Research On Signals Detection And Modulation Recognition Technologies Of Non-cooperative Communication

Signals detection and modulation recognition are the key technologies of receivers in non-cooperative communication system, which have the important application value in adaptive modulation, military reconnaissance and electronic countermeasure fields. According to the problems that current signals detection and modulation recognition technologies have poor performance and could not meet the requirement of practical application in non-cooperative communication. This dissertation is mainly concerned with the the key technologies of signals detection and modulation recognition in non-cooperative communication, which including parameters estimation and recognition of digital modulation signals over multipath channels, recognition digital modulation signals with non-Gaussian noise and parameters estimation and recognition for time-frequency overlapped signals over single channel. The author’s major contributions are outlined as follows:1. According to the problems that traditional bandwidth estimation schemes for OFDM signals have low estimation accuracy and high complexity in low SNR over multiple channels, a novel bandwidth estimation scheme for OFDM signals base on Empirical Mode Decomposition is proposed. This scheme effectively overcomes the effects of noise. Simulation results show that this scheme has higher estimation accuracy and lower computational complexity. According to the problems that traditional SNR blind estimation schemes for OFDM signals have poor performance and high1complexity over multiple channels, a novel SNR blind estimation scheme for OFDM signals based on AR model and high-order cumulant is proposed and this scheme dose not need any priori information and has better estimation performance and lower complexity over multiple channels. According to the problems that time domain parameter estimation schemes for ZP-OFDM signals have low estimation accuracy in low SNR over multiple channels, a novel time domain parameter estimation scheme for ZP-OFDM signals is proposed. This scheme effectively estimates the total length of the symbols by power autocorrelation function, Wavelet de-noising and smoothing filtering. This scheme also estimates the length of the zero prefix by using magnitude-squared value of the data of the total length of the symbols and Wavelet decomposition and reconstruction. Simulation results show that this scheme has better performance in low SNR over multiple channels.2. According to the problems that the recognition schemes of digital modulation signals with frequency offset and phase offset have poor performance in low SNR over multipath channels, a novel recognition scheme of digital modulation signals base on cyclostationarity property is proposed. It is proved that this scheme could eliminate the effect of frequency offset, phase offset, noise and multipath fading channels. Simulation results show that this scheme has effective feasibility and robustness. According to the problems that the modulation subcarriers of OFDM signals with pilot are recognized difficultly over multiple channels, a novel subcarriers recognition scheme for OFDM signals base on high-order cumulant and improved subtractive clustering is proposed. This scheme could eliminate the effect of attenuation and phase rotation. Simulation results show that this scheme could effectively achieve the recognition of modulation subcarriers for OFDM signals with pilot.3. According to the problems that traditional recognition schemes of digital modulation signals with non-Gaussian noise have poor recognition performance, this paper is proposed a novel recognition scheme based on generalized Fractional Fourier Transform and fractional lower Wigner-Ville distribution. This scheme extracts the recognition characteristic parameters which are the maximum of the spectrum density of zero center normalized instantaneous amplitude of Fractional Fourier Transform and the maximum of fractional lower Wigner-Ville distribution amplitudes to identify the digital modulation signals with a non-Gaussian noise. Simulation results show that this scheme has better recognition performance and better robustness than the traditional schemes. According to the problems that traditional recognition schemes of digital modulation signals have poor recognition performance and high complexity in an Alpha stable distribution noise environment, a novel recognition scheme of digital modulation signals based on generalized Fractional Fourier Transform and fractional lower covariance spectrum is proposed. This scheme extracts the characteristic parameters which are the maximum of the spectrum density of normalized instantaneous frequency of Fractional Fourier Transform and the maximum of fractional lower covariance spectrum amplitudes to identify the digital modulation signals an Alpha stable distribution noise environment. Simulation results show that this scheme has higher recognition rates, better robustness and lower complexity than the traditional schemes.4. According to the problems that traditional number estimation schemes for time-frequency overlapped signals over single channel have poor performance, a novel number estimation scheme for overlapped signals based on fourth-order cyclic cumulant is proposed. This scheme has good anti-noise performance and is robust for signals spectrum overlap rates. According to the problems that traditional frequency estimation schemes for time-frequency overlapped signals over single channel have poor performance and high complexity, a novel frequency estimation scheme for overlapped signals based on fourth-order cyclic cumulant is proposed. Simulation results show that this scheme has better estimation performance and lower complexity than the traditional schemes. According to the problems that traditional symbol rate estimation schemes for time-frequency overlapped signals over single channel have poor performance and high complexity, a novel symbol rate estimation scheme for overlapped signals based on cyclic spectrum is proposed. This scheme analyzes the feasibility of discrete spectral lines detection in the cyclic spectrum cross-section and verifies its effectiveness in simulation. Simulation results show that this scheme not only has strong anti-noise ability and lower complexity.5. According to the problems that the traditional recognition schemes for time-frequency overlapped signals over single channel have poor performance and only can recognize single type modulation signal, a novel recognition scheme for time-frequency overlapped signals over single channel based on high-order cyclic cumulant is proposed. This scheme has strong anti-noise ability. Simulation results show that this scheme not only has better recognition performance and lower complexity, but also is robust for signals spectrum overlapped rates.