强跟踪多模型估计器

Strong-Tracking Multiple Model Estimator

本文提出了一种基于最小二乘估计的强跟踪滤波器 (STF)单重渐消因子求解方法 .从参数自适应与模型自适应有机结合的角度出发 ,将STF与交互式多模型算法 (IMM)相结合 ,设计了强跟踪交互式多模型估计器(STMME) .仿真表明 :STMME在跟踪机动目标时 ,对速度 ,加速度的跟踪精度明显优于传统的IMM 。

Firstly we analyse the properties of Strong Tracking Filter (STF) and Interacting Multiple Model Algorithm and find that STF is a parameter adaptive algorithm and IMM is a model adaptive algorithm.It means that they may be combined effectively.Secondly we propose a new method based on the Least Squared Estimation to search for the fading factor in STF.After that,we design a Strong Tracking Multiple Model Estimator (STMME) by combining the new STF with IMM.Finally,the simulations show that STMME greatly improves accuracy of velocity and acceleration compared with the conditional IMM when tracking the maneuvering target.And the computation burden increases only 6%.