
Proceedings Paper
A multiple IMM approach with unbiased mixing for thrusting projectilesFormat | Member Price | Non-Member Price |
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Paper Abstract
This paper presents a multiple interacting multiple model (MIMM) procedure to estimate the state of thrusting/
ballistic projectiles in the atmosphere for the purpose of impact point prediction (IPP). Given a very short
time span of observations, the strong interaction between drag and thrust in the dynamic model, in the sense of
ambiguity in the estimation, significantly affects the estimation performance and the final IPP accuracy. This
leads to the need to use an MIMM estimator with various initial drag coefficient estimates. The modes of each
IMM estimator are for the thrusting and the ballistic phases and different extended Kalman filters (EKF) are
used as the mode-matched filters with different dimension states. A novel unbiased mixing procedure for an IMM
estimator is introduced to deal with state estimates with unequal dimensions, as is the case for the thrusting and
ballistic models. The IPP is carried out at the end of the observation period by using the most probable mode
of the selected IMM estimator, the latter being the one with the highest likelihood in the MIMM approach.
Paper Details
Date Published: 5 May 2011
PDF: 13 pages
Proc. SPIE 8050, Signal Processing, Sensor Fusion, and Target Recognition XX, 805006 (5 May 2011); doi: 10.1117/12.882841
Published in SPIE Proceedings Vol. 8050:
Signal Processing, Sensor Fusion, and Target Recognition XX
Ivan Kadar, Editor(s)
PDF: 13 pages
Proc. SPIE 8050, Signal Processing, Sensor Fusion, and Target Recognition XX, 805006 (5 May 2011); doi: 10.1117/12.882841
Show Author Affiliations
Ting Yuan, Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)
Peter Willett, Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)
Peter Willett, Univ. of Connecticut (United States)
E. Mozeson, Univ. of Connecticut (United States)
S. Pollak, Univ. of Connecticut (United States)
David Hardiman, AMRDEC (United States)
S. Pollak, Univ. of Connecticut (United States)
David Hardiman, AMRDEC (United States)
Published in SPIE Proceedings Vol. 8050:
Signal Processing, Sensor Fusion, and Target Recognition XX
Ivan Kadar, Editor(s)
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