A Fractional Integrator Based Novel Detector for Weak Signal Detection with Watermark Application
Sumit Kumar, Rajib Kumar Jha · 2018
The detection of a weak signal from noisy data is an important task in many signal processing applications such as radar communication, biomedical engineering etc. However, the amplitude of the known signal plays a big role in terms of complexity and performance of the detector. In other words, detection of the weak signal is a big challenge. Here, we investigate approximated fractional integrator (AFI) based detector. The proposed method has been employed for detection of DC signal which is present in the Gaussian noise. Our proposed method has been compared with some state-of-the-art methods in terms of probability of detection (PD) for a constant value of probability of false alarm (PFA). The PDhas been plotted for varying signal-to-noise ratio (SNR) at a constant value of PFA. Furthermore, we apply the proposed method for watermark application. The outcomes of the proposed method are convincing and it suggests that the proposed method works better or comparable to some state-of-the-art methods.