Paper
20 August 2003 Adaptive system for detecting stationary targets with real-aperture radar
Author Affiliations +
Abstract
Trained algorithms are required for detecting stationary targets with practical real-beam radars. The parameters of these algorithms are unique to each site or clutter class. A problem arises when an algorithm trained on one clutter class is applied, perhaps inadvertently, to another class. In this case, the performance of the system can degrade to an unacceptable level. We have developed a system that adapts, online, the parameters of the algorithm to the encountered clutter type. This system consists of two neural networks - one for adapting the coefficients of the algorithm and the other for adapting the threshold level.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hiralal C. Khatri, Francois Koenig, Roberto Innocenti, and Kenneth I. Ranney "Adaptive system for detecting stationary targets with real-aperture radar", Proc. SPIE 5077, Passive Millimeter-Wave Imaging Technology VI and Radar Sensor Technology VII, (20 August 2003); https://doi.org/10.1117/12.488641
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Neural networks

Radar

Target detection

Detection and tracking algorithms

Synthetic aperture radar

Algorithm development

Neurons

Back to Top