基于非机动单站的目标运动状态无偏估计OA北大核心CSTPCD

To address the challenge of target tracking for non-maneuvering,single-station setups in long-range scenarios,we propose a target tracking algorithm leveraging three-dimensional angle of arrival data,characterized by its asymptotically unbiased nature.Initially,we construct a motion and observation model centered on a non-maneuvering single station,assuming a known rate prior,and examine the system's ob-servability.To tackle the bias inherent in the pseudo linear least squares algorithm,we introduce a con-strained total least squares method that demonstrates asymptotically unbiased properties,with its effective-ness validated through simulations.In tests involving three-dimensional angle tracking over distances in the hundred-kilometer range,with angle measurement standard deviations at 0.1°,0.2°,and 0.3°,the con-strained total least squares method achieves a time-average relative distance error of 6%,12%,and 21%within 50-100 seconds,respectively,and an absolute position error of 9 km,19 km,and 35 km;at initial distances of 70,140,and 280 km,the errors are 1%,6%,and 30%for the same duration,with absolute errors of 0.7 km,9 km,and 30 km.Notably,the relative distance error can be reduced to below 10%within 100 seconds,marking a significant precision enhancement,while maintaining operational speed comparable to the pseudo linear least squares method.The constrained total least squares approach exhibits rapid convergence,high accuracy,and swift processing,showing resilience against angle measurement er-rors and initial distance variations.It offers a robust solution for 3D angle of arrival tracking of non-maneu-vering single-station targets in distant settings.