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Open AccessArticle

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

by Xin Wang 1,*, Zhi Yu 1, Le Yang 2 and Ji Li 3
1
Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Department of Electronic Engineering, Jiangnan University, Wuxi 214122, China
2
Department of Electrical and Computer Engineering, College of Engineering, University of Canterbury, Christchurch 8020, New Zealand
3
Locaris Technology Co., Ltd., Zhengzhou 450000, China
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(1), 129; https://doi.org/10.3390/math8010129
Received: 3 December 2019 / Revised: 6 January 2020 / Accepted: 10 January 2020 / Published: 15 January 2020
(This article belongs to the Section Engineering Mathematics)
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 multistatic sonar; target location; hybrid Cramér–Rao bound; weighted least squares; nonlinear estimation; non-iterative estimator; perturbation analysis; linear model; bias analysis; complexity analysis
MDPI and ACS Style

Wang, X.; Yu, Z.; Yang, L.; Li, J. Design and Analysis of a Non-Iterative Estimator for Target Location in Multistatic Sonar Systems with Sensor Position Uncertainties. Mathematics 2020, 8, 129.

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