Coded Cover for Acoustic Vector Sensors
C. YAN (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Geert Leus – Mentor (TU Delft - Signal Processing Systems)
Daniel Fernandez Comesana – Mentor
G. Joseph – Graduation committee member (TU Delft - Signal Processing Systems)
Nitin Jonathan Jonathan Myers – Graduation committee member (TU Delft - Team Nitin Myers)
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Abstract
This study delves into the application of coded covers in enhancing Acoustic Vector Sensor (AVS) performance for sound source localization. We initially explored the use of a coded mask inspired by ultrasound imaging. However, our analysis indicated that the coded mask primarily acts as a scaling factor without substantial benefits for direction of arrival (DOA) estimation.
In response, we investigated an alternative approach using a larger cover with spaced channels, positioned above the AVS sensor. In this setup, each channel operates independently, and their combined acoustic outputs are analyzed upon reaching the sensor. Importantly, the upper surface channels can be viewed as a virtual uniform linear array (ULA), allowing the application of compressed analysis methods.
Two distinct DOA estimation approaches were developed: the compressive sampling (CS) method and the compressive covariance sensing (CCS) method. Both methods were validated, showing improved accuracy in angle estimation. Notably, the CCS method exhibited the potential to expand the number of detectable sound sources using a single AVS.
In summary, while the coded mask did not offer significant advantages, the coded cover design, along with the CS and CCS methods, improved DOA accuracy and extended the detection capabilities of single AVS.