Detection Method and FPGA Implementation of Ultra-Low SNR LFM Signal by Duffing Oscillator Based on Frequency Period Alignment

Aiming at the problems of high complexity and poor accuracy of the existing estimation methods for linear frequency modulation (LFM) signal parameters under the condition of ultralow signal-to-noise ratio (SNR), this paper proposes a method of LFM signal parameter estimation using frequency periodicity based on Duffing oscillator detection system. By using the fourth-order Runge Kutta algorithm to analyze the chaos algorithm and the modified period-graph averaging method to calculate the power spectrum density, the FPGA implementation of the detection system is completed. This method utilizes the periodic alignment points between the reference frequency of the Duffing oscillator and the frequency of the LFM signal, and determines the time instances of frequency alignment through power spectral density analysis, and the carrier frequency, modulation frequency and frequency modulation slope of LFM signal are determined. Experimental results show that the proposed method can detect LFM signals with an average error of less than 1% at a sampling rate of 2.5 GHz and a SNR of -20 dB, and the effectiveness of the proposed method is verified.