基于机场活动地图信息改进AIMM-UKF算法的移动目标跟踪OA北大核心CSTPCD

Given the unique challenges posed by high-density traffic flow and diverse moving targets on airport sur-faces,ensuring accurate tracking is essential for effective operation of airport automated equipment such as un-manned vehicles within airports.To address the limitations of the existing Adaptive Interactive Multi-Model-Un-scented Kalman Filter algorithm(AIMM-UKF)in tracking moving targets in airport movement areas,an enhanced tracking algorithm is proposed by incorporating high precision airport map information into AIMM-UKF to im-prove tracking accuracy.Using the detailed airport operating procedures file from the airport map database(AM-DB),the construction CAD drawing of an airport is simplified and accurately corrected with ArcGIS software and the second-order polynomial registration method to complete the high-precision airport map correction.The data collected by airport intelligent monitoring equipment is processed in real time,with the coordinate information of moving targets being corrected using the high-precision airport map information.This correction adjusts the observa-tion values in the moving target tracking algorithm.Additionally,by incorporating adaptive correction of the Mar-kov transition probability matrix and applying the observation matrix for secondary correction,tracking accuracy and model matching are improved.Monte Carlo simulation experiments have demonstrate that this improved algo-rithm utilizes high-precision airport map information to refine the observation values of moving targets.Compared with the Adaptive Correction Markov Transition Probability Matrix Interactive Multiple Model-Unscented Kalman Filter algorithm,this improved algorithm achieves an average reduction of 62.69%in the root mean square error(RMSE)of position and 56.84%in the RMSE of speed.In comparison,this algorithm exhibits superior model matching and superior filtering performance,significantly enhancing the tracking accuracy of moving targets within airport environments.