机器人2025，Vol.47Issue(3)：315-327,13.DOI:10.13973/j.cnki.robot.240285
面向时变观测噪声的无人机光电系统对地目标的无源定位方法
Passive Localization Method of Ground Targets by Unmanned Airborne Optoelectronic Systems Involving Time-varying Observation Noise
摘要
Abstract
Aiming at the time-varying observation noise problem faced by UAV(unmanned aerial vehicle)optoelectronic systems in multi-target passive localization,a joint adaptive extended Kalman filter(JAEKF)algorithm is proposed to real-ize passive geo-localization of ground targets.The algorithm adopts a three-level hierarchical processing architecture:the classical extended Kalman filter framework is constructed at level 1 to achieve the baseline estimation of the target geograph-ic coordinates,and effectively suppress the static observation noise interference;the dynamic residual covariance matrices is analyzed in real time at level 2 to adaptively adjust the weight distribution of the predicted and measured values in the observation model;and the adjustment mechanism for the time-varying forgetting factor is designed at level 3 to make the predicted values of the observation covariance adaptively adapt to the changes of UAV flight attitude,forming a double adap-tive compensation system.Simulation and real flight experiments show that the average positioning accuracy of the proposed algorithm for multiple targets is 14.69 m,and the error range is 1.87～5.21 min the condition of time-varying noise,indicating that the algorithm has the characteristics of high accuracy,strong stability and good real-time performance.关键词
无源目标定位/齐次坐标转换/无人机光电平台/卡尔曼滤波Key words
passive target localization/homogeneous coordinates transformation/UAV(unmanned aerial vehicle)opto-electronic platform/Kalman filtering引用本文复制引用
闫啸家,孙世岩,胡清平,应文健,石章松..面向时变观测噪声的无人机光电系统对地目标的无源定位方法[J].机器人,2025,47(3):315-327,13.基金项目
国家自然科学基金(61640308) （61640308）
湖北省自然科学基金(2023AFB900). （2023AFB900）
