Frequency Hopping Signal Extraction And Parameter Estimation In Complex Environment

Compared with conventional communication methods,frequency-hopping communication has excellent anti-interference and anti-interception performance,so it is widely used in military and civil communication fields.With the development of military countermeasures and cognitive radio technology,the research on non-cooperative reception,extraction and analysis of frequency hopping communication signals has become one of the current research focuses,so the design of frequency hopping reconnaissance analysis algorithms with better performance has important research significance.Not only that,With the rapid development of communication technology,both civil and military communication environments have become more and more complex.The received signals usually include unrelated signals such as interference and noise.Therefore,how to extract a pure frequency hopping signal is important for The analysis of frequency hopping signals is of great significance Therefore,based on single-antenna reception,this paper studies the denoising,extraction and parameter estimation methods of single or multiple frequency hopping signals in an interference environment.The specific work is as follows.First of all,this thesis analyzes and studies the performance of existing time-frequency analysis methods,and compares and analyzes the characteristics of different methods by introducing quantitative measurement indicators based on information entropy,and provides design basis for subsequent frequency hopping signal extraction and parameter estimation.Secondly,apply the selected time-frequency analysis method to study the preprocessing technology of frequency hopping signals in complex environments,including removing noise and interference in the time-frequency diagram,so as to realize the extraction of frequency hopping signals.Based on the analysis of the existing energy threshold denoising and histogram denoising methods,an improved low-complexity denoising method is designed.This method has low implementation complexity and little performance loss.For the time-frequency diagram after denoising,based on the analysis of the existing time-frequency cancellation interference and morphological interference removal,a de-interference algorithm based on connected domain labeling is designed,and the extraction performance of frequency hopping signals is better.,And will not cause loss to the energy of the frequency hopping signal.Finally,the parameter estimation of frequency hopping signal is studied.Aiming at the problem that a single signal time-frequency ridge will have many abnormal points when the signal-to-noise ratio is low,a time-frequency ridge smoothing method using morphological filtering is researched and designed,thereby improving the parameters based on the time-frequency ridge Estimated performance.Then it analyzes the two-dimensional quadratic difference estimation frequency hopping parameter algorithm.Aiming at its shortcomings such as too large number of samples and not strong practical application,a frequency hopping signal parameter estimation method based on the center of gravity of the connected domain is proposed.The performance of low signal-to-noise ratio is greatly improved.For the parameter estimation of multi-user frequency hopping signals,an algorithm based on the area of the connected domain is used for sorting,and then the parameter estimation of the frequency hopping signal based on the center of gravity of the connected domain is performed,and the effectiveness of the method is verified by simulation.