Radar false alarm processing using proposed algorithm for Xampling and compressive sensing

Abstract

This paper combines application of Compressive Sensing theory in radar signal, and the approach of the Xampling. Based on the characteristic of sparse radar signal, it can be sampled at Finite Rate of Innovation (FRI) [1], Xampling converts high dimensional signal to a lower dimensional signal using Fourier coefficients directly from analog signal [2]. A well-known CAMP algorithm was used to reconstruct the under sampled sparse radar signal and improves its Signal-to-Noise Ratio in case of received radar signal has a high SNR [3]. In present work, a proposed algorithm called Adaptive CAMP algorithm is applied to the radar signal in order to deal with the problem of the false alarms that appear in reconstructed radar signal from the CAMP algorithm in case of received low SNR. The performance of the Adaptive CAMP algorithm as well as the CAMP algorithm is evaluated using the Receiver Characteristic Curve (ROC) to compare the proposed design with the CAMP algorithm in case of low SNR.