Print Email Facebook Twitter Theory and Practice of Waveforms for Compressive-Sensing Radar Title Theory and Practice of Waveforms for Compressive-Sensing Radar Author Gourova, R.N. Contributor Pribic, R. (mentor) Yarovoy, A. (mentor) Faculty Electrical Engineering, Mathematics and Computer Science Department Microwave Sensing, Signals and Systems Programme Electrical Engineering, track Telecommunications and Sensing Systems Date 2015-09-23 Abstract The main problem discussed in this Thesis is waveform design for compressive sensing radar. Radar systems are used for a variety of different applications ranging from medicine to underground detection. The choice of waveforms determines the capabilities of the radar to distinguish between different closely spaced targets and frequencies. If chosen correctly it can improve the detection performance of the system. In the past ten years a new paradigm has emerged, called compressive sensing. It has attracted researchers from numerous fields as it promises to improve data collection as currently known. Radar is one of the fields interested in utilizing compressive sensing for improving, among others, resolution and detection performance. Waveform design plays an important role again due to the particular requirements for applying compressive sensing. In this work three different waveforms -LFM, Alltop and OFDM, are chosen and studied in the context of suitability for compressive sensing radar. Different performance measures, such as processing gain and point spread function gain, are investigated and various scenarios testing numerous capabilities of the waveforms are defined. The experiments are designed to test the waveforms in presence of a single target, to exploit resolution capabilities in presence of extended and point target, and not last to check their Doppler performance. The outcome of this Thesis is studying the waveforms in a realistic setting and presenting the results for both traditional and sparse signal processing. To reference this document use: uuid:82386dcf-cf46-4c0a-b9d8-a3cb2423ba29 Embargo date 2065-09-23 Part of collection Student theses Document type master thesis Rights (c) 2015 Gourova , R.N.