Reserach On Target Localization Based On Underwater Acoustic Sensor Networks Under Weak Communication Environment

With the continuous growth of human demand for marine resources and information,underwater target localization technology based on underwater acoustic sensor networks is gaining more and more attention.Among them,autonomous underwater vehicles are often widely used in civil,military,and commercial applications as localization targets in underwater acoustic sensor networks because of their autonomy,flexibility,and great role in underwater detection.However,the localization problem of underwater vehicles becomes more challenging due to weak communication characteristics such as nodes movement,asynchronous clocks,and non-line-of-sight errors in the underwater environment.In this thesis,we investigate the above-mentioned localization problem under underwater acoustic weak communication conditions by designing localization protocols and localization methods that match the weak communication characteristics.The main research work of this thesis is as follows.To improve the deployment efficiency of the network and reduce energy consumption in the localization process,an underwater acoustic sensor network with only one buoy node is constructed.Meanwhile,a two-level information interaction protocol is designed considering the limited communication distance of the anchor nodes in the network.To solve the problem of underwater target localization accuracy degradation caused by the passive movement of anchor nodes in the underwater acoustic sensor network,an anchor node self-localization method based on an indirect adjustment algorithm is proposed.The irregularity and uncertainty of the anchor node error are used to iteratively correct the predefined position of the anchor node.The simulation results show that the algorithm is effective in correcting the position of the anchor node.For the underwater vehicle localization problem under the asynchronous clock and anchor node position uncertainty in the underwater acoustic sensor network,an underwater vehicle cooperative localization algorithm based on iterative adjustment algorithm is proposed.A localization optimization problem on minimizing the sum of measurement errors is constructed by introducing time difference measurement,and then the underwater vehicle position and clock parameters under asynchronous clock are solved.Based on this,a cooperative positioning mechanism is proposed for the iterative position between the underwater vehicle and the anchor node.The mechanism further reduces the anchor node position error with the increase of positioning iterations under the uncertainty of anchor node position,and solves a more accurate underwater vehicle position.The simulation verifies the effectiveness of the algorithm.For the underwater vehicle localization problem under the influence of non-line-of-sight error and asynchronous clock,a localization method for the underwater vehicles based on machine learning and filtering algorithm is proposed.In the initial stage of localization,a support vector machine-based node screening strategy is designed to screen out the anchor nodes disturbed by the initial non-line-of-sight errors.In the localization process,a two-step Kalman filtering algorithm is designed to eliminate the non-zero mean part of the non-line-of-sight error and obtain more accurate time difference measurements under asynchronous clock conditions.Further,to eliminate the effect of the remaining variance after filtering,an improved CHAN algorithm considering the non-line-of-sight error is designed,which solves the target position by combining the filtered measurements and the weight coefficients associated with the non-line-of-sight error.Simulation and experimental results show that the localization method has better localization performance compared with comparison algorithms.