The Research On High-resolution Technology Based On Array-based Direction Finding

Nowadays, electronic warfare requires high performance direction finding and positioning system. Spatial spectrum estimation algorithms have been touted by experts and scholars in related fields, because of its high resolution, high accuracy and stability characteristics. Although the study of the algorithms has made a lot of achievements or papers, the algorithms from large-scale practical application there are still some gaps. In this paper, we focu on the main difficulties that the source number estimation algorithms for traditional high-precision estimation can’t meet the complex electromagnetic environment and in the non-ideal environment(low SNR, small number of snapshots), spatial spectrum estimation algorithm resolution serious decline. This paper will study spatial spectrum estimation algorithm and source estimation method which can be used in the actual environment. The main contents of this paper:In this paper, we analyze the characteristics of the MUSIC algorithm to establish the model and antenna array signal model, depth understanding of existing sources estimation algorithm, and analyze the advantages and disadvantages of the existing algorithms, we detailed analysis the reasons about the traditional algorithms in a sharp decline in the performance of non-white noise. It supports the theory for follow-up studies.For the shortcomings of many sources estimate algorithm, based on the theory of information criterion source estimation method and diagonal loading technique, characteristic-value correcting method was used to smooth noise eigenvalue, a correction factor was proposed to ensure that the method can be applied in a complex environment. Because of the correction factor can be as divergent noise characteristic values to adjust the size, it ensured that the algorithm can keep decent performance in different circumstances. Simulation results show that the methods described in this paper has better adaptability than the conventional algorithm and it meets the accuracy requirements at a lower SNR.Completely aliasing of spatial spectrum peaks was found to be the reason that leading to a substantial decline of MSUIC algorithm performance, based on it, a method to separate two peaks from a completely aliasing spatial spectrum peak was proposed, and putting forward a concept of peak separation. MUSIC algorithm based on spectral peak separation was proposed when peak separation principle was applied to MUSIC algorithm. Simulation results show that the MUSIC algorithm based on spectral peaks separated maintain a low root mean square error and a high resolution success rate when the SNR is small(-3d B), although the difference of two angle of incidence is very small.Adaptive signal number estimation method proposed in this paper can effectively solve the problem that most sources estimate algorithm is non-adaptable, the method can be applied in the average linear, circular array, and the background noise is no longer confined space white noise. MUSIC algorithm based on spectral peak separation is mainly used in low signal to noise ratio, and the use of lower number of snapshots is not high, to improve the success rate of adjacent signal resolution.