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A Knowledge Based Approach In Gmti For The Estimation Of The Clutter Covariance Matrix In Space Time Adaptive Processing

Ground Moving Target Indication (GMTI) operation relies on clutter suppression
techniques for the detection of slow moving ground targets in the presence of strong
radar returns from the ground. Space Time Adaptive Processing (STAP) techniques
provide a means to achieve this goal by adaptively forming the clutter suppression
filter, whose parameters are obtained using an estimated covariance matrix of the
clutter data. Therefore, the performance of the GMTI operation is directly aected
by the performance of the estimation process mentioned above. Knowledge based
techniques are applicable in applications such as the parametric estimation of the
clutter covariance matrix and the estimation of the clutter covariance matrix in a nonhomogeneous
clutter environment. In this study, a knowledge based approach which
makes use of both a priori and instantaneous data is proposed for the mentioned estimation
process. The proposed approach makes use of Shuttle Radar Topography
Mission (SRTM) data as well as instantaneous platform ownship data in order to determine
distributed homogeneous regions present in the region of interest / and afterwards
employs Doppler Beam Sharpening (DBS) maps along with the colored loading
technique for the blending process of the a priori data and the instantaneous data corresponding to the obtained homogeneous regions. A nonhomogeneity detector
(NHD) is also implemented for the elimination of discrete clutter and target-like signals
which may contaminate the STAP training data. Simulation results are presented
for both the knowledge aided and the traditional cases. Finally, the performance of
the STAP algorithm will be evaluated and compared for both cases. Results indicate
that by using the developed processing approach, detection of previously undetectable
targets become possible, and the overall number of false alarms is reduced.

Identiferoai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12615014/index.pdf
Date01 October 2012
CreatorsAnadol, Erman
ContributorsTanik, Yalcin
PublisherMETU
Source SetsMiddle East Technical Univ.
LanguageEnglish
Detected LanguageEnglish
TypeM.S. Thesis
Formattext/pdf
RightsAccess forbidden for 1 year

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