Time-Frequency-Space Multidimensional Parameter Estimation Of Frequency Hopping Signal Based On Time-Frequency Analysis

Parameter estimation of frequency hopping signal is a key link in reconnaissance work.The carrier frequency of the frequency hopping signal can jump randomly according to certain rules,and the communication frequency band is usually mixed with various strong interference signals and noise.Therefore,how to accurately extract the frequency hopping signal from the received signal and accurately estimate the parameters has become a research difficulty.With the continuous upgrading of the electronic countermeasure environment,the carrier frequency band used in frequency hopping communication is increasing and the frequency hopping range is expanding.It is very expensive and complicated to realize the time domain Nyquist sampling of high-frequency signals with the existing ADC sampling technology.At the same time,for the reception of spatial data,high-frequency signals will also limit the minimum spacing of the receiving array.Therefore,it is of great research value to study the parameter estimation algorithm of high-frequency frequency hopping signals under the condition of time-space domain undersampling.Based on this background,based on the powerful means of analyzing non-stationary signals-time-frequency analysis,this thesis focuses on the estimation algorithm of time,frequency and space parameters of frequency hopping signals.The specific work is as follows :(1)Applying the traditional time-frequency analysis method and time-frequency post-processing method to the analysis of frequency hopping signals,and comparing the time-frequency aggregation and computational power of different time-frequency analysis methods qualitatively and quantitatively through simulation,the time-frequency analysis strategy applicable to frequency hopping signals is given: for the time-frequency characteristics of frequency hopping signals,the time-frequency post-processing method can be used for local analysis on the basis of the results obtained by the traditional time-frequency analysis method,which can improve the time-frequency aggregation while significantly reducing the computational cost.(2)The existing parameter estimation algorithm of frequency hopping signal combines time-frequency analysis method with image processing technology,which can realize the parameter estimation of frequency hopping signal in complex electromagnetic environment.However,because most of them adopt traditional time-frequency analysis method,the limitation of time-frequency focusing and the problem of data area expansion caused by image processing lead to low estimation accuracy of the algorithm.Therefore,this thesis uses the time-frequency post-processing method based on the idea of regional energy center to optimize the traditional frequency hopping signal parameter algorithm,so as to realize the high-precision estimation of time-frequency-space multi-dimensional parameters of frequency hopping signal.Based on this algorithm,a time-frequency-space multi-dimensional parameter estimation framework for frequency hopping signals based on time-frequency analysis under Nyquist sampling is built by using uniform linear array.The simulation results show the high accuracy of the proposed multi-dimensional parameter estimation framework for frequency hopping signals under Nyquist sampling.(3)The time-space undersampling parameter estimation algorithm based on the closed robust Chinese remainder theorem has limitations on the received signal and cannot realize the parameter estimation of frequency hopping signal in complex electromagnetic environment.Therefore,this thesis proposes for the first time to combine time-frequency analysis with the closed robust Chinese remainder theorem to extract the remainder from the received data in complex electromagnetic environment to realize signal parameter reconstruction.At the same time,the spectrum of time-frequency analysis also has the problem of fence effect and spectrum leakage,and the data reconstruction algorithm based on the closed robust Chinese remainder theorem has a limit range for the remainder error.Therefore,this thesis introduces the spectrum correction algorithm to improve the success rate of the parameter reconstruction algorithm.Based on the above algorithms,this thesis uses non-uniform arrays to build a time-frequency-space multi-dimensional parameter estimation framework for frequency hopping signals based on time-frequency analysis under spatio-temporal undersampling.The simulation implementation proves the effectiveness of the proposed framework.