The emergence of co-located Multiple Input - Multiple Output (MIMO) radar in recent years has meant that snapshot imaging of a target scene can be achieved without the large number of antennas and circuits of a conventional phased array radar, for a given angular resolution. This thesis presents two applications of MIMO radar systems. Firstly, the cross sectional imaging of ice shelves in Antarctica. Two trials were conducted using a single channel SFCW radar to collect data, one from a 2D MIMO array and another from a linear MIMO antenna layout. The results from the signal processing of the data are then provided to highlight the effectiveness of the MIMO antenna layout for ice shelf imaging. The second application is the identification of obstructions at railway level crossings, which require real-time detection of large targets within the boundaries of a level crossing. For real-time imaging, however, the use of multiple transmitters and receivers has now placed constraints on other parts of the radar system for fast data capture and signal processing. To alleviate this problem, the application of sparse sampling in angular space for MIMO radars is investigated to reduce hardware costs and the amount of data required for a snapshot image. Results from a practical demonstration of the sparse array using an FMCW radar as well as from further simulations using a combination of random number PDFs are presented. For ice shelf imaging, a stationary MIMO radar is capable of producing the depth profile without the need for a moving SAR system. A sparsely sampled MIMO antenna array can aid real-time detection of obstructions in level crossings with minimum hardware costs. The results presented in this thesis provide opportunities for further developments in MIMO radars for both geophysical and terrestrial applications.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:626825 |
| Date | January 2014 |
| Creators | Hari Narayanan, A. |
| Publisher | University College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://discovery.ucl.ac.uk/1420954/ |
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