Adaptive subspace tracking algorithm based on acoustic vector sensor array
Wang Hai-lu · 2008
An acoustic vector sensor measures the acoustic pressure and all three components of the ac- oustic particle velocity at a single point in space. The main advantage of those acoustic vector-sensors over traditional scalar sensors is that they make full use of more available acoustic information,hence they will be widely used in the near future. Using acoustic vector sensor army,all direction of arrival (DOA) with out ambiguity can be estimated by multiple signal classification(MUSIC)algorithm.But when the source bearing is time-varying,the algorithm can not track the source bearing in real time. In order to resolve the problem,an adaptive subspace tracking algorithm using the maximum likelihood adaptive subspace estimation(MALASE)algorithm and MUSIC algorithm is proposed.Computer simulation results show that the method has good direction tracking performance with an error of only about 0.4°.