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Linear Prediction For Single Snapshot Multiple Target Doppler Estimation Under Possibly Moving Radar ClutterOztan, Baha Baran 01 August 2008 (has links) (PDF)
We have devised a processor for pulsed Doppler radars for multi-target detection in same folded range under land and moving clutter. To this end, we have investigated the estimation of parameters, i.e., frequencies, amplitudes, and phases, of complex exponentials that model target echoes under radar clutter characterized by antenna scanning modulation with observation limited to single snapshot, i.e., one burst. The Maximum Likelihood method of estimation is presented together with the bounds on estimates, i.e., Cramé / r-Rao bounds. We have analyzed linear prediction, together with its efficient implementation invented by Tufts & / Kumaresan, and compared its performance to other high resolution frequency estimation algorithms all modified to run under clutter. The essential part of the work is that line spectra estimation techniques model the clutter process also as a complex exponential. In addition, linear prediction combined with linear time&ndash / invariant maximum Signal to Interference Ratio (SIR) processor is analyzed. A technique to determine the model order, which is required by the frequency estimation algorithms, is presented that does not distinguish between targets and clutter. Clutter region concept is introduced to identify targets from clutter. The possibility to use these algorithms for target classification is briefly explained after providing a literature survey on helicopter echoes.
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Spectral And Statistical Analyses Of Experimental Radar Clutter DataKahyaoglu, Nazli Deniz 01 December 2010 (has links) (PDF)
The performance of radar detection and imaging systems strongly depends on the characteristics of radar clutter. In order to improve the radar signal processing algorithms, successful analysis and modeling of radar clutter are required. For a successful model of radar clutter, both the spectral and statistical characteristics of the clutter should be revealed. Within the scope of this study, an experimental radar data acquisition system is established to analyze radar clutter. The hardware and the data processing system are first verified using generic signals and then a set of measurements is taken in the open terrain. In this thesis, the limitations and problems encountered during the establishment of the system are explained in detail. The spectral and statistical analyses performed on the recorded data are examined. The temporal
and spatial behavior of the measured clutter data are explored. The hypothetical models proposed so far in the literature are tested on the experimental data and the fitting of models to the experimental data is confirmed using various goodness-of-fit tests. Finally, the results of the analyses are interpreted in the light of the radar system parameters and the characteristics of the illuminated terrain.
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Neural Network Classification Approach to Clutter Removal for UTM-Enabling Low-Altitude Radar SurveillanceEmshoff, Brandon Lane January 2021 (has links)
No description available.
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