Abstract
This paper proposes and investigates a new structure for the unbiased separation, tracking, and enhancement of uncorrelated sources by a linear array. The structure consists of a matrix preprocessing beamformer followed by an adaptive linear combiner and a postprocessing beamformer. The weights of the adaptive linear combiner are updated by using the LMS algorithm and, together with the preprocessor, implement an adaptive array whose response zeros are adjusted to minimize the output power with unity element weight vector norm constraint. By properly designing the preprocessor, first-order movements in the response zeros can be individually and proportionally controlled by first order changes in the weights in the linear combiner, and the preprocessor outputs will be due to individual sources and receiver noise in the steady state. By measuring the powers of the preprocessor outputs, it will be possible to determine if a particular preprocessor output is due to an actual source (if the associated zero is tracking a source) or merely receiver noise (if the associated zero is not tracking any source). Further SNR enhancement is then carried out by making use of those preprocessor outputs due to receiver noise to remove the correlated receiver noise components in the other preprocessor outputs tracking actual sources through the use of a matrix postprocessor. Apart from the implementation of the preprocessor and postprocessor which will be inevitable in any source separation system and which have to be designed only occasionally and whenever the response zeros have been found to have changed significantly, the algorithm has an implementation complexity which is proportional to the array size. However, as the preprocessor outputs are due primarily to individual sources in the steady state, the algorithm has only one single asymptotic time constant controlled by the designed misadjustment level and has fast tracking performance.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.