Interacting multiple model tracking algorithm fusing input estimation and best linear unbiased estimation filter

• Published in: IET radar, sonar & navigation sonar & navigation, 2017-01, Vol.11 (1), p.70-77
• Main Authors: Sheng, Hu, Zhao, Wenbo, Wang, Jingen
• Format: Article
• Language: English
• Subjects: adaptive signal detection; adaptive tracking algorithm; Algorithms; best linear unbiased estimation filter; BLUE filter; constant velocity motion; CV motion; fusing input estimation; IMM‐IE; innovation sequence modification technique; interacting multiple‐model tracking algorithm; manoeuver detection; manoeuver estimation; manoeuvre fluctuation; Manoeuvring; manoeuvring target tracking; MIE; modified input estimator; Navigation; Research Article; robust tracking; Robustness; Sonar; Target tracking; Tracking; tracking filters; Tradeoffs
• ISSN: 1751-8784; 1751-8792; 1751-8792
• DOI: 10.1049/iet-rsn.2015.0657

In manoeuvring target tracking, a primary tradeoff is the robust tracking of manoeuvres against the accurate tracking of constant velocity (CV) motion. To achieve this goal, an interacting multiple model (IMM) algorithm fusing input estimation (IE) and best linear unbiased estimation (BLUE) filter is presented. First, the constant input assumption of IE is modified to track possible manoeuvre fluctuation. Then, an innovation sequence modification technique is proposed so manoeuvre can be detected and estimated sequentially. With improvements above, a modified input estimator (MIE) is designed to track varying manoeuvres. In view of the optimal tracking of BLUE filter for CV motion, MIE and BLUE filter are fused within IMM framework to generate an overall adaptive tracking algorithm. Simulation results reveal the proposed approach yields better accuracy for CV tracking and robustness for manoeuvre tracking.