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Proceedings Paper

Model for the detection and tracking of multiple targets
Author(s): James A. Anderson; N. C. Mohanty; Pradeep Kumar Bhattacharya; A. S. King
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Paper Abstract

The detection and tracking of multiple targets in the presence of clutter in the infrared images involve the use of sophisticated algorithms and signal processing that are important aspects of the development of massively parallel processing skills. The problem is difficult if the target intensity is low and is of small size compared to the clutter. Further, the target size and velocity are usually unknown. It is desirable to obtain optimum filtering to detect low-intensity targets and to evaluate the performance of the filter and tracking algorithms based on observed data. The problem of tracking the targets by computer has been developed. However, an accurate clutter model is the key to precise target detection. Clutter is usually a non-stationary process. It is necessary to estimate the power spectral density of the clutter in real-time such that a multi-dimensional matched filter can be designed to detect the targets. This paper formulates the model and filter design.

Paper Details

Date Published: 5 July 1995
PDF: 7 pages
Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); doi: 10.1117/12.213012
Show Author Affiliations
James A. Anderson, Southern Univ. and A&M College (United States)
N. C. Mohanty, Southern Univ. and A&M College (United States)
Pradeep Kumar Bhattacharya, Southern Univ. and A&M College (United States)
A. S. King, Intel Corp. (United States)


Published in SPIE Proceedings Vol. 2484:
Signal Processing, Sensor Fusion, and Target Recognition IV
Ivan Kadar; Vibeke Libby, Editor(s)

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