Doppler Processors as Suboptimum Approaches for Detecting Targets with Unknown Doppler Shift

This paper tackles the detection of Swerling I targets with unknown Doppler shift in colored Gaussian interference. If the radar illuminated area is enough large, a Gaussian clutter model can be assumed. The average likelihood ratio has been formulated and sub-optimum approaches based on the Constra...

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Bibliographic Details
Main Authors: del Rey Maestre, N., Mata Moya, D., Jarabo Amores, M.P., de-Nicolas, J. Martin, Barcena Humanes, J.L.
Format: Conference Proceeding
Language:English
Subjects:
CGLR
Clutter
Detectors
Doppler shift
MTI
Neyman-Pearson detector
Program processors
Radar
radar detection
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Summary:This paper tackles the detection of Swerling I targets with unknown Doppler shift in colored Gaussian interference. If the radar illuminated area is enough large, a Gaussian clutter model can be assumed. The average likelihood ratio has been formulated and sub-optimum approaches based on the Constrained Generalized Likelihood Ratio (CGLR) analyzed. CGLR detectors have been considered as references solution for evaluating the detection performances and the computational cost of detection schemes including robust Doppler processor based on Moving Target Indicator (MTI) filters. The considered detection schemes are based on a Doppler filtering techniques to reduce the presence of clutter and an envelope detector. Two Doppler processor schemes have been considered: MTI filter designed for maximizing the improvement MTI factor averaged over all target Doppler shifts and a bank of MTI filters optimized for a set of target Doppler shifts. Results show that MTI filter-bank outperforms MTI averaged filter over a wider region of the Ω s variation interval reducing the computational cost with respect to the CGLR detector.
DOI:10.1109/CICSYN.2013.63