Optimal geometric configuration of sensors for received signal strength based cooperative localization of submerged AUVs

Abstract

Cooperative localization is one of the recent techniques that are being utilized for localization/navigation of Autonomous Underwater Vehicles (AUVs). Received Signal Strength (RSS) based cooperative localization is relatively unexplored field and only a little literature is available about it. Proper positioning of the sensors to maximize the observability of the AUVs is very critical for cooperative localization. In this paper, a method for estimating optimal geometric configuration of sensors is presented for 3D localization of targets using RRS measurements. An evaluation function based on Fisher Information Matrix (FIM) theory has been derived keeping in view the underwater acoustic channel characteristics. Most of the real world constraints such as acoustic waves characteristics in water, multiple-AUVs system and computation complexity have been considered. The proposed evaluation function has been solved using successive optimization algorithm to obtain optimal positions of the sensors. The algorithm ensured that the computation complexity should remain limited even when number of sensor AUVs is increased. Various simulation examples are then presented to calculate optimal formation for different systems/situations. Finally, efficacy of proposed method has been proved using Extended Kalman Filter (EKF) based simulations to compare the localization error between optimal formations and random formations of the sensors.