Parameter estimation of LFM signal intercepted by Nyquist folding receiver based on particle swarm optimization and fractional Fourier transform

In many radar and communications applications, signal information needs to be detected and estimated over ultra-wide radio frequency bandwidths. The Nyquist folding receiver (NYFR) theoretically enables reconnaissance using a single analog-to-digital converter (ADC). The NYFR generates a Nyquist Zone (NZ) related local oscillator and transforms the acquired linear frequency modulation (LFM) signal into a signal that combines LFM and LOS modulation. A method is proposed to estimate frequency modulation slope the parameters of LFM signal captured by NYFR. Firstly, according to the time-frequency diagram of captured signal, the precise NZ and coarse frequency modulation slope are calculated based on the particle swarm optimization algorithm. The fitting effects of different fitness functions are tested, and the optimal fitness functions and the parameters of particle swarm optimization are given. Then, LOS information is removed from the mixed modulation signal, and the precise frequency modulation slope is gained through fractional Fourier transform (FrFT). Simulation results demonstrate that the approach presented in this paper is capable of precisely estimating the parameters of signals acquired by NYFR.