Path Planning For The Autonomous Underwater Vehicle Aiming At Locating The Underwater Target

Autonomous underwater vehicle(Autonomous Underwater Vehicle,AUV),as an underwater unmanned platform,has been widely used in underwater acoustic positioning because it can act flexibly in different sea areas because it does not need human control,no cable,autonomous navigation and so on.Route planning is the premise of AUV autonomy.Traditional path planning methods mainly consider obstacle avoidance and shortest path length,but do not fully consider the particularity of AUV mission.When AUV carries underwater target positioning task,planning a path that not only meets the requirements of obstacle avoidance but also has high positioning accuracy can effectively improve the efficiency of AUV.In order to solve this problem,this paper makes an in-depth study on the path planning with high positioning accuracy of AUV,which carries out the underwater target positioning task.This paper first introduces the underwater target positioning scene of a single observation platform,based on this underwater positioning scene,uses the method based on signal time difference of arrival(TDOA)as the underwater positioning method,introduces the positioning principle and application scene of this method,and uses the partial differential method to simulate and analyze the positioning accuracy of the method based on time difference of arrival in different routes of AUV.The positioning accuracy distribution results are verified by Monte Carlo simulation experiments,and the positioning results of the target positioning method based on time difference of arrival in different paths are simulated.Through the simulation results,it is concluded that the AUV navigation path has a great impact on the positioning accuracy of the positioning method.The traditional path planning methods mainly consider the problems of obstacle avoidance and path minimization,and do not fully consider the task execution efficiency of underwater operation of unmanned platform.When AUV carries out underwater target positioning task,the positioning accuracy is greatly affected by AUV navigation path,and the positioning accuracy is significantly reduced based on the traditional path planning method.In addition,underwater acoustic positioning sonar has a limited line of sight(usually side view),and the target may be beyond the range of sonar line of sight,which will not only reduce the positioning accuracy of the target,but also lead to the omission of the target.In order to solve this problem,this paper improves the artificial potential field method and ant colony algorithm,and proposes an AUV path planning method based on improved artificial potential field method and improved ant colony algorithm.The improved artificial potential field method is applied to path planning with optimal local path positioning accuracy.In the improved artificial potential field method,it is proposed that the positioning accuracy distribution is transformed into the positioning accuracy potential field,and the positioning accuracy potential field is superimposed on the artificial potential field to improve the positioning accuracy of the route;in order to keep the target in the sight of sonar all the time,the concept of sight force is put forward,and the sight force is introduced into the artificial potential field method,and the radial velocity of AUV matches the horizontal open angle of sonar by changing the mathematical expression of sight force.The effectiveness of the improved artificial potential field method proposed in this paper is verified by simulation experiments and lake experiments.The improved ant colony algorithm is applied to path planning with optimal global path positioning accuracy.In the improved ant colony algorithm,the positioning accuracy value is introduced into the transfer probability as an evaluation factor.According to the improved transfer probability,the AUV tends to move in the direction of high positioning accuracy,recording the average positioning accuracy of each route,and updating the pheromone increment with the average positioning accuracy as the measurement standard,which can make the path with high average positioning accuracy have higher pheromone increment.In order to keep the target in the sight of sonar,the Bresenham circle drawing algorithm is introduced into the ant colony algorithm.When the target is located in a certain grid,the Bresenham circle drawing algorithm is used to plan a circular path with the target as the center for AUV in the grid map.The effectiveness of the improved ant colony algorithm proposed in this paper is verified by simulation experiments.The improved artificial potential field method is a local route planning method,which updates the route in real time according to the solution results of underwater targets.This method constantly updates the route in the process of AUV driving,and requires real-time operation and real-time transmission with AUV.The improved ant colony algorithm is a global route planning method,which plans the route for AUV in advance in the local computer.This method only needs to input the route planning results to AUV before AUV travel,but it has poor adaptability to dynamic obstacles.