Time-Domain Wideband DOA Estimation Under the Convolutional Sparse Coding Framework
Zhengyu Wan, Wei Liu
Abstract
The wideband direction of arrival (DOA) estimation problem can be formulated into a narrowband form by applying discrete Fourier Transform (DFT) to sensor measurements; however, a large number of temporal snapshots are required in order to meet the narrowband assumption in the frequency-domain. To reduce the number of snapshots required, a convolutional sparse coding (CSC) based wideband signal model is proposed for direct time-domain DOA estimation, and a group sparsity based minimization problem is formulated. Simulation results indicate that the proposed time-domain CSC (TD-CSC) based method has a better performance than the frequency-domain method, but with a higher computational complexity.
Topics & Concepts
NarrowbandWidebandComputer scienceAlgorithmFrequency domainTime domainComputational complexity theoryDirection of arrivalConvolutional codeDiscrete Fourier transform (general)Coding (social sciences)Fourier transformSpeech recognitionElectronic engineeringMathematicsDecoding methodsTelecommunicationsShort-time Fourier transformStatisticsFourier analysisEngineeringComputer visionMathematical analysisAntenna (radio)Direction-of-Arrival Estimation TechniquesSpeech and Audio ProcessingStructural Health Monitoring Techniques