Weak Signal Detection Using Stochastic Resonance with Approximated Fractional Integrator

In this paper, a new technique for weak signal detection using stochastic resonance (SR) with approximated fractional integrator (AFI) has been investigated. To improve the performance of weak signal detector, AFI is convolved with noisy samples which (i.e., AFI) attenuates the noise because of its low-pass filtering nature. SR noise ( i.e., some fixed amount of noise) is added externally, which causes further improvement in detection. The external noise under SR has been obtained in Neyman–Pearson (NP) framework. For comparison, receiver operating characteristic curve has been analysed. The parameters, probability of detection ( $$P_D$$ ) and deflection coefficient ratio are also calculated at a fixed value of probability of false alarm ( $$P_{\mathrm{FA}}$$ ). It has been observed that the performance of the proposed detector is better or comparable to most of the state-of-the-art techniques.