Studies On Technologies Of Direction-of-Arrival Estimation And Analysis Of Communication Signals

It is very important to analyze and identify the complex communication signals, and also to locate the impinging sources in the military and civilian areas. Direction of arrival (DOA) estimation is an important topic in electronic reconnaissance system. Frequency estimation and spectrum analysis are the foundation of the analysis of complex communication signals in electronic reconnaissance system. Chaotic direct sequence spread spectrum (DSSS) communication systems have merits of anti-reconnaissance and low probability of intercept, and they will play an increasingly important role in future military communications. Blind estimation of chaotic DSSS signal has received considerable attention in recent years.The main work of this dissertation is studying the electronic reconnaissance system: (1) The structure of the array sensors together with the signal properties in time domain are used to study the problems of high-resolution two-dimensional (2-D) DOA estimation and pair-matching; (2) For spectrum analysis, several frequency estimation algorithms and spectrum analysis methods are developed; (3) Blind estimation techniques of chaotic DSSS signal are studied. The main creative works are concluded as follows.We make an in-depth study on pair-matching in joint estimation of 2-D DOA for L-shape arrays. A new method of 2-D DOA estimation based on joint SVD is proposed to achieve automatically pair-matching with better estimation precision. Furthermore, two modified pair-matching algorithms based on the cross-correlation matrix are developed, which extend the range of the elevation and azimuth angles. An algorithm of joint estimation frequency and DOA based on the pseudocovariance matrix in time domain is investigated. The DOA and frequency are estimated respectively, and the pair-matching can be achieved with the cross-correlation of pseudocovariance matrices.A new algorithm of joint estimation of 2-D DOA for double L-shape arrays is investigated. This method makes use of a restriction of space direction formed by the special structure of array sensors. The new method can not only be used to pair the elevation angles and azimuth angles, but also improve the estimation accuracy by weighted least squares algorithm. Three implementation schemes are given at last.Two methods of 2-D DOA estimation for L-shape arrays with noncircular sources are proposed. The method of joint SVD can be adaptive to more signal sources, achieve a better estimation precision and automatically pair 2-D angle estimates by the merits of noncircular characteristics and the structure of L-shape arrays. By using the noncircular characteristics, the fast algorithm provides a better performance than the traditional fast algorithm such as propagator method (PM).Three fast frequency estimation techniques are discussed respectively. The iterative method of frequency estimation based on multi-channels, with high estimation precision, low SNR threshold, is easy to implement with hardware. The method based on partial auto-correlation technique is computationally efficient. And the estimation precision of the algorithm based on pre-filtering does not depend on the signal frequency to be estimated. For spectrum analysis, a fast algorithm for non-uniform Fourier Transform is developed to fast compute the signal spectrum at arbitrary frequency components, and it can be used in the receiver of electronic reconnaissance.A new method of blind estimation for short-code chaotic spread spectrum sequence is proposed, which is based on principal component analysis (PCA) and has good performance at low SNR condition. Two new methods are developed for blind estimation for long-code chaotic spread spectrum sequence. One is based on nonlinear modeling and prediction, and it can despread the long-code chaotic DSSS signal blindly and obtain the parameters, such as spread gain and information code synchronization. The other is based on the generalized synchronization (GS) and Unscented Kalman filter (UKF), and it can despread the long-code chaotic DSSS signal blindly and has a good performance at low SNR condition.