Abstract
The cooperative localization of submerged autonomous underwater vehicles (AUVs) using the Time Difference of Arrival (TDOA) measurements of surface AUV sensors is an effective method for many applications of AUVs. Proper positioning of the sensors to maximize the observability of the AUVs is very critical for cooperative localization. In this paper, a novel method for obtaining the optimal formation of sensor AUVs has been presented for the three-dimensional (3D) cooperative localization of targets using the TDOA technique. An evaluation function for estimating the optimal formation has been derived based on Fisher Information Matrix (FIM) theory for a single target as well as multiple-target cooperative localization systems. An iterative stepping algorithm has been followed to solve the evaluation function and obtain the optimal positions of the sensors. The algorithm ensured that the computation complexity should remain limited, even when the number of sensor AUVs is increased. Various simulation examples are then presented to calculate the optimal formation for different systems/situations. The effect of the position of the reference sensor and operating depth of the target AUVs on the optimal formation of the sensors has also been studied, and conclusions are drawn. For implementation of the proposed method for more practical scenarios, a simulation example is also presented for cases when the target’s position is only known with uncertainty.
Highlights
Autonomous underwater vehicles (AUVs) have been the focus of research in recent times due to their increasing applications in both military and civil fields such as oceanographic surveys, underwater search and rescue, underwater structure monitoring, underwater surveillance and mine counter operations, etc
In contrast to previous research studies, we have considered most of the constraints that are faced in the real-world problem of the cooperative localization of autonomous underwater vehicles (AUVs)
When the evaluation function, which is given by Equation (21), reaches its maximum, the corresponding formation of the sensor AUVs will be in an optimal formation
Summary
Autonomous underwater vehicles (AUVs) have been the focus of research in recent times due to their increasing applications in both military and civil fields such as oceanographic surveys, underwater search and rescue, underwater structure monitoring, underwater surveillance and mine counter operations, etc. The key methods to estimate the target’s slave vessels or targets, measure their position relative to the accurate position of the sensor AUVs position using sensor AUVs’ information include the Received Signal Strength (RSS), Angle of andArrival apply (AoA), correction to the INS to bound error. RangeRSS measurement more suitable choices for the localization of targets due to time-varying path loss, multiple path affect, and accurate and commonly used methods for the cooperative localization of AUVs. The range themeasurement bending of sound waves in water [7]. Range measurement and TDOA are more accurate and method requires precise time clock synchronization among sensors and targets, which commonly used methods forthe theother cooperative localization of AUVs. range measurement is a challenging task.
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