Re-entry vehicle tracking with a new multiple model estimation applicable to highly non-linear dynamics

• Published in: IET radar, sonar & navigation Vol. 9; no. 5; pp. 581 - 588
• Main Author: Shin, Sang-Jin
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.06.2015
• Subjects: Algorithms; Derivation; Dynamical systems; entry, descent and landing (spacecraft); filtering theory; highly nonlinear dynamic system; IMM algorithm; multiple model estimation algorithm; Navigation; nonlinear dynamical systems; Nonlinear dynamics; nonlinear estimation; object tracking; re‐entry vehicle tracking; Sonar; Tracking; tracking filters; Vehicles; multiple model estimation algorithm; entry, descent and landing (spacecraft); filtering theory; vehicles; object tracking; nonlinear estimation; highly nonlinear dynamic system; IMM algorithm; nonlinear dynamical systems; tracking filters; re-entry vehicle tracking
• ISSN: 1751-8784; 1751-8792
• DOI: 10.1049/iet-rsn.2014.0083

This study proposes a new multiple model estimation algorithm. Although the derivation of the proposed algorithm is different from the existing interacting multiple model (IMM), both algorithms are exactly the same if the dynamic system is linear. However, for non-linear systems, it appears that the proposed algorithm is different from the IMM algorithm. The proposed algorithm is applied to the tracking problem of re-entry vehicles that is known as highly non-linear system. The estimation performance of the proposed algorithm is compared with IMM by a series of simulation runs. The result shows that the proposed algorithm improves the estimation performance.