ArticleSensors (Basel, Switzerland)2019
Underwater Target Localization and Synchronization for a Distributed SIMO Sonar with an Isogradient SSP and Uncertainties in Receiver Locations.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Locating an Underwater Target Using Angle-Only Measurements of Heterogeneous Sonobuoys Sensors with Low Accuracy.Sensors (Basel, Switzerland) · 2022Article
- Cooperative Reception of Multiple Satellite Downlinks.Sensors (Basel, Switzerland) · 2022Article
- A Novel Approach for Underwater Vehicle Localization and Communication Based on Laser Reflection.Sensors (Basel, Switzerland) · 2019Article
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Authors and funding
4 authors.
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Abstract
A distributed single-input multiple-output (SIMO) sonar system is composed of a sound source and multiple underwater receivers. It provides an important framework for underwater target localization. However, underwater hostile environments bring more challenges for underwater target localization than terrestrial target localization, such as the difficulties of synchronizing all the underwater receiver clocks, the varying underwater sound speed and the uncertainties of the locations of the underwater receivers. In this paper, we take the sound speed variation, the time synchronization and the uncertainties of the receiver locations into account, and propose the underwater target localization and synchronization (UTLS) algorithm for the distributed SIMO sonar system. In the distributed SIMO sonar system, the receivers are organized in a star topology, where the information fusion is carried out in the central receiver (CR). All the receivers are not synchronized and their positions are known with uncertainties. Moreover, the underwater sound speed is approximately modeled by a depth-dependent sound speed profile (SSP). We evaluate our proposed UTLS algorithm by comparing it with several benchmark algorithms via numerical simulations. The simulation results reveal the superiority of our proposed UTLS algorithm.
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