Multi-UUV (Unmanned Underwater Vehicle) cooperative system underwater target tracking algorithm for fuzzy adaptive interacting multiple model (FAIMM)

Abstract

The invention provides a multi-UUV (Unmanned Underwater Vehicle) cooperative system underwater target tracking algorithm for a fuzzy adaptive interacting multiple model (FAIMM). Firstly, according to the bearing-only target tracking principle of the multi-UUV cooperative system, a discrete nonlinear state and observation equation for the target tracking system is built; then, according to the characteristics of underwater target motion, in combination of five kinds of target motion modes, analysis is carried out according to the dynamic state transition matrix, the coupled inequality relation among the five modes is put forward, and a motion mode set adapted to underwater target tracking is selected optimally; then, an intermediate Gauss distribution function is adopted as a membership function, a mode probability is used as an evaluation index for filter information and corresponding covariance acquired by each mode, and fuzzy reasoning for the mode transition probability is designed; and finally, the FAIMM algorithm is designed and realized. During the multi-UUV cooperative system bearing-only target tracking process, the least number of target motion sets is selected, adaptive change of the mode transition probability is realized through the fuzzy reasoning, disordered competition among the modes are reduced, the filter accuracy is higher, and demands of multi-UUV cooperative system underwater target tracking can be met.

Description

technical field [0001] The invention belongs to the field of underwater target tracking, and specifically relates to a multi-UUV cooperative system underwater target tracking algorithm based on a fuzzy self-adaptive multi-interaction model. Background technique [0002] Unmanned Underwater Vehicle (UUV) underwater passive target tracking mainly uses the underwater acoustic equipment carried by the UUV to passively receive the orientation information of the underwater moving target (submarine) to estimate the target's distance, velocity, acceleration and other motion characteristics. , to realize the positioning and tracking of underwater targets, this method is also called Bearing-Only Tracking. Because this observation method belongs to the passive acceptance of target radiation signals, it has strong concealment and can often surprise and destroy underwater targets. However, due to the limited acquisition of underwater information by single-station UUV, the objectivity of...

AI Technical Summary

Problems solved by technology

Generally, in order to better cover the actual state of underwater target motion, the more motion models selected, the better, but as the number of models increases, the amount of calculation will increase exponentially, and at the same time, it will cause disorder among multiple models Competition, but reduces the tracking accuracy and real-time performance of the tracking algorithm

In other words, there are still two problems in the actual application of IMM in UUV: (1) how to select and optimize a suitable target motion model, (2) how to design a suitable and accurate model conversion probability

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