General Framework of Compressive Sampling and Its Application to Radar Signals

Abstract

Today we are moving towards the era of digital devices i.e. we want to replace every analog device with a suitable digital device. Digital devices operate on the digital signals but most of the times origination of the signal is in analog form. So we need to convert analog signal to digital signal before processing by using Analog to Digital Converter (ADC) devices. But analog to digital conversion is bounded by Nyquist criteria i.e. number of samples to represent an analog signal should be at least twice of the maximum frequency of the signal. This bottleneck criterion prevents us to use digital signal processing for the devices which operate on high frequencies like Radar (Radio Detection and Ranging). Compressive sampling allows us to recover the original analog signal with very less number of samples as compared to the number of samples given by Nyquist rate. But compressive sampling can be implemented on the sparse signals. Radar signals can be made sparse in dictionary domain due to prior knowledge of the transmitted waveform at the receiver. So we used compressive sampling technique for radar signals.