Electrical engineering

Physics

Subspace topology

Acoustic source localization

Noise (video)

Algorithm

Image (mathematics)

Engineering

Voltage

Artificial intelligence

Harmonics

Sound (geography)

Multiple signal classification

Direction of arrival

Antenna (radio)

Acoustics

Programming language

Microphone array

SIGNAL (programming language)

Microphone

Computer science

Sound pressure

Speech recognition

Computer vision

Smoothing

Telecommunications

IEEE/ACM Transactions on Audio Speech and Language Processing

Subspace approach of MUSIC (multiple signal classication) has become one of the most popular multi-source direction of arrival (DOA) estimations due to its easy implementation in practice. However, its localization accuracy is vulnerable to noise. This paper develops a novel MUSIC algorithm, more suitable in noisy environments, using the relative sound pressure measurements of a higher order microphone array. This proposed MUSIC approach is also decomposed into the spherical harmonics domain where a frequency smoothing technique is allowed to de-correlate the coherent source signals for improved localization accuracy. The proposed algorithm is also capable of estimating the number of active sound sources, which is pre-requisite knowledge for the traditional MUSIC approach. Extensive experimental results in diverse environments using both simulated and real recordings show advantages of the proposed algorithm over the traditional MUSIC method as well as another recently proposed multi-source localization approach.

Multiple Source Direction of Arrival Estimations Using Relative Sound Pressure Based MUSIC