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      Adaptive Detectors for Two Types of Subspace Targets in an Inverse Gamma Textured Background

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          Abstract

          Considering an inverse Gamma prior distribution model for texture, the adaptive detection problems for both first order Gaussian and second order Gaussian subspace targets are researched in a compound Gaussian sea clutter. Test statistics are derived on the basis of the two-step generalized likelihood ratio test. From these tests, new adaptive detectors are proposed by substituting the covariance matrix with estimation results from the Sample Covariance Matrix (SCM), normalized SCM, and fixed point estimator. The proposed detectors consider the prior distribution model for sea clutter during the design stage, and they model parameters that match the working environment during the detection stage. Analysis and validation results indicate that the detection performance of the proposed detectors out performs existing AMF (Adaptive Matched Filter, AMF) and ANMF (Adaptive Normalized Matched Filter, ANMF) detectors.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 June 2017
          : 6
          : 3
          : 275-284
          Affiliations
          [1 ] (Department of Electronic and Information Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, China)
          Article
          68c69796320a4a6d87c4d8d954da30f3
          10.12000/JR16088

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Categories
          Technology (General)
          T1-995

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