Abstract

This paper focuses on target localization problem in a multi-station redundancy system which finds broad applications in sonar, radar, wireless sensor networks, and location based service. Previous solutions can only be applied to the minimum system, such as TOA method with three sensors or need matrix inversion. To solve this problem, a simple closed-form solution for a multi-station redundancy localization system is proposed by using the estimation variance as the weighting coefficient to compute an average of each group’s localization result. The proposed method, with simple algebraic solution, requires no matrix inversion and can be used for low-cost hardware devices. The method is derived in TOA solution. It can also be extended to other locating technologies. Numerical examples are provided to illustrate the performance of the proposed method in root-mean-square error. The positioning accuracy of the proposed method is close to Cramer-Rao low bound.

Highlights

  • Target localization has a wide range of applications in sonar, radar, and location-based service [1]

  • Simulations demonstrated that the theoretical variance fits well with root-mean-square error (RMSE) in both TOA solution and AOA solution

  • We have developed a simple method for target localization in a multistation redundancy system

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Summary

Introduction

Target localization has a wide range of applications in sonar, radar, and location-based service [1]. Since the algebraic methods are based on local information of a minimum system, the direct extension for those methods to a multistation redundancy system may not obtain optimal performance since those solutions cannot make use of extra measurements to improve position accuracy [8]. To improve the localization accuracy, matrix methods [5, 6, 8, 11, 21,22,23,24,25] based on global information of measurements from all sensors were developed for a multistation.

Problem Formulation
The Proposed Method
Performance Analysis
Simulation Results
Conclusions
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