An Efficient Estimator for Target Localization in a Multistation Redundancy System without Matrix Inversion

Abstract

This paper focuses on target localization problem in a multistation redundancy system which finds broad applications in sonar, radar, and location-based service. Previous solutions can only be applied to the minimum system, such as the TOA method with three sensors and the AOA method with two sensors or need matrix inversion. To solve this problem, we propose a simple closed-form solution for a multistation redundancy localization system 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. We derive the method in TOA solution and AOA solution, respectively. The proposed method 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 Cramér-Rao low bound both in TOA solution and AOA solution.