Situation Assessment: An End-to-End Process for the Detection of Objects of Interest

Author

Pollard, Evangeline ; Rombaut, Michele ; Pannetier, Benjamin

Author_Institution

IMARA, French Nat. Inst. for Res. in Comput. Sci. & Control (INRIA), Le Chesnay, France

Volume

49

Issue

4

fYear

2013

fDate

Oct-13

Firstpage

2195

Lastpage

2210

Abstract

Semiautomatic approaches are developed for wide area situation assessment in near-real-time. The two-step method consists of two granularity levels. The first entity assessment uses a new multi-target tracking (MTT) algorithm (hybridization of Gaussian mixture-Cardinalized probability hypothesis density (GM-CPHD) filter and multiple hypothesis tracker (MHT) with road constraints) on ground moving target indicator (GMTI) data. The situation is then assessed by detecting objects of interest such as convoys with other data types (synthetic aperture radar (SAR), video). These detections are based on Bayesian networks and their credibilistic counterpart.

Keywords

Gaussian processes; belief networks; filtering theory; object detection; probability; target tracking; Bayesian networks; GM-CPHD filter; GMTI data; Gaussian mixture-cardinalized probability hypothesis density filter; MHT; MTT algorithm; credibilistic counterpart; end-to-end process; granularity levels; ground moving target indicator data; multiple hypothesis tracker; multitarget tracking algorithm; object detection; semiautomatic approaches; wide area situation assessment; Adaptation models; Context; Estimation; Filtering algorithms; Radar tracking; Roads; Target tracking;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2013.6621810

Filename

6621810