Research On 2-D Direction Finding Algorithm Based On Uniform Circular Array

The invention of the radio technology makes radio direction finding technology develop rapidly. A variety of direction finding technology has constantly been put forward. Among them, the two-dimensional (2-D) direction finding technology can provide azimuth and elevation information of target simultaneously, so it is widely used in many fields. In 2-D direction finding, uniform circular array (UCA) has been widely selected as they guarantee instant 360° coverage and uniform direction finding accuracy and resolution in azimuth estimate. In this thesis, the 2-D direction finding algorithms based on UCA are studied, mainly including the interferometer direction finding technology and the spatial spectrum estimation technology.Firstly, the basic structure of direction finding system is introduced and the receiving signal model of uniform circular array is presented. And then the principle of phase interferometer is introduced and the factors which have influence on the direction finding accuracy of it are discussed. Aimed at the contradiction between the direction finding accuracy and phase ambiguity on size requirement of array, several kinds of common methods of ambiguity resolution are analyzed. Correlative interferometer can avoid the ambiguity problem by introducing a correlation matching operation. It also can weaken the adverse influence of non-ideal factors such as mutual coupling, amplitude-phase inconsistency, noise, etc. Therefore, it has higher accuracy than phase interferometer. However, in 2-D direction finding applications, the computational complexity of correlative interferometer is great, which is difficult to meet the real-time demand in wideband direction finding applications with multiple frequency channels.Secondly, in view of the problem of large amount computational complexity of correlative interferometer in 2-D direction finding applications, an improved method based on dimension separation thoughts is presented. This method divides original 2-D angle searching into twice 1-D searching processes by exploiting the property that the correlation coefficient is not sensitive to the elevation, which can greatly reduce the computational complexity without direction finding accuracy loss. To solve the possible ambiguity problem of the improved method at high frequency, a dimension separation-based method by phase difference increments is proposed. A virtual array with smaller radius can be built through phase difference increments. The dimension separation-based method is implemented on the virtual array to acquire a coarse estimate of direction of arrival. In order to compensate the accuracy loss brought from the virtual transformation, the phase differences of original array is exploited to acquire higher direction finding accuracy. Simulation results demonstrate the effectiveness of proposed algorithm and show the efficiency of it relative to conventional correlative interferometer algorithm.Finally, super resolution direction finding technique based on the spatial spectral estimation was studied to solve the problem that phase interferometer cannot realize the monitoring of multiple targets at the same frequency. In this thesis, the classical MUSIC algorithm is firstly selected as an example to introduce the basic ideas of spatial spectrum estimation, and then the factors affecting resolution is analyzed. What’s more, the subject about estimation of source number which is closely related to the spectrum estimation method based on subspace is investigated, and the performance of different algorithms is compared. At last, the direction finding fuzzy problem in spatial spectrum estimation is discussed, and the condition of array without rank-1 ambiguity and methods of ambiguity resolution are given.