Gaussian Parameterized Information Aided Distributed Cooperative Underwater Positioning Algorithm

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.