Browsing by Subject "Matched Filtering"
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Item Open Access Clutter detection in pulse-doppler radar systems(2010) Güngör, AhmetAmong various types of radar systems, the pulse-Doppler radar is the most widely used one, especially in military applications. Pulse Doppler radars have a primary objective to detect and estimate the range and the radial velocity of the targets. In order to have a basis for the detection, first reflected echo signals are matched filtered and then the time-alligned pulse returns are transformed to the Fourier domain to obtain the range-Doppler matrix. The resulting range-Doppler matrix is input to target detection algorithms. For this purpose, constant false alarm rate (CFAR) algorithms are run on the range-Doppler matrix. It is useful to run different CFAR algorithms inside the clutter region and outside the clutter region because the statistics are different inside and outside of the clutter. In order to achieve this discrimination, the position of the clutter has to be detected in the range-Doppler matrix. Moreover, the clutter may not always appear around zero Doppler frequency when realistic terrain models and moving platforms are considered. Two algorithms for clutter detection using range-Doppler matrix elements are investigated and their performance analysis is presented in this thesis. The first algorithm has higher error rates but lower computational complexity,whereas, the second one has lower error rates but higher computational complexity. Both algorithms detect clutter position by filtering the range-Doppler matrix elements via non-linear filters. In addition to the probabilistic error rate analysis, simulation results on some realistic cases are presented. It is concluded that the first algorithm is a good choice for low clutter-to-noise ratio values when a low-complexity algorithm is required. On the other hand, the second algorithm has better performance in all clutter-to-noise ratio values but it requires more computational power.Item Open Access Doppler frequency estimation in pulse doppler radar systems(2009) Soğancı, HamzaPulse Doppler radar systems are one of the most common types of radar systems, especially in military applications. These radars are mainly designed to estimate two basic parameters of the targets, range and Doppler frequency. A common procedure of estimating those parameters is matched filtering, followed by pulse Doppler processing, and finally one of the several constant false alarm rate (CFAR) algorithms. However, because of the structure of the waveform obtained after pulse Doppler processing, CFAR algorithms cannot always find the Doppler frequency of a target accurately. In this thesis, two different algorithms, maximum selection and successive cancelation, are proposed and their performances are compared with the optimal maximum likelihood (ML) solution. These proposed algorithms both utilize the advantage of knowing the waveform structure of a point target obtained after pulse Doppler processing in the Doppler frequency domain. Maximum selection basically chooses the Doppler frequency cells with the largest amplitudes to be the ones where there is a target. On the other hand, successive cancelation is an iterative algorithm. In each iteration, it finds a target that minimizes a specific cost function, until there are no more targets. The performances of these algorithms are investigated for several different point target scenarios. Moreover, the performances of the algorithms are tested on some realistic target models. Based on all those observations, it is concluded that maximum selection is a good choice for high SNR values when a low-complexity algorithm is needed, on the other hand, successive cancelation performs almost as well as the optimal solution at all SNR values.