An innovative aviation target tracking algorithm is presented in this paper,utilizing high-altitude unmanned airship dual photoelectric sensors in conjunction with Unmanned Aerial Vehicle(UAV)-borne two-coordinate radar.The algorithm addresses the challenge of integrating sensor data to accurately track targets when individual sensors lack complete target position information,thus overcoming limitations of traditional point-trace association methods.Initially,a two-level point-trace correlation algorithm based on angle and distance is introduced for multi-sensor measurement association following coordinate system transformation.Subsequently,a line-plane intersection fusion localization algorithm is proposed to determine the initial target track position through techniques such as least squares method,intersection projection,distance nearest point solution,and homologous data compression.Leveraging heterogeneous information from space-based multi-platform reconnaissance,an extended Unscented Kalman Filter(UKF)is designed to track aviation targets by enhancing the traditional UKF.Simulation results demonstrate that this algorithm achieves superior precision in tracking high-speed aerial targets.
关键词
信息融合/目标跟踪/量测关联/扩维无迹卡尔曼滤波器/空基多平台
Key words
Information fusion/Target tracking/Measurement association/Extended Unscented Kalman Filter(UKF)/Space-based multi-platform
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