Study On DOA Analysis Method Under Impulsive Noise Environment

Array signal processing technology develops fast during the past years. DOA estimation as a core question of array signal processing draws more and more attention, which is widely used in sonar, radar, communication, earthquake detection, biomedical, anti-jamming position and so on. Traditionanl DOA estimation methods analysis is based on the second statistics and Gaussian distribution, but in reality, there are lots of noises with significant peak pulse characteristics, whose statistical characteristics do not accord with the traditional Gaussian noise. More extensively applicable a stable distribution model is usually applied to describe this kind of impulsive random signal. Because a stable distribution noise does not own limited second order moment, the performance of DOA estimation methods based on the second statistics degenerates seriously and even failure completely. According to this phenomenon, new DOA estimation methods applied to impulse noise environment arc studied by combining the fractional lower order statistics based signal processing methods with traditional DOA estimation methods.First, this dissertation introduces the research background and the current development of the subject; second, expounds DOA estimation methods and the decorrelate coherence technology; Third, introduces the definitions of α-stable distribution and the fractional lower order statistics and current DOA estimation methods based on the fractional lower order statistics. Finally, according to different forms of the received array, new DOA estimation methods for coherent signals which applied to α-stable distribution noise environment are proposed.When the received array is uniform linear array (ULA), decoherence MUSIC and ESPRIT estimation methods under impulse noise environment degenerate because of lacking of the autocorrelation matrix. In this dissertation, spatial smoothing technology or signal Eigvector Rearranging method are used to decoherence for coherent signals and using nonlinear processing method to restain impulse noise received signals, modified MUSIC estimation methods(FSM、FSRM、LERM) and modified ESPRIT estimation method (FSE、 FERE) are proposed. Theory analysis and simulation results suggest that the new methods can restain the interference of impulse noise effectively, and give the accurate DOA estimation of coherent signals. When making the DOA estimation of coherent signals based on uniform circular array (UCA), the manifold matrix of UCA is transformed into a form similar to that of a uniform linear array by using mode space method firstly, then combine the signal processing methods based on the fractional lower order statistics and spatial smoothing decoherence technology with traditional MUSIC and ESPRIT methods, modified MUSIC algorithm (LMSM) and modified ESPRIT algorithm (LMSE) are proposed which are applied to a stable distribution. Theory analysis and simulation results show that these two algorithms both have good performance under the Gaussian noise and impulse noise environment and obtain the effective DOA estimation for coherent signals of UCA.