Paper
30 August 1989 Multitarget Identification In Airborne Surveillance
Adam Caromicoli, Thomas Kurien
Author Affiliations +
Abstract
This paper describes a Bayesian multitarget identification algorithm for a multisensor airborne surveillance system. The identification algorithm represents a part of the joint multitarget tracking and identification algorithm derived for the airborne surveillance system. We show that the addition of identity to the position and velocity state for each target improves the capability to associate sensor reports with target tracks. This paper also formulates a generalized model for the sensor observables used for target identification: the generalized model is used to develop a recursive identification algorithm; it is also used to evaluate the amount of information provided by each of the sensor observables for target identification. Results obtained from a prototype of the decision aid demonstrate the effectiveness of the identification algorithm to identify targets in a multitarget surveillance scenario.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Adam Caromicoli and Thomas Kurien "Multitarget Identification In Airborne Surveillance", Proc. SPIE 1098, Aerospace Pattern Recognition, (30 August 1989); https://doi.org/10.1117/12.960435
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Sensors

Detection and tracking algorithms

Target recognition

Surveillance

Algorithm development

Kinematics

Target detection

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