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- Type of Document: Ph.D. Dissertation
- Language: Farsi
- Document No: 49475 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Nayebi, Mohammad Mehdi
- Abstract:
- The use of multiple-input multiple-output (MIMO) radar to overcome traditional radar weaknesses has received much attention in recent studies.For example, the detection of targets with low radar cross section (RCS) level is still very difficult since the target can be seen only from one side. MIMO radars by diversity of locations or waveforms solve this problem. One of the fundamental problems in the design of MIMO radars is optimal detectors.This problem has been investigated in recent years under various assumptions. We studied this subject under some assumptions such as single point target, Swerling scattering models for radar cross section and Gaussian interference.In this paper we introduce a new model for the design of a statistical MIMO radar detector that has the ability to combine information of sequential scanning, working in a very low signal-to-noise and determining the velocity vector without direct measurement of the target Doppler. In our proposed system, the target is assumed to move in a piecewise linear trajectory and multi-scan data is stored. The time dependence is considers in data, leads to 3D data space from consecutive scans. A GLRT detector is derived that employs consecutive observations in a central unit. Then a sub optimum detector is introduced in which each pair of transmitters-receivers works separately and the central unit decides with a binary algorithm. The exact theoretical performances of both detectors are extracted and their qualities are compared. Numerical simulations verify all results
- Keywords:
- Detection ; Swerling Model ; Multi-Input Multi-Output (MIMO)Radar ; Target Detection ; Binary Algorithm
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