摘要
针对转弯率未知或变化条件下的精确跟踪问题开展研究,给出了基于UKF的自适应协同转弯跟踪算法,该算法充分利用了扩维技术和自适应渐消因子技术,不断实时估计转弯率,同时基于渐消因子调节过程噪声及其对应的增益,并对不敏卡尔曼滤波算法的采样范围进行自适应调节,使采样点更接近目标真实状态。仿真表明该算法在转弯率变化时获得了较好的跟踪性能,有效提升了对于转弯机动目标跟踪的准确性和稳定性。
This paper studies the accurate tracking problem under the condition of unknown or changing turning rate,an adaptive coordinated turning tracking algorithm based on UKF is proposed.The algorithm makes full use of the dimensionality extension technology and the adaptive fading factor technology,continuously estimates the turning rate in real time and adjusts the process noise and its corresponding gain based on the fading factor.At the same time,adaptively adjusts the sampling range of the unscented Kalman filter algorithm to make the sampling points closer to the real state of the target.Simulation results show that the algorithm achieves good tracking performance when the turning rate changes,and effectively improves the accuracy and stability of tracking maneuvering target.
作者
李盈萱
王中训
董云龙
Li Yingxuan;Wang Zhongxun;Dong Yunlong(School of Physics and Electronic Information,Yantai University,Yantai 264005,China;Information Fusion Institute,Naval Aviation University,Yantai 264001,China)
出处
《电子技术应用》
2022年第9期27-31,共5页
Application of Electronic Technique
