A Multi-UAV Cooperative Search Method Based on Gaussian Distribution Prediction

Abstract

The invention discloses a multi-unmanned aerial vehicle collaborative multi-moving object search search method based on Gaussian distribution prediction. The multi-unmanned aerial vehicle collaborative multi-moving object search method based on Gaussian distribution prediction is characterized by comprising the steps that 1, a task area R is represented by a search probability graph; 2, the Bayes rule is used to update the posterior probability; 3, the objective positions of moving objects are predicted through the application of the Gaussian distribution, and the search probability graph is updated; 4, a distribution model prediction control method is used for constructing the search model of the multi-unmanned vehicle collaborative multi-moving objects search; 5, unmanned aerial vehicles solve a decision information input sequence and obtain heading deflection angles and fly according to the heading deflection angle when the constraint condition is met; 6, a time step is progressively increased, the step 2, the step 3, the step 5 and the step 6 are executed repetitively until the time step exceeds the total time step of search of the unmanned aerial vehicles, and then searching is over. The multi-unmanned aerial vehicle collaborative search method based on the Gaussian distribution prediction can achieve the task of searching multiple moving objects by multiple unmanned aerial vehicles in a collaborative mode, improve the accuracy of searching of the unmanned aerial vehicles, and ensure the accomplished accuracy of the searching task.

Description

technical field [0001] The invention relates to a multi-UAV cooperative search method based on Gaussian distribution prediction, which belongs to the technical field of computer simulation and method optimization. Background technique [0002] The search task is crucial in the process of the drone's mission, and it is the basis for it to perform other tasks. Only when relevant valuable information is searched can it carry out attacks, tracking, interference, pretending, calibration, deception, evaluation, etc. . In recent years, UAV search technology has played a pivotal role in both military and civilian use, and its application scope has become more and more extensive: In terms of military use, UAV search technology has been well reflected in major wars. It makes war more technological and efficient; in terms of civilian use, drone search technology is mainly used in border patrols, environmental monitoring, public security monitoring, etc. Therefore, more and more count...

AI Technical Summary

Problems solved by technology

[0003] At present, UAV search technology mainly focuses on a single UAV to perform tasks alone. However, due to the limited load resources of a single UAV and the limitation of sensor detection angle, it is often difficult to perform the task. Therefore, multi-machine cooperative search methods should be used. But the current multi-machine cooperative search methods such as: coverage search method, greedy search method, dynamic programming method, Dijkstra algorithm, etc. are mainly for multi-machine cooperative search for static targets; there are few programs for cooperative search for moving targets. But in the actual environment, many of the searched targets are in a state of motion, such as: the enemy's moving tanks, the unfortunate people lost in the expedition, the people who escaped in the disaster, the endangered protected animals, etc., so there is a need for an excellent Multi-machine cooperative search method for moving targets

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