DOA Estimation In Impulsive Noise Environment Based On Uniform Circular Array

The classical methods of direction of arrival estimation can estimate the direction of arrival accurately, such as MUSIC algorithm and ESPRIT algorithm. But they are effective only when the array model is uniform linear array. The DOA estimation methods based on uniform circular array can estimate the azimuth and elevation. In addition, uniform circular array can get same distinguishing ability and estimation accuracy in any direction for its approximate isotropy. So it has important application in the field of radio monitoring.Cyclostationary signals are usually processed in the radio monitoring system. Cyclic statistics can identify stationary signal and circular stationary signal effectively and restrain the interference signals with different cyclic frequencies, so cyclic statistics is an important tool to wireless locating in the radio monitoring system. Noise measurement data often occurs with strong impulse due to natural and human factors in the radio channel. We usually adopt Alpha-stable distribution model to describe noise. So this paper works on the DOA estimation problem based on UCA in impulsive noise environment.Firstly, the paper researches properties of cyclostationary signals, including cyclic mean, cyclic correlation function and cyclic spectrum correlation function. Then, the detailed analysis and simulation test have been made to AM, BPSK and QPSK signals.Secondly, the DOA estimation methods based on the fractional lower-order cyclic correlation have been studied in ULA, which include the MUSIC algorithm and the ESPRIT algorithm. Then the detailed analysis and test are made to them.Thirdly, since the conventional DOA estimation methods based on UCA degenerate severely in the impulsive noise environment, this paper presents a new concept referred to as the fractional lower order cyclic correlation matrix based on UCA. Then two methods have been proposed, which are called cyclic MUSIC algorithm based on UCA in impulsive noise environment. Simulation results show that the proposed FLOCC-UCA-MUSIC algorithm can restrain the impulsive noise effectively and estimate the azimuth and elevation of signals accurately.Fourth, this paper have proposed cyclic ESPRIT algorithm based on UCA in impulsive noise environment. Simulation results show that the proposed FLOCC-UCA-ESPRIT algorithm can restrain the impulsive noise effectively and estimate the azimuth and elevation of signals accurately. At last, the plan for next step is made based on the summarization of the paper.