Content Gazette - August 2012 - 19

Call for Papers
IEEE Journal of Selected Topics in Signal Processing
Special Issue on Multi-target Tracking
The t rack-oriented multiple h ypothesis t racking ( MHT) ap proach h as b een es tablished as t he most accu rate multi-target t racking
algorithm o ver many years. Recently, the r andom f inite s et ( RFS) b ased al gorithms h ave drawn a great d eal o f at tention i n t he
tracking community. Some successful RFS based multi-target tracking algorithms are the probability hypothesis density (PHD) filter
cardinalized PHD (CPHD) filter and the multi-Bernoulli filters. These RFS-based filters can adaptively estimate the clutter model as
well d etection p robability p rofile from d ata. T his f eature is c urrently a bsent the MHT. M oreover, th e CPHD f ilter which is
comparable to the MHT, in the few attempts at benchmarking their performance, is only cubic in complexity. While there are a f ew
attempts to co mpare the performance o f the MHT and Gaussian mixture CPHD (GM-CPHD) a r igorous and detailed evaluation of
these advanced tracking algorithms in terms of tracking accuracy and computational complexity is needed at present. In many radar
tracking p roblems, th e ta rget is modeled a s a p oint ta rget a nd a t most o ne measurement is a ssumed to o riginate from a ta rget in a
dwell/scan. However, for a high range resolution (HRR) radar sensor, measurement on the target extent can be obtained. Similarly, a
video or electro-optical (EO) sensor can image an extended target. Thus, measurements by video or EO sensors demand the need for
extended target tracking. If a group of closely spaced targets are moving together, then it is not possible for a sensor (e.g. a ground
moving target indicator (GMTI) radar sensor) to resolve all targets in the group. Hence, a group tracking algorithm is needed for this
class of problems. Due to increasing terrorist activities in recent years, the problem of tracking multiple contaminant clouds has drawn
a great deal of interest. The filtering distribution for this class of problems is complex and highly nonlinear. Moreover, the dimension
of t he s tate s pace i s high a nd M arkov ch ain M onte Carlo ( MCMC) t echniques h ave been p opular. F or t he multi-target t racking
problem using the over-the-horizon radar (O THR), there can b e multiple detections for a target i n a d well due t o reflection f rom
multiple ionosphere layers. This requires advanced algorithms in both the MHT and RFS based tracking algorithms.
Topics of interest include, but are not limited to:
* Random Finite Set multi-target filters
* Extended object and group tracking
* Tracking of multiple contaminant clouds
* Multi-target tracking using over-the-horizon radar (OTHR) sensor
* Tracking airborne targets using the passive coherent location (PCL) system
* Tracking space debris
* Joint tracking and classification using kinematic and feature measurements
* Network-centric Multi-platform target tracking
* Multi-target tracking and cooperative positioning in a system of networked sensors
* Data registration error estimation in multi-sensor multi-target tracking systems.
* Robust multitarget tracking in the presence of model uncertainty
* Coupled tracking and sensor management
* Rigorous performance evaluation of multiple target tracking algorithms
* Performance bounds and metrics for multi target tracking
* Track-before-detect

Suggested time table for paper submission:
Manuscript submission due: September 1, 2012
First review completed: November 1, 2012
Revised manuscript due: December 15, 2012
Second review completed: February 1, 2013
Final manuscript due: February 15, 2013

Contact information for guest editors

Dr. Mahendra Mallick, mahendra.mallick@gmail.com, Propagation Research Associates, Inc., Marietta, GA, USA.
Prof. Ba Ba-Ngu Vo, ba-ngu.vo@uwa.edu.au, University of Western Australia, Perth, Australia.
Prof. T. Kirubarajan, kiruba@mcmaster.ca, McMaster University, Hamilton, Ontario, Canada.
Dr. Sanjeev Arulampalam, Sanjeev.Arulampalam@dsto.defence.gov.au, Defence Science and Technology Organisation (DSTO),
Edinburgh, Australia.

1
www.signalprocessingsociety.org

[19]

AUGUST 2012


http://www.signalprocessingsociety.org

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