Embargo End Date2019-11-15
Permanent link to this recordhttp://hdl.handle.net/10754/629873
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Access RestrictionsAt the time of archiving, the student author of this dissertation opted to temporarily restrict access to it. The full text of this dissertation became available to the public after the expiration of the embargo on 2019-11-15.
AbstractThe topic of multiple input multiple output (MIMO) radar recently gained considerable interest because it can transmit partially correlated or fully independent waveforms. The inherited waveform diversity helps MIMO radars identify more targets and adds flexibility to the beampattern design. The realized advantages come at the expense of enhanced processing requirements and increased system complexity. In this regards, a closed-form method is derived to generate practical finite-alphabet waveforms with specific correlation properties to match the desired beampattern. Next, the performance of adaptive estimation techniques is examined. Indeed, target localization or reflection coefficient estimation usually involves optimizing a given cost-function over a grid of points. The estimation performance is directly affected by the grid resolution. In this work, the cost function of Capon and amplitude and phase estimation (APES) adaptive beamformers are reformulated. The new cost functions can be evaluated using the two-dimensional fast-Fourier-transform (2D-FFT) which reduces the estimation runtime. Generalized expressions of the Cram´er-Rao lower bound are computed to assess the performance of our estimators. Afterward, a novel estimation algorithm based on the monopulse technique is proposed. In comparison with adaptive methods, monopulse requires less number of received pulses. Hence, it is widely used for fast target localization and tracking purposes. This work suggests an approach that localizes two point targets present in the hemisphere using one set of four antennas. To separate targets sharing the same elevation or azimuth angles, a second set of antennas is required. Two solutions are suggested to combine the outputs from the antenna sets and improve the overall detection performance. The last part of the dissertation focuses on the application and implementation side of radars rather than the theoretical aspects. It describes the realized hardware and software design of a compact portable 24 GHz frequency-modulated-continuous-wave (FMCW) radar. The prototype can assist the visually impaired during their outdoor journeys and prevents collisions with their surrounding environment. Moreover, the device performs diverse tasks such as range-direction mapping, velocity estimation, presence detection, and vital sign monitoring. The experimental result section demonstrates the device’s capabilities in different use-cases.
Showing items related by title, author, creator and subject.
Generalised two target localisation using passive monopulse radarJardak, Seifallah; Ahmed, Sajid; Alouini, Mohamed-Slim (IET Radar, Sonar & Navigation, Institution of Engineering and Technology (IET), 2017-04-07) [Article]The simultaneous lobing technique, also known as monopulse technique, has been widely used for fast target localisation and tracking purposes. Many works focused on accurately localising one or two targets lying within a narrow beam centred around the monopulse antenna boresight. In this study, a new approach is proposed, which uses the outputs of four antennas to rapidly localise two point targets present in the hemisphere. If both targets have the same elevation angle, the proposed scheme cannot detect them. To detect such targets, a second set of antennas is required. In this study, to detect two targets at generalised locations, the antenna array is divided into multiple overlapping sets each of four antennas. Two algorithms are proposed to combine the outputs from multiple sets and improve the detection performance. Simulation results show that the algorithm is able to localise both targets with <;2° mean square error in azimuth and elevation.
Low Complexity Moving Target Parameter Estimation for MIMO Radar using 2D-FFTJardak, Seifallah; Ahmed, Sajid; Alouini, Mohamed-Slim (IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers (IEEE), 2017-06-16) [Article]In multiple-input multiple-output radar, to localize a target and estimate its reflection coefficient, a given cost function is usually optimized over a grid of points. The performance of such algorithms is directly affected by the grid resolution. Increasing the number of grid points enhances the resolution of the estimator but also increases its computational complexity exponentially. In this work, two reduced complexity algorithms are derived based on Capon and amplitude and phase estimation (APES) to estimate the reflection coefficient, angular location and, Doppler shift of multiple moving targets. By exploiting the structure of the terms, the cost-function is brought into a form that allows us to apply the two-dimensional fast-Fourier-transform (2D-FFT) and reduce the computational complexity of estimation. Using low resolution 2D-FFT, the proposed algorithm identifies sub-optimal estimates and feeds them as initial points to the derived Newton gradient algorithm. In contrast to the grid-based search algorithms, the proposed algorithm can optimally estimate on- and off-the-grid targets in very low computational complexity. A new APES cost-function with better estimation performance is also discussed. Generalized expressions of the Cramér-Rao lower bound are derived to asses the performance of the proposed algorithm.
Computation of Electromagnetic Fields Scattered From Objects With Uncertain Shapes Using Multilevel Monte Carlo MethodLitvinenko, Alexander; Yucel, Abdulkadir; Bagci, Hakan; Oppelstrup, Jesper; Tempone, Raul; Michielssen, Eric (2019-02-14) [Poster]Computational tools for characterizing electromagnetic scattering from objects with uncertain shapes are needed in various applications ranging from remote sensing at microwave frequencies to Raman spectroscopy at optical frequencies. Often, such computational tools use the Monte Carlo (MC) method to sample a parametric space describing geometric uncertainties. For each sample, which corresponds to a realization of the geometry, a deterministic electromagnetic solver computes the scattered fields. However, for an accurate statistical characterization the number of MC samples has to be large. In this work, to address this challenge, the continuation multilevel Monte Carlo (CMLMC) method is used together with a surface integral equation solver. The CMLMC method optimally balances statistical errors due to sampling of the parametric space, and numerical errors due to the discretization of the geometry using a hierarchy of discretizations, from coarse to fine. The number of realizations of finer discretizations can be kept low, with most samples computed on coarser discretizations to minimize computational cost. Consequently, the total execution time is significantly reduced, in comparison to the standard MC scheme.