Particle filter based DOA estimation for multiple source tracking (MUST)

Direction of arrival estimation is a well researched topic and represents an important building block for higher level interpretation of data. The Bayesian algorithm proposed in this paper (MUST) can estimate and track the direction of multiple, possibly correlated, wideband sources. MUST approximates the posterior probability density function of the source directions in time-frequency domain with a particle filter. In contrast to other previous algorithms, no time-averaging is necessary, therefore moving sources can be tracked. MUST uses a new low complexity weighting and regularization scheme to fuse information from different frequencies and to overcome the problem of overfitting when few sensors are available.     «

Direction of arrival estimation is a well researched topic and represents an important building block for higher level interpretation of data. The Bayesian algorithm proposed in this paper (MUST) can estimate and track the direction of multiple, possibly correlated, wideband sources. MUST approximates the posterior probability density function of the source directions in time-frequency domain with a particle filter. In contrast to other previous algorithms, no time-averaging is necessary, theref...     »