The process conventionally used to estimate the parameters of targets de tected by radar is matchedfiltering. It is optimal for the detection of a single point target. Compressed Sensing suggests a new treatmentfor the radar, also performing in the multi targets case. In addition, we seek to apply this treatment to step-frequency waveforms. We get betterperformances, particularly in terms of tracking and recognition. We formulate the problem of Compressed Sensing to the radar, and generate waveforms designed to improve the treatment of radar signal via Compressed Sensing approach. Our main interest is a very particular structure composed by periodic patterns ofpulses affected to different carrier frequencies, chosen ultimately at random as suggested by the classical Compressed Sensing analysis. That specific shape ables to get efficient reconstruction algorithms with fine resolution and low number of measurements, making this approach more interesting than a standard step frequency waveform without periodic structure....
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