JOURNAL ARTICLE

<title>Moving target tracking using multiple sensors</title>

Manikant D. LodayaRichard Bottone

Year: 2000 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 4048 Pages: 333-344   Publisher: SPIE

Abstract

Multiple Sensors improve tracking performance. The Kinematic Automatic Tracker (KAT) may drop a track when the Joint STARS aircraft is turning or the track is screened. In situation like this multiple sensors can improve tracking performance. Two algorithms for tracking moving targets using multiple sensors are developed. Both algorithms are based on modifying the existing KAT architecture. The first approach is based on the use of the best sensor's Moving Target Indicators (MTIs) when the sensors have overlapping dwells. The second and more general approach uses the report-to-track fusion algorithm. The first approach is frame- based (with multiple dwells), whereas the second approach is dwell- based. The tracking results are presented for the first algorithm for a two-sensors Korean scenario with increasing complexity. We also show the advantages of using multiple sensors for tracking using a simulated Korea scenario. For the report-to-track fusion algorithm, we present preliminary tracking results for a simulated scenario using two UAV sensors.

Keywords:
Computer science Tracking (education) Computer vision Sensor fusion Artificial intelligence Track (disk drive) Radar tracker Tracking system Real-time computing Kalman filter Radar

Metrics

5
Cited By
0.42
FWCI (Field Weighted Citation Impact)
0
Refs
0.72
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence

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