数字信号处理中MUSIC方法的新教学思路
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摘要
多重信号分类MUSIC算法是基于信号与噪声子空间正交性的一种超分辨谱估计方法。自适应波束形成技术则是通过在干扰信号波达方向上置零来实现输出信干噪比最大化。通过在所有感兴趣波达方向上扫描,波束形成器也可以用来实现波达方向估计。MUSIC算法和波束形成技术的原理看似不同。然而,有文献表明,MUSIC算法可被表示为一个波束形成器。基于这一事实,在本文中,我们首先介绍了MUSIC算法和最小无失真响应波束形成技术MVDR的原理。然后,给出MUSIC算法和MVDR波束形成器的等价表示形式。最后,将MUSIC算法与MVDR波束形成器进行比较。通过上述内容的讲解,可以使学生获得关于MUSIC算法新的认识。
Multiple Signal Classification( MUSIC) algorithm is developed based on the so-called orthogonality of the signal and noise subspaces,which has the advantage of super-resolution. Beamforming techniques which form nulls at the direction of interferences maximizes the output signal-to-interference and noise ratio. The functionality of the MUSIC algorithm and beamforming techniques seems different with each other. However,there has been literature shows that the MUSIC algorithm can be alternatively expressed as a beamformer. Based on this fact,in this paper,we firstly introduce the MUSIC algorithm and the beamforming techniques. Then,the alternative formulation of the MUSIC algorithm as a beamformer is presented. Thirdly,based on this alternative formulation,we evaluate performance of the MUSIC algorithm and compare it with the minimum variance distortionless response beamformer to bring students a new insight of the MUSIC algorithm.
Multiple Signal Classification( MUSIC) algorithm is developed based on the so-called orthogonality of the signal and noise subspaces,which has the advantage of super-resolution. Beamforming techniques which form nulls at the direction of interferences maximizes the output signal-to-interference and noise ratio. The functionality of the MUSIC algorithm and beamforming techniques seems different with each other. However,there has been literature shows that the MUSIC algorithm can be alternatively expressed as a beamformer. Based on this fact,in this paper,we firstly introduce the MUSIC algorithm and the beamforming techniques. Then,the alternative formulation of the MUSIC algorithm as a beamformer is presented. Thirdly,based on this alternative formulation,we evaluate performance of the MUSIC algorithm and compare it with the minimum variance distortionless response beamformer to bring students a new insight of the MUSIC algorithm.
引文
[1]Ralph,O.Schmidt,Multiple Emitter Location and Signal Parameter Estimation,IEEE Transactions On Antennas and Propagation,vol.AP-34,No.3,276-280,March 1986.
[2]A.Banerjee,A joint economic-lot-size model for purchaser and vendor,Decision Sciences,vol.17,pp.292-311,1986.J.Capon,High Resolution Frequency-wavenumber Spectrum Analysis,Proceedings of the IEEE,vol.57,No.8,1408-1418,August1969.
[3]B.P.Ng,A MUSIC Approach for Estimation of Directions of Arrival of Multiple Narrowband and Broadband Sources,Signal Processing,vol.40,No.2-3,319-323,1994.
[2]A.Banerjee,A joint economic-lot-size model for purchaser and vendor,Decision Sciences,vol.17,pp.292-311,1986.J.Capon,High Resolution Frequency-wavenumber Spectrum Analysis,Proceedings of the IEEE,vol.57,No.8,1408-1418,August1969.
[3]B.P.Ng,A MUSIC Approach for Estimation of Directions of Arrival of Multiple Narrowband and Broadband Sources,Signal Processing,vol.40,No.2-3,319-323,1994.