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基于机场活动地图信息改进AIMM-UKF算法的移动目标跟踪

常鑫 马光辉 高建树 郝世宇

交通信息与安全2024,Vol.42Issue(2):87-94,104,9.
交通信息与安全2024,Vol.42Issue(2):87-94,104,9.DOI:10.3963/j.jssn.1674-4861.2024.02.009

基于机场活动地图信息改进AIMM-UKF算法的移动目标跟踪

Improved AIMM-UKF Mobile Target Tracking Algorithm Based on Airport Map Information

常鑫 1马光辉 2高建树 1郝世宇2

作者信息

  • 1. 中国民航大学交通科学与工程学院 天津 300300
  • 2. 中国民航大学电子信息与自动化学院 天津 300300
  • 折叠

摘要

Abstract

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.

关键词

机场交通管控与运行/场面移动目标/机场地图数据库/AIMM-UKF/转移概率矩阵/观测矩阵

Key words

airport traffic control and operation/surface moving target/AMDB/adaptive interacting multiple mod-el-unscented Kalman(AIMM-UKF)/probability transition matrix/observation matrix

分类

航空航天

引用本文复制引用

常鑫,马光辉,高建树,郝世宇..基于机场活动地图信息改进AIMM-UKF算法的移动目标跟踪[J].交通信息与安全,2024,42(2):87-94,104,9.

基金项目

国家重点研发计划项目(2021YFB2600500)资助 (2021YFB2600500)

交通信息与安全

OA北大核心CSTPCD

1674-4861

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