Paper
17 May 2016 Trackability: resolvability of two closely-spaced targets
Steven Schoenecker, Peter Willett, Yaakov Bar-Shalom
Author Affiliations +
Abstract
Recent research has developed a novel framework for determining target trackability using the Maximum Likelihood Probabilistic Multi-Hypothesis Tracker (ML-PMHT). This framework allows for the calculation of the PDF of the peak point in the ML-PMHT log-likelihood ratio (LLR) due to clutter as well as the PDF of the peak point in the LLR due to the target. If it is possible to reliably discriminate between the peak target PDF and the peak clutter PDF, then the target is able to be tracked. We expand on this framework by adding a second target and determining the conditions under which both targets can be individually tracked. This work develops the first step toward that goal — it introduces the second target to the framework (an interfering target), and determines how close it can get to the original target before the peak generated by the original target is no longer distinguishable from the peak generated by the interfering target. At this point, the original target will no longer be trackable.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steven Schoenecker, Peter Willett, and Yaakov Bar-Shalom "Trackability: resolvability of two closely-spaced targets", Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 984205 (17 May 2016); https://doi.org/10.1117/12.2223171
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Cited by 1 scholarly publication.
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KEYWORDS
Palladium

Target detection

Detection and tracking algorithms

Photodynamic therapy

Pulmonary function tests

Control systems

Convolution

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