This Engineering Doctorate concerns the enhancement and detection of slow-moving targets in SAR images. Moving targets are incorrectly located or not captured at all in SAR images. Slow-moving targets within the clutter-Doppler-band appear at incorrect locations within the SAR image. Detecting these slow targets would have broad applications in defence surveillance, traffic monitoring and perimeter protection. As an industrially motivated project, partnered with Selex ES, this work goes beyond the explanation and confirmation of theories and looks at the practicality of implementing techniques. The goal of the research is to develop algorithms with general applicability that can also be specifically exploited on current Selex ES SAR systems. Additionally, the benefit of larger numbers of channels should be evaluated to help guide future product development. After finding the capabilities of single channel SAR to be limited to the detection of very bright targets, the main focus of the research is the use of multiple spatial channels to improve moving target capabilities. A multichannel SAR simulator has been developed that, along with multiple flight trials with the PicoSAR radar system, provides data sets that are used to develop and test the algorithms presented in this work. A theoretical background is given that includes analysis of deramp-on-receive processing, multichannel SAR image formation and the Selex ES PicoSAR system. Also included is a novel derivation of the effects of moving targets in spotlight SAR imagery that confirms previous results without the previous approximations. The derivation uses an entirely new approach that considers the closing velocity of moving targets rather than explicit analysis of the signal phases. The main thrust of the research looks at image-domain exploitation of dual channel SAR to suppress stationary clutter and enhance the returns from moving targets. Adaptive channel alignment is used to calibrate and align multiple channels such that the magnitude and phase differences between the channels can be used to cancel stationary clutter contributions. After this clutter suppression, the velocity of bright targets can be then estimated so that they can be correctly focused and positioned within the SAR image. In the more common case where moving targets remain dim after clutter suppression, a third channel is needed to estimate target velocity. Simulated data is used to demonstrate clutter suppression interferometry as a technique to achieve this. The use of real data throughout all of these considerations leads to the conclusion that current dual-channel radar systems such as PicoSAR can be used to detect dim, slow-moving targets. To correct the motion-induced degradation of these targets, it will be necessary to have a third spatial channel but significant gains can be made with only two.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:650391 |
| Date | January 2015 |
| Creators | Kennedy, Stuart Alan |
| Publisher | University of Glasgow |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://theses.gla.ac.uk/6460/ |
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