Browsing by Subject "Ambiguity Function"

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    Range-doppler radar target detection using denoising within the compressive sensing framework
    (IEEE, 2014-09) Sevimli, R. Akın; Tofighi, Mohammad; Çetin, A. Enis
    Compressive sensing (CS) idea enables the reconstruction of a sparse signal from a small set of measurements. CS approach has applications in many practical areas. One of the areas is radar systems. In this article, the radar ambiguity function is denoised within the CS framework. A new denoising method on the projection onto the epigraph set of the convex function is also developed for this purpose. This approach is compared to the other CS reconstruction algorithms. Experimental results are presented1. © 2014 EURASIP.
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    Sıkıştırılmış algılama kullanarak Uzaklık-Doppler radar hedef tespiti
    (IEEE, 2014-04) Sevimli, R. Akın; Tofighi, Mohammad; Çetin, A. Enis
    Sıkıştırılmış algılama(SA) fikri, az sayıda ölçümlerden seyrek bir sinyalin geri çatımını mümkün kılar. SA yaklaşımı bir çok farklı alanda uygulamalara sahiptir. Bu alanlardan birisi de radar sistemleridir. Bu makalede, radar belirsizlik fonksiyonu (Ambiguity Function) SA çatısı altında gürültüden arındırılmıştır. Bu amaç için dışbükey fonksiyonun epigraf kümesine izdüşüm tabanlı yeni bir gürültüden arındırma metodu geliştirilmiştir. Bu yaklaşım, diğer SA geri çatım algoritmalarıyla karşılaştırılmıştır. Deneysel sonuçlar sunulmuştur.
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    Target detection and imaging on passive bistatic radar systems = Pasif bistatik radar sistemleri üzerinde hedef tespiti ve görüntülenmesi
    (2014) Sevimli, Rasim Akın
    Passive Bistatic Radar (PBR) systems have become more popular in recent years in many research communities and countries. Papers related to PBR systems have increasingly received significant attention in research. There are many target detection methods for PBR system in the literature. This thesis assumes a system scenario based on stereo FM signals as transmitters of opportunity. Ambiguity function (AF) is a function that determines the locations of targets in range-Doppler map turns out to be noisy in practice. This can cause a problem with low SNR-valued targets because they cannot be visible. To solve this problem, compressive sensing (CS) and projection onto the epigraph set of the `1 ball (PES-`1) are used to denoise the range-Doppler map. Some CS methods are applied to the system scenario, which are Basis Pursuit (BP), Orthogonal Matching Pursuit (OMP), Compressed Sampling Matching Pursuit (CoSaMP), Iterative Hard Thresholding (IHT). In addition, AF is generally used to determine the similarities between two signals. Therefore, different correlation methods can be also used to compare the surveillance and time delayed frequency shifted replica of the reference signal. Maximal Information Coefficient (MIC), Pearson correlation coefficient, Spearman’s rank correlation coefficient are used for the target detection. This thesis proposes a least squares (LS) based method which outperforms other correlation algorithms in terms of PSNR and SNR. Two LS coefficients are obtained from the real and imaginary parts of predicting the surveillance signal using the modulated reference signal. Norm of LS coefficients exhibit a peak at target locations. The proposed method detects close targets better than the ordinary AF method and decreases the number of sidelobes on multiple FM channels based the PBR system.