Direction of arrival estimation using adaptive directional time-frequency distributions

• Published in: Multidimensional systems and signal processing Vol. 29; no. 2; pp. 503 - 521
• Main Authors: Ali Khan, Nabeel, Ali, Sadiq, Jansson, Magnus
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.04.2018; Springer Nature B.V
• Subjects: Adaptive algorithms; Adaptive directional Time-frequency distribution; Algorithms; Artificial Intelligence; Circuits and Systems; Direction of arrival; Direction of arrival estimation; Electrical Engineering; Engineering; Frequency estimation; High resolution TFDs; Instantaneous frequency estimation; MUSIC; Robustness (control systems); Signal,Image and Speech Processing; Source separation; Time-frequency distributions; MUSIC; Instantaneous frequency estimation; Adaptive directional Time-frequency distribution; High resolution TFDs; Direction of arrival estimation
• ISSN: 0923-6082; 1573-0824; 1573-0824
• DOI: 10.1007/s11045-016-0435-y

Time-frequency distributions (TFDs) allow direction of arrival (DOA) estimation algorithms to be used in scenarios when the total number of sources are more than the number of sensors. The performance of such time–frequency (t–f) based DOA estimation algorithms depends on the resolution of the underlying TFD as a higher resolution TFD leads to better separation of sources in the t–f domain. This paper presents a novel DOA estimation algorithm that uses the adaptive directional t–f distribution (ADTFD) for the analysis of close signal components. The ADTFD optimizes the direction of kernel at each point in the t–f domain to obtain a clear t–f representation, which is then exploited for DOA estimation. Moreover, the proposed methodology can also be applied for DOA estimation of sparse signals. Experimental results indicate that the proposed DOA algorithm based on the ADTFD outperforms other fixed and adaptive kernel based DOA algorithms.