Research On Single Beacon Aided Underwater Localization Technique

With the deepening of human research on the ocean,the navigation and positioning system of underwater vehicles is developing in the direction of large-range,large-scale and highprecision.Single beacon positioning technology is a technology that uses a single beacon placed on the seabed to locate underwater vehicles such as Autonomous Underwater Vehicle(AUV)through ranging information.Arranging an acoustic beacon underwater can make calibration and installation easier and faster.Since a single ranging information cannot determine the specific position of an underwater vehicle,it is necessary to establish a positioning model based on the speed and azimuth information of its own sensors.This paper aims to improve the positioning accuracy and robustness of the single-beacon-aided positioning system,and studies the initial position calculation method of the single beacon positioning system,the singlebeacon-aided single AUV positioning method and the method of single-beacon-aided cooperative localization of multi-AUVs.Since the single beacon positioning system requires multiple ranging information in the time domain combined with its own speed and other sensors information to realize the position calculation of the underwater vehicle.Therefore,due to the lack of observation information,it is necessary to analyze the observability of the system.In addition,the single beacon positioning requires the position information at the previous moment,so the initial position calculation problem is a unique problem of the single beacon system.Therefore,a multihypothesis initial position discrimination method is proposed,and the feasibility and effectiveness of the proposed initial position solution method of the single beacon positioning system are verified through the analysis of field data.In the single-beacon-aided single-AUV positioning system,the AUV uses the speed and azimuth information obtained by its own sensor combined with the distance information obtained through the time delay with the single beacon to obtain its own position estimate.This paper proposes a single beacon localization method based on an adaptive network fuzzy inference system to improve Extended Kalman Filter.In actual applications,the requirements for a single beacon positioning system may vary due to different task requirements or operating environments.When faced with many state variables or requiring fast positioning,it is necessary to reduce computing time and increase computing speed,and new processing methods are needed.To this end,a sparse extended information filtering algorithm is proposed.Finally,the effectiveness and feasibility of the proposed single beacon localization method based on the adaptive network fuzzy inference system based on the improved extended Kalman filter and the sparse extended information filtering method are verified through the analysis of experimental data on the lake.The single beacon can also assist the cooperative localization system to estimate the position of the AUV equipped with low-precision navigation equipment.This type of AUV in the cooperative localization system can not only collect position assistance information from other AUVs,but also obtain the assistance information provided by a single beacon to correct its own position estimation.This paper proposes a novel factor graph and cubature Kalman filter integrated algorithm.At the same time,the underwater positioning environment is complicated,and the proposed algorithm needs to be supplemented according to the factors that may affect the positioning performance.First,the AUV’s own speed sensor may be abnormal due to insufficient accuracy or beyond the range,so the maximum correntropy criterion is used to pre-process the speed information before filtering;secondly,due to the noise in the transmission process,the ranging information may appear abnormal,So let it adaptively change the noise matrix on the basis of the cubature Kalman filter;finally,in view of the actual situation that the underwater sound speed is constantly changing,the effective sound speed is updated with the sum product algorithm of the factor graph.Aiming at the possible continuous speed abnormalities,a backup cooperative localization method is proposed.Finally,using simulation and field data,it is proved that the proposed method can not only improve the positioning accuracy of the AUV,but also maintain the robustness of the system.