact of the surface‐generated noise is considered. Compared with the scalar vertical line array (VLA) in simulation, the localisation performance of SVS has higher requirements for the signal‐to‐noise ratio (SNR) but is much smaller in size. In the experiment, Gaussian white noise from 310 to 430 Hz was emitted to simulate the underwater target. Compared with traditional match‐field processing (MFP), the multi‐step method is much more stable, accurate, and efficient. The computing time is drastically shortened.