Compressed spectrum Sensing in Cognitive Radar systems

Compressed Sensing is a new signal processing methodology that allows to reconstruct sparse signals using a relatively small number of samples in the form of random projections. These samples are collected at a much lower rate than Nyquist rate. This paper focuses on the application of Compressed Sensing in Cognitive Radar systems that use wide operating frequency bandwidths for spectrum sensing and sharing. Compressed sensing can provide a significant reduction in acquisition time reducing the cost for high resolution analog-to-digital converters with large dynamic range, and high speed signal processors.