Comparison of Single-point and Two-point Difference Track Initiation Algorithms using Position Measurements

摘要：

We consider the problem of initializing the tracking filter of a target moving with nearly constant velocity when position-only (1D, 2D or 3D) measurements are available. It is known that the Kalman filter is optimal for such a problem,provided it is correctly initialized. We compare a single-point and the well- known two-point difference track initialization algorithms. We analytically show that if the process noise approaches zero and the maximum speed of a target used to initialize the velocity variance approaches infinity, then the singlepoint algorithm reduces to the two-point difference algorithm.We present numerical results that show that the single-point algorithm performs consistently better than the two-point difference algorithm in the mean square error sense. We also present analytical results that support the conjecture that this is true in general.

关键词： Track initiation Kalman filter unbiased estimator minimum mean square error

作者: M.Mallick B.F.La Scala

作者单位: 1048 Highland Drive Del Mar, CA 921014, USA Melbourne Systems Laboratory Dept of Electrical & Electronic Engineering University of Melbourne Vic

会议类型: 国际会议

会议名称: The International Colloquium on Onformation Fusion 2007(2007年国际信息融合研讨会)

会议地点: 西安

会议语种:英文

页码: 45-52

在线出版日期: 2007-08-22（万方平台首次上网日期，不代表论文的发表时间）