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KNOWLEDGE BASED ADAPTIVE PROCESSING FOR GROUND MOVING TARGET INDICATION
 

Summary: KNOWLEDGE BASED ADAPTIVE PROCESSING FOR
GROUND MOVING TARGET INDICATION
Raviraj Adve1, Todd Hale, and Michael Wicks
Raviraj Adve Todd Hale Michael Wicks
Dept. of Elec. and Comp. Engg. Air Force Research Laboratory
University of Toronto Air Force Inst. of Technology Sensors Directorate
10 King's College Rd. 2950 P Street 26 Electronics Parkway
Toronto Wright-Patterson AFB Rome
Ontario M5S 3G4, Canada OH 45324, USA NY 13403, USA
Abstract
This paper presents a preliminary knowledge based approach to Space-Time Adaptive Processing
(STAP) for ground moving target indication from an airborne platform. The KB-processor accounts
for practical aspects of adaptive processing, including detection and processing of non-homogeneous
data, appropriate selection of training data, and accounting for array effects such as mutual coupling
and channel mismatch. In combining these hitherto separate STAP issues into a unified approach,
this paper furthers the move of STAP from theory to practice. The KB-approach is tested using
measured data from the Multi-Channel Airborne Radar Measurements program.
1 Introduction
Space-Time Adaptive Processing (STAP) techniques promise to be the best means to detect weak
targets in severe, dynamic, interference scenarios including clutter and jamming. STAP techniques

  

Source: Adve, Raviraj - Department of Electrical and Computer Engineering, University of Toronto

 

Collections: Engineering