Research On Anti-interference In Frequency Hopping Communication Systems Based On Blind Source Separation

With the development of science and technology, electronic warfare gradually becomes an important modern warfare operation. The electromagnetic environment of the future electronic battlefield will be more and more complicated with the continuous development of all kinds of electronic warfare technology in the world. The traditional frequency hopping communication technology is at the expense of limited spectrum resources to improve its anti-interference ability, and this kind of sacrifice is limited, so we need new technology to improve the anti-interference ability of frequency hopping communication. With the advantage of blind source separation technology, this dissertation studies the anti-jamming technology of the frequency hopping communication combining with the blind source separation technology to improve the anti-interference ability of the system. The main subject of this dissertation includes the following.We study the blind source separation technology of frequency hopping signals based on the spatial time-frequency distribution matrix. The frequency-hopping signal is a typical non-stationary signal, and different frequency hopping signals have different frequency hopping pattern. Making full use of these characteristics of the frequency hopping signals, this dissertation puts forward for using the smooth pseudo Wigner Ville distribution(SPWVD) of observation signals to construct a four-dimensional matrix, and detect monophyletic time-frequency points, and use the joint approximate diagonalization of eigen-matrices(JADE) to estimate the unitary matrix, and then to isolate the source signals. The dissertation improves the time-frequency points selection method based on the existing selection methods. The new blind source separation method based on spatial time-frequency distribution matrix improves the separation performance, but the complexity of the algorithm is increased.We study the Fast Independent Component Analysis(FastICA) algorithm based on negative entropy maximization. With the receiving signals from a variety of electronic equipment, the frequency hopping signals contained in the observation signal are statistically independent. This dissertation make full use of the independency of frequency hopping signal, at most only a Gaussian signal in source signals and the largest negative entropy of Gaussian signal, and proposes the FastICA algorithm based on the negative entropy maximization to separate the observation signal containing frequency hopping signals. The dissertation improves the iterative algorithm on the basis of the original FastICA algorithm. The new FastICA algorithm improves the precision of separation, and its complexity is far less than the complexity of the blind source separation algorithm based on the spatial time-frequency distribution matrix. According to analysis and simulation, we find that the separation precision of the improved FastICA algorithm is not sensitive to the change of the interference-to-signal ratio(ISR), but becomes better with the increasing signal-to-noise ratio(SNR). In order to analyze the impact of blind source separation technique on the bit error rate(BER) performance, this dissertation compares the BER performance of the dispreading after BSS and the one without BSS. According to analysis and simulation, we find that the BER of the performance of the former is better than that of the latter.We study the underdetermined mixing matrix estimation of frequency hopping signals. Although the frequency hopping signal is not sparse in time domain, but sparse in time-frequency domain by short-time Fourier transform(STFT). With the properties of the frequency hopping signals, the dissertation uses the K-means clustering algorithm to estimate the mixing matrix, and puts forward a new method of selecting the initial clustering center. According to analysis and simulation, we find that the estimation precision of the hybrid matrix is better than that of the existing selection methods.The frequency hopping technology combining with the blind source separation improves the anti-interference ability, and the study will effectively promote the continuous development of military communication anti-jamming technology, so it has an important military significance and a great realistic meaning.