Open AccessMulti‐sensor track‐to‐track fusion with target existence in cluttered environments
Author(s) -
Lee Eui Hyuk,
Song Taek Lyul
Publication year - 2017
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.2016.0497
Subject(s) - track (disk drive) , computer science , tracking (education) , sensor fusion , probabilistic logic , fusion , tracking system , artificial intelligence , real time computing , computer vision , kalman filter , linguistics , philosophy , operating system , psychology , pedagogy
Multi‐sensor fusion for multiple target tracking in cluttered environments is needed for improving tracking accuracy and track maintenance over single sensor target tracking in real target tracking applications. A track quality measure, such as the probability of target existence, can be used when fusing local sensor tracks for false track discrimination at the fusion centre and to improve the performance of the track‐to‐track association. The track quality measure is a highly effective tool for track maintenance and lowers the computational load by sending tracks with a high probability of target existence to the track centre. In this study, the authors utilise the iterative joint‐integrated probabilistic data association technique for multi‐sensor distributed fusion systems. Track‐to‐track fusion performance also depends on distributed fusion architecture. The track‐to‐track fusion algorithm is evaluated in distributed fusion systems without memory, with memory, and with feedback. The track confirmation rates and position errors are simulated and compared with low‐level centralised fusion, which is theoretically optimal.