The Fourth Order Cumulant-Based MUSIC Algorithm for Harmonic Retrieval in Colored Noise
Hou Chu-lin, Wang De-shi · 2009
The MUSIC algorithm is well known for its high resolution capability and various aspects of its statistical performance have been investigated. In this paper, a general fourth order cumulant matrix which conforms with the structure of MUSIC algorithm is introduced. Because the fourth order cumulant is insensitive to Gaussian noise, the MUSIC-type method can be reformulated using the fourth-order cumulant matrices instead of autocorrelation matrices when additive noise is colored Gaussian. By doing so, the additive colored Gaussian noise can be suppressed. So fourth order cumulant-based MUSIC algorithm provides better resolution and estimation performance when noise is color. Firstly,the theory of MUSIC algorithm is studied; additionally, the relation between fourth order cumulant and autocorrelation function is analyzed. Simulation results demonstrate the effectiveness of the cumulant-based MUSIC algorithm, and it can restrain effectively the effect of coloured noise comparing with its equivalent second-order statistics-based version. Moreover, it has higher resolution probability and low SNR scenario in direction of arrival estimation.