Gaussian Parameterized Information Aided Distributed Cooperative Underwater Positioning Algorithm

Abstract

With the exploration of marine resources, the number of underwater nodes is increasing with each passing day, and the demand of mutual cooperative position between nodes is becoming extremely urgent. The existing underwater positioning technology is mainly realized by transplanting cooperative position technology from ground space, without taking into consideration the consequent problems of complex underwater acoustic channels, large signal propagation attenuation and the limited load of underwater nodes. According to the characteristics of the underwater cooperative position network, this paper proposes gaussian parameterized information aided distributed cooperative positioning algorithm (GPI-CP) with underwater environment. The algorithm utilized here is the form of Gauss parameter to calculate information and establish a confidence model. In order to reduce the computational complexity, the Taylor model was adopted to linear approximate European distance. Then distributed underwater node cooperative position is obtained by combing with the factor map theory. This algorithm combined with the sum-product theory and parameterized Gaussian information transmission, is promising to realize fast underwater cooperative position and reduce communication calculations. The proposed algorithm was simulated and analyzed in terms of location ambiguity, ranging error and the number of nodes, etc. When the proposed algorithm was compared with the existing underwater cooperative position method, it was noticed that the position performance had improved more than 10% and the communication calculation is less.

Fisher-Information-Matrix-Based USBL Cooperative Location in USV–AUV Networks

“…However, the above collaborative positioning methods all have shortcomings in complex underwater environments: on the one hand, with an increase in the number of robots and sensors, the underwater acoustic channel becomes complicated, the computational complexity increases, the underwater node load is limited, and other problems arise [18,19]; on the other hand, the system requires a large amount of energy to achieve positioning and communication, so there are high requirements for the battery life and operating costs of the equipment.…”

A Novel Factor Graph and Cubature Kalman Filter Integrated Algorithm for Single-Transponder-Aided Cooperative Localization

“…Sun et al proposed a CL algorithm based on a hybrid topology architecture using relative measurement graph method [25]. In the literature [26], Gaussian parameterizations of messages are combined in the framework of factor graph. Factor graph can merge different available asynchronous sensor information efficiently and accurately [27] and can be readily modified by adding corresponding factor nodes and edges [28].…”

Three-Dimensional Ultra-Short Base Line Based Underwater Acoustical Localization Utilizing Modified Newton Algorithm

“…The existing underwater localization system mainly includes the underwater acoustic localization (UWAL) system and the underwater optical/wireless localization networks [1][2][3][4]. Since the propagation loss of the acoustic signal is much lower than that of the optic signal or the wireless signal in the water, the UWAL is the most effective way to achieve the long-range underwater localization [5][6][7][8].…”