Browsing by Subject "Radar signal processing"

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    Approximate computation of DFT without performing any multiplications: application to radar signal processing
    (IEEE, 2014) Arslan, Musa Tunç; Bozkurt, Alican; Sevimli, Rasim Akın; Akbaş, Cem Emre; Çetin, A. Enis
    In many radar problems it is not necessary to compute the ambiguity function in a perfect manner. In this article a new multiplication free algorithm for approximate computation of the ambiguity function is introduced. All multiplications (a × b) in the ambiguity function are replaced by an operator which computes sign(a × b)(a + b). The new transform is especially useful when the signal processing algorithm requires correlations. Ambiguity function in radar signal processing requires high number of correlations and DFT computations. This new additive operator enables an approximate computation of the ambiguity function without requiring any multiplications. Simulation examples involving passive radars are presented.
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    Compressed sensing on ambiguity function domain for high resolution detection
    (IEEE, 2010) Güldoǧan, Mehmet B.; Pilancı, Mert; Arıkan, Orhan
    In this paper, by using compressed sensing techniques, a new approach to achieve robust high resolution detection in sparse multipath channels is presented. Currently used sparse reconstruction techniques are not immediately applicable in wireless channel modeling and radar signal processing. Here, we make use of the cross-ambiguity function (CAF) and transformed the reconstruction problem from time to delay-Doppler domain for efficient exploitation of the delay-Doppler diversity of the multipath components. Simulation results quantify the performance gain and robustness obtained by this new CAF based compressed sensing approach. ©2010 IEEE.
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    Compressive sensing based target detection in delay-doppler radars
    (IEEE, 2013) Teke, Oguzhan; Arıkan, Orhan; Gürbüz, A.C.
    Compressive Sensing theory shows that, a sparse signal can be reconstructed from its sub-Nyquist rate random samples. With this property, CS approach has many applications. Radar systems, which deal with sparse signal due to its nature, is one of the important application of CS theory. Even if CS approach is suitable for radar systems, classical detections schemes under Neyman-Pearson formulations may result high probability of false alarm, when CS approach is used, especially if the target has off-grid parameters. In this study, a new detection scheme which enables CS techniques to be used in radar systems is investigated. © 2013 IEEE.
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    FMCW radar sinyalleri ile LSTM tabanlı hedef sınıflandırması
    (Bilkent University, 2021-07-19) Güneş, Oytun; Morgül, Ömer
    Dünya Sağlık Örgütü’ne (WHO) göre, her yıl trafik kazalarından kaynaklı yaklaşık 20-50 milyon yaralanma olmaktadır. Yaralanmaların çoğu savunmasız yayalar, bisikletliler ve motosikletliler arasındadır. Otonom araçlar (OA) bu soruna mükemmel bir çözüm gibi görünmektedir. OA’lardaki radar sensörleri, hem hız ve menzili ölçtüğü, hem de kötü hava koşullarında çalışabildiği için etkili bir sensördür. Bu çalışmada ilk olarak, 24GHz FMCW radar sinyallerini simüle ederek 300 spektrogram içeren bir veri seti oluşturulmuştur. Bir 2 boyutlu simülasyon ortamında, orijine tek bir radar yerleştirildi ve bu dikdörtgen alana farklı parametrelerde diğer nesneler (örneğin yükseklik, yön, hız) yerleştirildi. Ardından, spektrogram görüntüleri üzerindeki Mikro-Doppler model özellikleri çıkarıldı ve Uzun Kısa Süreli Bellek Ağları (LSTM’ler) ile eğitildi. Önerilen yaklaşımın etkinliği test edildi, test setinde %95 ortalama doğruluk ve F1 skoru elde edildi, sonuçta diğer bazı yöntemlerden daha iyi performans gösterdi.
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    Radar fingerprint extraction via variational mode decomposition
    (IEEE, 2017) Gök, Gökhan; Alp, Y. K.; Altıparmak, F.
    In this paper, a novel method for extracting radar fingerprint using the unintentional modulation on radar signals is proposed. Proposed technique decomposes the unintentional modulations into its components using Variational Mode Decomposition (VMD) technique. Then, features that characterize each component are calculated. Simulations using real radar data show that proposed technique can classify radars in the dataset with high performance.
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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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    SNR improvement in electronic support measures systems via pulse integration
    (IEEE, 2017) Gök, Gökhan; Alp, Y. K.
    In ESM (Electronic Support Measures) systems, detection of intentional or unintentional modulation on pulses requires high SNR. By integrating the collected pulses emitted from the radar, SNR can be increased. For utilizing pulse integration, all the pulses should be aligned in time very accurately. In this work, we propose a new method, which estimates the time shifts between the pulses with very high accuracy and resolution. Experiments on both synthetic and real data sets show that proposed method aligns the radar pulses very successfully.