Browsing by Subject "Radar systems"

Now showing 1 - 8 of 8

Open Access
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.
Open Access
Cross-term free based bistatic radar system using sparse least squares
(SPIE, 2015) Sevimli, R. Akın; Çetin, A. Enis
Passive Bistatic Radar (PBR) systems use illuminators of opportunity, such as FM, TV, and DAB broadcasts. The most common illuminator of opportunity used in PBR systems is the FM radio stations. Single FM channel based PBR systems do not have high range resolution and may turn out to be noisy. In order to enhance the range resolution of the PBR systems algorithms using several FM channels at the same time are proposed. In standard methods, consecutive FM channels are translated to baseband as is and fed to the matched filter to compute the range-Doppler map. Multichannel FM based PBR systems have better range resolution than single channel systems. However superious sidelobe peaks occur as a side effect. In this article, we linearly predict the surveillance signal using the modulated and delayed reference signal components. We vary the modulation frequency and the delay to cover the entire range-Doppler plane. Whenever there is a target at a specific range value and Doppler value the prediction error is minimized. The cost function of the linear prediction equation has three components. The first term is the real-part of the ordinary least squares term, the second-Term is the imaginary part of the least squares and the third component is the l2-norm of the prediction coefficients. Separate minimization of real and imaginary parts reduces the side lobes and decrease the noise level of the range-Doppler map. The third term enforces the sparse solution on the least squares problem. We experimentally observed that this approach is better than both the standard least squares and other sparse least squares approaches in terms of side lobes. Extensive simulation examples will be presented in the final form of the paper.
Open Access
Joint multi-emitter signal seperation and angle of arrival estimation via variational mode decomposition
(IEEE, 2017) Soğanlı, Abdurrahim; Arıkan, Orhan
In this work, we propose a framework which separates multi-emitter signals arriving to uniform linear antenna receiver system. Proposed model uses a combination of variational mode decomposition (VMD) and space alternating expectation maximization (SAGE) algorithms. Former one separates emitter signals and estimates their frequencies while in the second part channel parameters (relative phases, angle of arrivals) are estimated using SAGE algorithm. Experimental results have showed that the proposed model can simultaneously estimates angle of arrivals of the multi-emitter signals working at the same frequencies.
Open Access
Range resolution improvement in passive coherent location radar systems using multiple FM radio channels
(IET, 2006) Taşdelen, Akif Sinan; Köymen, Hayrettin
Passive coherent location (PCL) radar systems that use single FM radio channel signal as illuminator of opportunity have limited range resolution due to low modulation bandwidth and high dependence on the content that is being broadcasted from the FM station. An improvement in range resolution is obtained by using multiple adjacent FM channels, emitted from co-sited transmitters, which is often the case in large towns in countries, where the FM channel allocations are relatively weakly regulated. The proposed scheme computes the autocorrelation function of the signal directly received from the FM co-located transmitter, and compares it to the cross-ambiguity function, obtained from direct and target scattered signals. The geometry of the problem is like in the case of monostatic radar. The range information is obtained by the delay between the cross-ambiguity function and the autocorrelation function. It is shown that down to -37dB signal to noise ratio (SNR) the autocorrelation function of 7 FM channels with different contents can be successfully extracted from the cross-ambiguity function. The detection of the time delays is a linear estimation problem. The issue of time-delay estimation is a known topic of research. A powerful estimator can be found.
Open Access
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.
Open Access
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.
Open Access
Simulation of real beam ground mapping mode of a pulsed radar
(IEEE, 2006) Onart, Serkan; Arıkan, Orhan
A Matlab© based realistic simulation software is developed for Real Beam Ground Mapping (RBGM) mode of a pulsed air-borne radar. The developed software successfully simulates the effects of basic radar parameters for the real beam mapping mode. A zero level Digital Terrain Elevation Data (DiTED) is used for terrain model. Radar return is calculated for a stationary antenna at a given height from the ground and tilt angle. Simulations can represent the effects of terrain occulting, shadowing, incidence angle depended scattering, range attenuation, antenna parameters (pattern, gain, beam width e.g.) and transmitter parameters (frequency, output power, pulse width, PRF e.g.) on radar returns for both sector and circular scans.
Open Access
Successive cancelation approach for doppler frequency estimation in pulse doppler radar systems
(IEEE, 2010) Soğancı, Hamza; Gezici, Sinan
In this paper, a successive cancelation approach is proposed to estimate Doppler frequencies of targets in pulse Doppler radar systems. This technique utilizes the Doppler domain waveform structure of the received signal coming from a point target after matched filtering and pulse Doppler processing steps. The proposed technique is an iterative algorithm. In each iteration, a target that minimizes a cost function is found, and the signal coming from that target is subtracted from the total received signal. These steps are repeated until there are no more targets. The global minimum value of the cost function in each iteration is found via particle swarm optimization (PSO). Performance of this technique is compared with the optimal maximum likelihood solution for various signal-to-noise ratio (SNR) values based on Monte Carlo simulations.