DOA Estimation Using Second-Order Differential of Invariant Noise MUSIC (SODIN-MUSIC)

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• 作者：Ali Massoud ; Aboelmagd Noureldin
• 关键词：DOA estimation ; MUSIC ; Probability of resolution ; Root mean square error
• 刊名：Circuits, Systems, and Signal Processing
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：36
• 期：2
• 页码：703-720
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Circuits and Systems; Electrical Engineering; Signal,Image and Speech Processing; Electronics and Microelectronics, Instrumentation;
• 出版者：Springer US
• ISSN：1531-5878
• 卷排序：36

文摘

Sensor arrays are widely used to locate the radiating sources by estimating the direction of arrival (DOA) of their incident signals. Among the most well-known methods employed for DOA estimation is the multiple signal classification (MUSIC). MUSIC provides outstanding performance in estimating DOAs in good propagation environments; however, it fails to estimate the DOAs in severe environments like low signal-to-noise ratio, small number of snapshots, when the incident waves are coming from close angles or when the sources are highly correlated. In this paper, we propose a new approach for DOA estimation with super-resolution capabilities and high accuracy even in the severe environments. The proposed approach is based on computing the second-order differential of invariant noise MUSIC (SODIN-MUSIC) spectrum. SODIN-MUSIC benefits from extracting useful information provided by the second-order differential of MUSIC spectrum and also utilizing the invariance property of noise subspace with respect to changing the power of the emitted signals. In this paper, the proposed SODIN-MUSIC method is developed to estimate both one-dimensional and two-dimensional DOA with any arbitrary array configurations. The simulation results show that SODIN-MUSIC yields superior performance in all distinct environments if compared to both conventional MUSIC and other newly developed MUSIC-based methods.