Blind parameter estimation of pseudo-random binary code-linear frequency modulation signal based on Duffing oscillator at low SNR  

作　　者：Ke Wang Xiaopeng Yan† Ze Li Xinhong Hao Honghai Yu 王珂;闫晓鹏;李泽;郝新红;于洪海(Science and Technology on Electromechanical Dynamic Control Laboratory,School of Mechatronical Engineering,Beijing Institute of Technology,Beijing 100081,China)

机构地区：[1]Science and Technology on Electromechanical Dynamic Control Laboratory,School of Mechatronical Engineering,Beijing Institute of Technology,Beijing 100081,China

出　　处：《Chinese Physics B》2021年第5期312-319,共8页中国物理B（英文版）

基　　金：the National Natural Science Foundation of China(Grant Nos.61973037 and 61673066).

摘　　要：Conventional parameter estimation methods for pseudo-random binary code-linear frequency modulation(PRBC-LFM)signals require prior knowledge,are computationally complex,and exhibit poor performance at low signal-to-noise ratios(SNRs).To overcome these problems,a blind parameter estimation method based on a Duffing oscillator array is proposed.A new relationship formula among the state of the Duffing oscillator,the pseudo-random sequence of the PRBC-LFM signal,and the frequency difference between the PRBC-LFM signal and the periodic driving force signal of the Duffing oscillator is derived,providing the theoretical basis for blind parameter estimation.Methods based on amplitude method,short-time Fourier transform method,and power spectrum entropy method are used to binarize the output of the Duffing oscillator array,and their performance is compared.The pseudo-random sequence is estimated using Duffing oscillator array synchronization,and the carrier frequency parameters are obtained by the relational expressions and characteristics of the difference frequency.Simulation results show that this blind estimation method overcomes limitations in prior knowledge and maintains good parameter estimation performance up to an SNR of-35 dB.

关 键 词：Duffing oscillator pseudo-random binary code-linear frequency modulation(PRBC-LFM)signal blind parameter estimation low signal-to-noise ratio(SNR) 

分 类 号：TN911.23[电子电信—通信与信息系统]