Open AccessMultiple model tracking of manoeuvring targets accounting for standoff jamming information
Author(s) -
Hou Jing,
Li X. Rong,
Jing Zhanrong
Publication year - 2013
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/iet-rsn.2012.0279
Subject(s) - jamming , gaussian , likelihood function , algorithm , tracking (education) , function (biology) , computer science , gaussian network model , probability density function , artificial intelligence , mathematics , statistics , estimation theory , physics , psychology , pedagogy , quantum mechanics , evolutionary biology , biology , thermodynamics
An Interacting Multiple Model (IMM) algorithm for manoeuvring target tracking in the presence of standoff jammer is proposed. In the IMM, the conventional Gaussian likelihood is replaced with a Gaussian sum (GS) likelihood, derived from a sensor model accounting for both the measurements and jamming information. Thus, the model‐conditioned posterior probability density function of the state is also a weighted sum of Gaussians but with recalculated weights. As a result of the combination of multiple models and jamming information, the proposed approach has a significant performance improvement when both manoeuvre and jamming occur. Simulation results show that the proposed approach outperforms the original IMM algorithm as well as the GS filters with only one model in terms of track loss and track accuracy.