This paper investigates the problem of ground vehicle tracking with a Ground Moving Target Indicator (GMTI)
radar. In practice, the movement of ground vehicles may involve several different manoeuvring types (acceleration,
deceleration, standstill, etc.). Consequently, the GMTI radar may lose measurements when the radial velocity of
the ground vehicle is below a threshold, i.e. falling into the Doppler blind region. In this paper, to incorporate the
information gathered from normal measurements and knowledge on the Doppler blindness constraint, we develop an
enhanced particle filtering method for which the importance distributions are inspired by a recent noise related doppler
blind (NRDB) filtering algorithm for GMTI tracking. Specifically, when constructing the importance distributions, the
proposed particle filter takes the advantages of the efficient NRDB algorithm by applying the extended Kalman filter
and its generalization for interval-censored measurements. In addition, the linearization and Gaussian approximations
in the NRDB algorithm are corrected by the weighting process of the developed filtering method to achieve a more
accurate GMTI tracking performance. The simulation results show that the proposed method substantially outperforms
the existing methods for the GMTI tracking problem.
Funding
This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Grant number EP/J011525/1. Dr. Miao Yu’s involvement was supported by the EPSRC Grant number EP/K014307/1 and the MOD University Defence Research Collaboration in Signal Processing.
History
School
Aeronautical, Automotive, Chemical and Materials Engineering
Department
Aeronautical and Automotive Engineering
Published in
IEEE Transactions on Aerospace and Electronic Systems
Volume
52
Issue
3
Pages
1408-1420
Citation
YU, M. ...et al., 2016. An enhanced particle filtering method for GMTI radar tracking. IEEE Transactions on Aerospace and Electronic Systems, 52(3), pp.1408-1420.
This is an Open Access Article. It is published by IEEE under the Creative Commons Attribution 3.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/