Signal Detection Based on Recursive Autocorrelation and mn Method for Synchronous Nyquist Folding Receiver

Synchronous Nyquist folding receiver (SNYFR) is an improved novel broadband receiver architecture that is possible to implement in the engineering. The output signal of SNYFR is usually a hybrid modulated signal, so corresponding signal detection methods need to be investigated, which is the premise of precise parameter estimation. In this paper, a signal detection method based on recursive autocorrelation and mn method for SNYFR is proposed. First, autocorrelation with a fixed length for SNYFR output signal is acquired. Then, in order to determine the existence of the signal, constant false alarm rate (CFAR) detector is introduced into the method to generate an adaptive threshold. Finally, the position where the signal exists is determined by mn method and the signal data are sent to back-end processor for parameter estimation. The proposed algorithm can not only adapt to low signal-to-noise ratio (SNR), but also has a high measurement accuracy with low computational complexity. The simulation demonstrates the viability and validity of the proposed method.