Performance enhancement of wide-band radar signals, using a new adaptive CAMP algorithm in compressive sensing

High resolution radar signals demands the use of high speed signal processor. Due to the sparse nature of radar signals, Compressive sensing (CS) enables the wide-band radar signals to be sampled at a low sampling rate, rather than a high sampling rate. This is attained through the use of a sparse sensing matrix. Complex approximate message passing (CAMP) algorithm is vastly used in reconstructing radar signals, because of its low complexity for real-time recovery and suitable for hardware integration. However, the CAMP algorithm achieves low detection performance at low Signal to Noise Ratios (SNRs). This paper proposes a new adaptive CAMP algorithm based on signal threshold, in order to solve the aforementioned shortcoming. Through simulation, the new adaptive CAMP is compared against the classical CAMP and the digital matched filter (DMF) algorithm using the Receiver Operating Characteristic (ROC) curves. The receivers operating characteristic curves (ROC) show that the new adaptive CAMP improves the probability of detection at lower SNRs.