Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7486
Title: Sparsity Based Robust Stretch Processing
Authors: İlhan, İhsan
Gürbüz, Ali Cafer
Arıkan, Orhan
Keywords: [No Keywords]
Issue Date: 2015
Publisher: IEEE
Source: IEEE International Conference on Digital Signal Processing (DSP) -- JUL 21-24, 2015 -- Singapore, SINGAPORE
Abstract: Strecth Processing (SP) is a radar signal processing technique that provides high-range resolution with processing large bandwidth signals with lower rate Analog to Digital Converter(ADC)s. The range resolution of the large bandwidth signal is obtained through looking into a limited range window and low rate ADC samples. The target space in the observed range window is sparse and Compressive sensing(CS) is an important tool to further decrease the number of measurements and sparsely reconstruct the target space for sparse scenes with a known basis which is the Fourier basis in the general application of SP. Although classical CS techniques might be directly applied to SP, due to off-grid targets reconstruction performance degrades. In this paper, applicability of compressive sensing framework and its sparse signal recovery techniques to strecth processing is studied considering off-grid cases. For sparsity based robust SP, Perturbed Parameter Orthogonal Matching Pursuit(PPOMP) algorithm is proposed. PPOMP is an iterative technique that estimates off-grid target parameters through a gradient descent. To compute the error between actual and reconstructed parameters, Earth Movers Distance(EMD) is used. Performance of proposed algorithm are compared with classical CS and SP techniques.
URI: https://hdl.handle.net/20.500.11851/7486
ISBN: 978-1-4799-8058-1
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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