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Proceedings Paper

Derivation of physics-based HRR moving target models
Author(s): Junshui Ma; Stanley C. Ahalt
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Paper Abstract

Although SAR has demonstrated excellent performance in stationary target identification, SAR resolution suffers in moving target scenarios. High Range Resolution (HRR) radar appears to be an attractive alternative in applications to moving target identification because HRR target signature can provide target scatterer information with high range resolution. Since many HRR processing steps, such as feature extraction and clutter suppression, are based on underlying modeling assumptions, devising a reliable physics-based HRR model for moving targets has become an increasingly important topic. In this paper, we derive a scattering-based HRR moving target model. However, the general form of the derived model is quite complex, and this complexity makes subsequent analysis difficult. We therefore simplify the complex model to obtain different simplified versions that facilitate the utility of the models. Simplifications is achieved by instantiating the parameters in this model with radar and target parameters from the real world, and then retaining only those terms with dominant value. A series of reliable, yet theoretically tractable models, are obtained with different degrees of simplification. The contributions of this paper are as follows: (1) Two new physics-based HRR moving target models with different degrees of simplification are presented; (2) These models make no assumptions regarding the distribution of the clutter; (3) Performance boundaries on the subsequent feature extraction algorithms are derived and delineated.

Paper Details

Date Published: 4 August 2000
PDF: 7 pages
Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); doi: 10.1117/12.395058
Show Author Affiliations
Junshui Ma, The Ohio State Univ. (United States)
Stanley C. Ahalt, The Ohio State Univ. (United States)

Published in SPIE Proceedings Vol. 4052:
Signal Processing, Sensor Fusion, and Target Recognition IX
Ivan Kadar, Editor(s)

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