A Data Fusion Localization Method for Radio Aviation Search and Rescue
With the vigorous development of China's marine economy and the urgent need for a modern aviation rescue support system in wars,aviation search and rescue positioning technology is receiving increasing attention.In the field of radio,aviation search and rescue positioning technology mainly includes ranging module,direction finding module,and corresponding multi-source fusion tech-nology.However,airborne equipment such as landing gear and tires on the search and rescue aircraft can cause serious obstruction and multipath to the receiving antenna,causing significant deviation of radio data,especially direction finding data,resulting in significant positioning errors in final positioning results.Therefore,this work proposes a robust artificial fish swarm particle filter localization scheme based on Bayesian filtering ideas and swarm intelligence algorithms.Firstly,individuals in particle filtering are considered as fish swarm individuals,and the resampling steps are optimized by imitating the feeding,clustering,tailgating,and random walking behav-iors of the fish swarm algorithm.Furthermore,improvements are made to the search range and optimization speed in the behavior,resul-ting in the formation of a ranging direction finding fusion localization algorithm.Actual data modeling and simulation results show that the fusion positioning method proposed by this algorithm can achieve relatively accurate position and angle accuracy in a short period of time,with strong convergence,good real-time performance,and robustness.
aviation rescuedirection findingartificial fish swarmfusion localization
万方数据
维普
