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- Type of Document: Ph.D. Dissertation
- Language: Farsi
- Document No: 51391 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Behnia, Fereidoon
- Abstract:
- Target localization in multiple-input multiple-output (MIMO) radar systems has been an active research topic during the recent years. Generally speaking, MIMO radars can be classified, based on the antennas geometry, into colocated and distributed architectures.The former provides waveform diversity and the latter makes use of spatial diversity provided by widely separated configuration of antennas, both of which improve localization and detection performance. In this study, we focus on the latter case. In this thesis, we investigate the localization problem in two parts, i.e., positioning based on bistatic time delay measurements and hybrid localization using combination of time delay, Doppler shift, and angle of arrival (AOA) measurements. In the first part, we propose three different localization methods, which can locate the target in an efficient manner. The first one is based on introducing nuisance parameters and employing the two-stage weighted least squares estimation. In the second method, the localization problem is formulated as a linear estimation problem by eliminating the nuisance parameters. In the third method, the exact solution of the associated constrained weighted least squares problem is obtained in a computationally efficient manner. The above methods are shown to be able to attain the Cramer-Rao lower bound (CRLB) performance and outperform the state-of-the-art methods. In the second part of this thesis, we propose a closed-form hybrid localization method from time delay and AOA measurements based on weighted least squares estimation. Furthermore, two different methods for moving target localization are proposed which employ both time delays and Doppler shifts as their measurement sets.Finally, the problem of moving target localization in the presence of antenna location uncertainties is investigated and an efficient closed-form estimator is proposed. The aforementioned methods are shown analytically and verified by numerical simulations to be efficient estimators, the accuracy of which achieve the CRLB. Numerical simulations are included to support the theoretical developments and demonstrate superiority of the proposed methods compared with the existing ones
- Keywords:
- Maximum Likelihood Estimation ; Cramer-Rao Bound ; Least Squares Estimation ; Multi-Input Multi-Output (MIMO)Radar ; Target Localization
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