Recovery of radar's beat signal based on compressive sampling

Abstract

Weather radar is a type of radar that used to detect rainfall, the direction of movement and speed, to know the level of rain and cloud composition. One of the problems that occurs in weather radar is the amount of raw data to be acquired in the digital signal processing process is too large, the size until Gigabyte. In order that, we using Compressive Sampling(CS) to reduce the radar's beat signal, as part of weather radar data. CS requires that the signal must be sparse on a certain basis. When using CS the radar's beat signal are compressed by projecting it onto a randomly generated orthogonal matrix and then recovered by ℓ1 norm optimization and Orhogonal Matching Pursuit (OMP) method. From the simulation, all the method of reconstruction can recover the beat signal radar. We also evaluate the relation of compression ratio and reconstruction accuracy. By PSNR measurement, we propose OMP algorithm for the better radar's beat signal reconstruction.