Mourad Barkat

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In this paper, we present two novel algorithms for automatic censoring of radar interfering targets in log-normal clutter. The proposed algorithms consist of two steps: removing the corrupted reference cells (censoring) and the actual detection. Both steps are performed dynamically by using a suitable set of ranked cells to estimate the unknown background(More)
In this paper, a new feature points extraction method based on the nonsubsampled contourlet transform (NSCT) is proposed for image registration. The primary motivation of this work is to determine the effectiveness of the NSCT transform for feature points extraction for the use of image registration. The performance of the proposed NSCT-based registration(More)
The effect of the PRF on the performances of the reduced rank STAP is discussed. The numerical evaluation is based on three different models of changing the PRF, namely quadratic, pseudorandom and chaotic with two methods of reduction of the rank: Principle Components (PC) and Signal to Interference Noise Ratio (SINR metric). Rank reduction reduces the(More)
In this paper, we address the problem of automatic target detection in Weibull clutter and multiple target situations, without any prior knowledge of neither the non stationary clutter statistics in which the radar operates nor the number of outliers that may be present in the reference window. In doing this, we develop the Forward and Backward Order(More)