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Merging frequency agile OFDM waveforms and Compressive Sensing into a novel radar concept
Compressive sensing (CS) is a new tool that intends to estimate the original information by means of convex optimization, using just a few measurements. In radar this original information consists of the range - Doppler map of the observed scene. The method allows undersampling since the band-limite...
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Main Authors: | , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | Compressive sensing (CS) is a new tool that intends to estimate the original information by means of convex optimization, using just a few measurements. In radar this original information consists of the range - Doppler map of the observed scene. The method allows undersampling since the band-limitedness of the waveform is no longer the limiting criterion, which turns to be the sparsity of the scene. Essentially, this article opens new prospects for radar waveforms by focusing on the orthogonal frequency division multiplexing (OFDM) signal in comparison with chirps, and shows how the concept of agility fits in a natural way with CS as a processing tool. Examples with conventional matched filtering support fair comparisons. The scenario of a 1D range profile sparsely filled with bright spots or point targets is investigated. |
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