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- W61961851 abstract "Compressive sensing (CS) provides a new paradigm in data acquisition and signal processing in radar, based on the assumptions of sparsity of an unknown radar scene, and the incoherence of the transmitted signal. The resolution in the conventional pulse-compression radar is foreseen to be improved by the implementation of CS. An unknown sparse radar scene can then be recovered through CS with a high probability, even in the case of an underdetermined linear system. However, the theoretical framework of CS radar has to be verified in an actual radar system, accounting for practical system aspects, such as the signal bandwidth, ease of generation and acquisition, system complexity, etc. In this thesis, we investigate linear frequency modulated (LFM), Alltop and Bjorck waveforms, which show theoretically favorable properties in a CS-radar system, in the basic radar problem of range-only estimation. The aforementioned waveforms were investigated through a model of a digital radar system - from signal generation in the transmitter, to sparse signal recovery in the receiver. The capabilities of the CS-radar versus the conventional pulse compression radar were demonstrated, and the Alltop and Bjorck sequences are proven to outperform the commonly used linear LFM waveform in typical CS-radar scenarios." @default.
- W61961851 created "2016-06-24" @default.
- W61961851 creator A5077363196 @default.
- W61961851 date "2013-07-31" @default.
- W61961851 modified "2023-09-26" @default.
- W61961851 title "Waveform Optimization for Compressive-Sensing Radar Systems" @default.
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