Location Adaptive Least Square Algorithm for Target Localization in Multi-Static Active Sonar

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概要

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• In multi-static sonar systems, the least square (LS) and maximum likelihood (ML) are the typical estimation criteria for target location estimation. The LS localizaiton has the advantage of low computational complexity. On the other hand, the performance of LS can be degraded severely when the target lies on or around the straight line between the source and receiver. We examine mathematically the reason for the performance degradation of LS. Then, we propose a location adaptive — least square (LA-LS) localization that removes the weakness of the LS localizaiton. LA-LS decides the receivers that produce abnormally large measurement errors with a proposed probabilistic measure. LA-LS achieves improved performance of the LS localization by ignoring the information from the selected receivers.

• The Institute of Electronics, Information and Communication Engineersの論文

著者

• JANG Eun

  School of Electronics Engineering, KNU

• HAN Dong

  School of Electronics Engineering, KNU

関連論文

• Location Adaptive Least Square Algorithm for Target Localization in Multi-Static Active Sonar

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