Research On Multi-AUV Cooperative Navigation Based On Distance Information

The ocean on the earth is huge,and there are a lot of resources in the ocean,so people’s enthusiasm for ocean research is growing.As an important means of exploring the ocean,the Autonomous Underwater Vehicle(AUV)has a wide range of applications in both military and civilian applications.In recent years,with the research of multi-robot systems by scholars,multi-AUV cooperative navigation and positioning technology has also received attention.Multi-AUV cooperative navigation and positioning technology is to use a few leader AUVs equipped with high-precision navigation equipment to improve the positioning accuracy of AUV only with low-precision navigation equipment and low cost.This paper is based on a multi-AUV navigation and positioning technology distance information,mainly to do the work the following aspects:Firstly,the paper discusses several common navigation methods for AUV when navigating in the underwater.After that,it introduces the related foundation and model of multi-AUV cooperative navigation,including the sensors,coordinate systems,parameter definitions and underwater communication ranging technology and kinematic model in multi-AUV cooperative navigation and positioning processSecondly,aiming at the multi-AUV cooperative navigation and positioning algorithm of single leader,the moving radius vector method is introduced,the mathematical model is established,and the observability of the system is analyzed and discussed by the observational rank criterion of nonlinear systems based on Lie derivative.Then we discuss the effects of different sampling periods and path complexity between leaders and followers on positioning results.Aiming at the case of ocean current interference during the navigation process,the mathematical model is re-established,the correctness of the navigation algorithm is verified by simulation.Aiming at the multi-AUV cooperative navigation and positioning algorithm of multi-leader,the extended Kalman filter algorithm,the unscented Kalman filter algorithm and the cubature Kalman filter algorithm are studied respectively.Based on the basic principles of three different filtering algorithms,the corresponding cooperative navigation algorithm is designed.The three algorithms are compared and analyzed from the perspectives of theoretical essence,estimation accuracy and computational complexity.Aiming at the unknown statistical characteristics of noise during navigation,the Sage-husa adaptive extended Kalman filter algorithm is established.The above algorithm is simulated to verify the effectiveness of the algorithm.Finally,the limitations of the Kalman filter algorithm are analyzed and the advantages of the factor graph algorithm are proposed.Then the factor graph representation method and the sum-product algorithm are introduced.The multi-AUV cooperative navigation algorithm based on factor graph is established.The simulation case is designed for the algorithm.The superiority is verified by comparison with the extended Kalman filter algorithm.