Multi-Component LFM Signal Parameter Estimation for Symbiotic Chirp-UWB Radio Systems

Symbiotic chirp-ultra wide bandwidth (UWB) radio system (SCURS) is a UWB radio system with the symbiosis of linear frequency modulation (LFM) and orthogonal frequency division multiplexing (OFDM) signals. It has a high data rate and can transmit data on two channels simultaneously. Moreover, multi-component LFM (MCLFM) parameter estimation plays an important role in the demodulation of SCURS. Furthermore, the complex electromagnetic environment also brings impulsive noise. In this paper, a novel parameter estimation method for MCLFM signals based on the fractional Fourier transform-bald eagle search algorithm (FRFT-BES) and synchroextracting short-time fractional Fourier transform-Hough (SSFT-Hough) with alpha-stable noise is proposed. First, we use a nonlinear transformation to eliminate the negative effect of alpha-stable noise on parameter estimation. Second, we combine the improved BES with FRFT to propose FRFT-BES and use it to estimate the frequency modulation rate. Finally, we propose a new time-frequency (TF) transform method with high TF resolution as SSFT, and we combine it with Hough transform (HT) to propose SSFT-Hough to estimate the initial frequency. Frequency modulation rate and initial frequency are widely used in MCLFM signals separation. Simulation results demonstrate that the proposed method performs well in low mixed signal-to-noise ratio (MSNR), and it is superior to existing methods.