DocumentCode :
263086
Title :
Group state estimation algorithm using Foliage Penetration GMTI radar detections
Author :
Mori, Shinsuke ; Hui Hoang ; Rago, Constantino ; Shea, Michael J. ; Davey, Patricia L. ; Arambel, Pablo O. ; Chee-Yee Chong ; Alter, Steve J.
fYear :
2014
fDate :
7-10 July 2014
Firstpage :
1
Lastpage :
8
Abstract :
This paper describes an algorithm for integrating detections from Foliage Penetrating (FOPEN) Ground Moving Target Indicator (GMTI) radar, to recognize groups of dismounts moving through dense foliage, and to estimate the group states, including the group sizes and the directions of their movements. Difficulties of processing FOPEN GMTI radar detections are best characterized as low target-state-dependent detection probabilities and high non-uniform persistent false alarm densities. To overcome these difficulties, we use the Sum-of-Gaussian (SOG) or Gaussian-Mixture (GM) Cardinalized Probability Hypothesis Density (CPHD) method to detect and track individual dismounts, and then, apply a group dynamics recognition method to the CPHD outputs to recognize the formation and the behavior of the dismounts groups.
Keywords :
Gaussian processes; mixture models; object detection; probability; radar detection; Gaussian-mixture; cardinalized probability hypothesis density; foliage penetration GMTI radar detections; ground moving target indicator; group dynamics recognition method; group state estimation algorithm; sum-of-Gaussian; Density functional theory; Radar cross-sections; Radar detection; Radar tracking; Target tracking; SOG-CPHD (GM-CPHD) tracking; foliage penetrating (FOPEN) GMTI radar; group state estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion (FUSION), 2014 17th International Conference on
Conference_Location :
Salamanca
Type :
conf
Filename :
6916154
Link To Document :
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