Design and Analysis of a Non-Iterative Estimator for Target Location in Multistatic Sonar Systems with Sensor Position Uncertainties

Xin Wang, Zhi Yu, Le Yang and Ji Li
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Xin Wang: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Department of Electronic Engineering, Jiangnan University, Wuxi 214122, China
Zhi Yu: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Department of Electronic Engineering, Jiangnan University, Wuxi 214122, China
Le Yang: Department of Electrical and Computer Engineering, College of Engineering, University of Canterbury, Christchurch 8020, New Zealand
Ji Li: Locaris Technology Co., Ltd., Zhengzhou 450000, China

Mathematics, 2020, vol. 8, issue 1, 1-30

Abstract: Target location is the basic application of a multistatic sonar system. Determining the position/velocity vector of a target from the related sonar observations is a nonlinear estimation problem. The presence of possible sensor position uncertainties turns this problem into a more challenging hybrid parameter estimation problem. Conventional gradient-based iterative estimators suffer from the problems of initialization difficulties and local convergence. Even if there is no problem with initialization and convergence, a large computational cost is required in most cases. In view of these drawbacks, we develop a computationally efficient non-iterative position/velocity estimator. The main numerical computation involved is the weighted least squares optimization, which makes the estimator computationally efficient. Parameter transformation, model linearization and two-stage processing are exploited to prevent the estimator from iterative computation. Through performance analysis and experimental verification, we find that the proposed estimator reaches the hybrid Cramér–Rao bound and has linear computational complexity.

Keywords: multistatic sonar; target location; hybrid Cramér–Rao bound; weighted least squares; nonlinear estimation; non-iterative estimator; perturbation analysis; linear model; bias analysis; complexity analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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