Study On Signal Analysis Of LFM And Complexity Evaluation In Complex Electromagnetic Environment

This is a modern generation with rapid development of wireless communication technology.There are various of communication signal styles and intensive spectrum overlapping components which forms a sophisticated electromagnetic environment with natural electromagnetic radiators.Consequently,because it contains sufficient information in those changeable signals,the key for capturing the controlling of massages or for winning a war is to appropriately illustrate or to process the signals.In this paper,the linear frequency modulation signal in complex electromagnetic environment is analyzed and processed,and the complexity evaluation of electromagnetic environment is studied.Linear FM signal is a classic non-stationary signal,widely used in radar,communications,sonar,earthquake and other fields.Domestic and foreign researchers have proposed methods for LFM signal processing and parameter estimation.Common methods include short-time Fourier transform,wavelet transform,Wigner-Ville transform,generalized S-transform and fractional Fourier transformation and other time-frequency analysis methods.These methods significantly affect signal analysis for single component and conventional multi-components.However,it is not going to work neither for low signal-to-noise ratio which exists in a complex electromagnetic environment,nor for multi-component LFM signals with similar parameters.Thus,the sutudy in the paper focus on the LFM analysis and complex electromagnetic complexity evaluation methods for complex electromagnetic environment.The main research and achievements are as follows:First,The short-time Fourier transform,wavelet transform,Wigner-Ville distribution and fractional Fourier transform are used to filter different signal-to-noise single-component chirp signals.The filtering effect and energy aggregation show different characteristics.According to the application of LFM signal,it is compressed to improve the propagation distance,and the two main parameters of LFM signal are briefly introduced.Then,The method of generalized S transform combined with singular value decomposition is proposed to filter multi-component chirp signals.The generalized S transform makes the signal peak in the time-frequency domain by coordinate rotation,while the noise signal is evenly distributed in the time-frequency domain.Accordingto this feature,a part of the noise signal can be filtered out.In the complex electromagnetic environment,the low signal-to-noise ratio multi-component LFM signal is further filtered by using the singular value decomposition method,and the singular value decomposition of the discretized generalized S-transform matrix is performed.The singular value of the characteristic noise is preserved and the characteristic signal to reserves,the process is used to filter the signal again.The simulation results show that this method can efficiently filter the noise in the multi-component chirp signal,and the accuracy of the subsequent parameter extraction is well improved.For the multi-component LFM signals with similar parameters or the same parameters,the normalized Fractional Fourier domain is proposed.Different normalization factors and peak spacing of multi-component signals are different.Choosing suitable normalization factor to achieve the best distance between the states.In order to find the most suitable normalization factor,this paper proposes a firefly algorithm to optimize the normalization factor.The simulation results show that the normalization factor of the optimized selection makes the spacing of the multi-component signals significantly is increase,and the accuracy of the extracted parameters is improved.The estimation of the direction of the arrival of the multi-component signal received by the linear array antenna is further verified.At last,After processing the multi-component signals in the complex electromagnetic environment,the complexity of the electromagnetic environment is qualitatively and quantitatively evaluated by using the extracted signal parameters.On the basis of four-domain method,this paper improves the evaluation method of electromagnetic environment complexity,and proposes the joint extraction of three parameters of time,frequency and energy occupancy for the first time with,avoiding the error caused by the separate extraction of parameters;increase frequency coincidence degree,signal modulation format,channel occupancy and background noise intensity as evaluation index,and use the limit learning machine with less time and less precision as the evaluation network to conduct qualitative and quantitative assessment of the electromagnetic environment complexity.The simulation experiment is carried out on the electromagnetic environment complexity evaluation demonstration platform set up by the research group,which verifies the method with describing the complexity of the electromagnetic environment more comprehensively and improve the accuracy of the electromagnetic environment complexity assessment.