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Journal ArticleDOI

Optimization of observer trajectories for bearings-only target localization

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TLDR
In this article, the authors proposed an approach based on maximizing the determinant of the Fisher information matrix (FIM) subject to state constraints imposed on the observer trajectory (e.g., by the target defense system).
Abstract
The problem of bearings-only target localization is to estimate the location of a fixed target from a sequence of noisy bearing measurements. Although, in theory, this process is observable even without an observer maneuver, estimation performance (i.e., accuracy, stability and convergence rate) can be greatly enhanced by properly exploiting observer motion to increase observability. This work addresses the optimization of observer trajectories for bearings-only fixed-target localization. The approach presented herein is based on maximizing the determinant of the Fisher information matrix (FIM), subject to state constraints imposed on the observer trajectory (e.g., by the target defense system). Direct optimal control numerical schemes, including the recently introduced differential inclusion (DI) method, are used to solve the resulting optimal control problem. Computer simulations, utilizing the familiar Stansfield and maximum likelihood (ML) estimators, demonstrate the enhancement to target position estimability using the optimal observer trajectories.

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Citations
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Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks

TL;DR: A maximum likelihood (ML) acoustic source location estimation method is presented for the application in a wireless ad hoc sensor network and consistently outperforms existing acoustic energy based source localization methods.
Journal ArticleDOI

Optimality analysis of sensor-target localization geometries

TL;DR: The aim of this work is to identify those relative sensor-target geometries which result in a measure of the uncertainty ellipse being minimized, and to show that an optimal sensor- target configuration is not, in general, unique.
Journal ArticleDOI

Target Location Estimation in Sensor Networks With Quantized Data

TL;DR: A signal intensity based maximum-likelihood target location estimator that uses quantized data is proposed for wireless sensor networks (WSNs) and is much more accurate than the heuristic weighted average methods and can reach the CRLB even with a relatively small amount of data.
References
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Book

Matrix computations

Gene H. Golub
Journal ArticleDOI

Fundamentals of statistical signal processing: estimation theory

TL;DR: The Fundamentals of Statistical Signal Processing: Estimation Theory as mentioned in this paper is a seminal work in the field of statistical signal processing, and it has been used extensively in many applications.
Book

Applied Optimal Control: Optimization, Estimation, and Control

TL;DR: This best-selling text focuses on the analysis and design of complicated dynamics systems and is recommended by engineers, applied mathematicians, and undergraduates.
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