Research On Route Constraint Modeling And Evaluation Method Of High Speed Unmanned Aerial Vehicle

High-speed unmanned aerial vehicles have the advantages of high speed,strong maneuverability,and long flying distance,are widely used in military and civilian fields.Before executing a flight mission,the mission planning system usually models the flight path constraint modeling first,and then uses the path planning algorithm to obtain a feasible path.The trajectory planning algorithm will get a large number of feasible trajectories,but it is difficult to judge the performance of a certain trajectory.Therefore,the mission planning system usually analyzes the performance of the trajectory in combination with the evaluation module.Thesis studies the modeling and evaluation of high-speed unmanned aerial vehicles path constraint,aiming to achieve the ordering of trajectory performance through trajectory evaluation and provide decision-making suggestions for flight crews.Aiming at the problem of path constraint modeling for high-speed unmanned aerial vehicle(UAV),thesis models from four aspects: aircraft performance constraints,flight environment constraints and multi-mode composite navigation constraints.The flying altitude of high-speed aircraft is high,and the battlefield situation is changing rapidly,the radar-missile threat source will randomly appear in the battlefield with a certain rule.Therefore,when modeling the flight environment constraints,thesis establishes a Markov model to calculate the location of sudden threats.The high-speed unmanned aerial vehicle uses inertial navigation system for navigation,supplemented by terrain height matching navigation and scene matching navigation for track correction.This navigation method requires the routes satisfy the navigation matching area constraint.Because whether the radar seeker carried by the aircraft can capture the target determines whether the aircraft can successfully complete the flight mission,so the target acquisition model is established in the mission constrain.In order to analyze the comprehensive performance of the trajectory,the thesis established a trajectory evaluation index system,which divided the indicators that affect the performance of the trajectory into four first-level indicators and eight second-level indicators.Use statistics,discrete sampling and Monte Carlo method to calculate each track evaluation index.In calculating the vehicle survivability,the paper develops a simple model to dynamically calculate the radar scattering cross-sectional area of the vehicle and analyzes the probability of the vehicle being detected,tracked,and intercepted.Therefore,thesis combines traditional comprehensive assessment methods with cloud models and proposes a cloud model-based TOPSIS assessment method and a cloud model-based fuzzy comprehensive assessment method.The former allows for more flexibility in the assessment by ranking the tracks using a method that adjusts the weighting of the numerical characteristics of the cloud model according to the decision maker’s preference when measuring the distance between cloud models.The latter is capable of not only ranking the tracks,but also giving the track’s performance rating and evaluating the resulting cloud model.The experimental results show that both methods can effectively achieve the ranking and evaluation of flight paths,which has advantages not found in conventional methods and can provide a reference for the flight crew’s decision making.