The aim of this study is to analyze the influence of neglecting K distributed clutter texture on wideband radar distributed targets detection. At first, the texture and the speckle of K clutter are researched and the Probability Density Function (PDF) of K clutter and its texture are derived, then the optimal detector by Neyman-Pearson (NP) is proposed, by contrast, another detector-Suboptimum Generalized Likelihood Ratio Test (GLRT) neglecting the clutter texture is given. Next, the estimation of covariance matrix is introduced. Finally, the numerical results are presented by means of Monte Carlo simulation strategy and the simulation results highlight that the performance loss of the 2 detectors in different shaping parameter, the result shows that the performance loss of the detector in K distributed clutter less than 1 db due to the texture is neglected and adaptively estimating the covariance matrix and the K clutter texture can be neglected on wideband radar targets detection.

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