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作 者:鲁其兴 汤新民 周杨 LU Qixing;TANG Xinmin;ZHOU Yang(College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China;College of Transportation Science and Engineering,Civil Aviation University of China,Tianjin 300300,China)
机构地区:[1]南京航空航天大学民航学院,江苏南京211106 [2]中国民航大学交通科学与工程学院,天津300300
出 处:《系统工程与电子技术》2024年第2期675-683,共9页Systems Engineering and Electronics
基 金:国家自然科学基金(61773202,52072174);中国航空无线电电子研究所航空电子系统综合技术国防科技重点实验室基金(6142505180407);中国民航管理干部学院民航通用航空运行重点实验室开放基金(CAMICKFJJ-2019-04)资助课题。
摘 要:为了解决“当前”统计模型由于固定机动频率及假定加速度极限值,在复杂机场环境下机动目标跟踪性能降低的问题,提出一种双变量自适应的“当前”统计模型滤波算法。首先,利用加速度噪声一阶时间相关过程模型,推算出实时在线调整的机动频率。然后,根据位置状态估计值与加速度变化率,通过运动学理论模型和位置滤波残差,推导出实时在线更新的加速度方差,从理论上实现了模型自适应更新。最后,基于场面真实广播式自动相关监视(automatic dependent surveillance-broadcast,ADS-B)轨迹数据进行验证,结果表明改进的“当前”统计模型能够在非等间隔预测的基础上实现自适应调参,且在位置、速度和加速度上的轨迹拟合精度均得到了提高,并在速度和加速度跟踪误差方面得到了收敛。In order to solve the problem that the maneuvering target tracking performance of the“current”statistical model is degraded in complex airport environment due to fixed maneuvering frequency and assumed acceleration limit value,a bivariate adaptive“current”statistical model filtering algorithm is proposed.Initially,the maneuvering frequency of real-time online adjustment is calculated by using the first-order time dependent process model of acceleration noise.Then,according to the position state estimation value and the acceleration change rate,the acceleration variance of real-time online update is derived through the kinematics theoretical model and the position filtering residual,which theoretically realizes the adaptive update of the model.Finally,based on the real automatic dependent surveillance-broadcast(ADS-B)trajectory data of the scene,the verification results show that the improved“current”statistical model can achieve adaptive parameter adjustment on the basis of unequal interval prediction,and the trajectory fitting accuracies in position,velocity,and acceleration have been improved,and the tracking errors in velocity and acceleration have been converged.
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