Array Signal Processing: Concepts and Techniques
Array Signal Processing: Concepts and Techniques
Detection of Wheezes Using a Wearable Distributed Array of Microphones
BSN '09 Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks
Wideband smart antenna theory using rectangular array structures
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Optimal array pattern synthesis using semidefinite programming
IEEE Transactions on Signal Processing
Microphone array speech processing
EURASIP Journal on Advances in Signal Processing - Special issue on microphone array speech processing
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Frequency-Invariant (FI) beamforming is a well known array signal processing technique used in many applications. In this paper, an algorithm that attempts to optimize the frequency invariant beampattern solely for the mainlobe, and relax the FI requirement on the sidelobe is proposed. This sacrifice on performance in the undesired region is traded off for better performance in the desired region as well as reduced number of microphones employed. The objective function is designed to minimize the overall spatial response of the beamformer with a constraint on the gain being smaller than a pre-defined threshold value across a specific frequency range and at a specific angle. This problem is formulated as a convex optimization problem and the solution is obtained by using the Second Order Cone Programming (SOCP) technique. An analysis of the computational complexity of the proposed algorithm is presented as well as its performance. The performance is evaluated via computer simulation for different number of sensors and different threshold values. Simulation results show that, the proposed algorithm is able to achieve a smaller mean square error of the spatial response gain for the specific FI region compared to existing algorithms.