Performance Of Compressive Sensing Radar Mimo Using Non Uniform Sampling And Orthogonal Matching Poursuit



Some of waves are poorly captured by Radar system because of the ionospheric cutoff due to a low frequency. So it becomes difficult to acquire the return signals. A recent paradigm for signal acquisition and reconstruction, known as compressive Sensing (Compressive Sensing, CS), provides a promising data acquisition technique for applications this require a limited number of measurements and leads to the development of a new type of converter : the Analog to Information Converter (AIC). Unlike standard Analog to Digital converters (ADC), AIC can sample at a lower rate than that prescribed by Nyquist Shannon, exploiting the sparsity of signals. The main goal of this article is to study the application of compressed sampling for the acquisition of Radar signals. Based on the characteristic properties of our signals of interest, we progressively and methodologically constructed our acquisition scheme : From the study of signals compressibility, to the choice of the AIC architecture and the signal reconstruction algorithm etc.


Compressive Sensing, CS, Radar signals, AIC, Nyquist Shannon

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