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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics
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Fundamentals of Differential Beamforming (Paperback, 1st ed. 2016)
Loot Price: R1,941
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Fundamentals of Differential Beamforming (Paperback, 1st ed. 2016)
Series: SpringerBriefs in Electrical and Computer Engineering
Expected to ship within 10 - 15 working days
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This book provides a systematic study of the fundamental theory and
methods of beamforming with differential microphone arrays (DMAs),
or differential beamforming in short. It begins with a brief
overview of differential beamforming and some popularly used DMA
beampatterns such as the dipole, cardioid, hypercardioid, and
supercardioid, before providing essential background knowledge on
orthogonal functions and orthogonal polynomials, which form the
basis of differential beamforming. From a physical perspective, a
DMA of a given order is defined as an array that measures the
differential acoustic pressure field of that order; such an array
has a beampattern in the form of a polynomial whose degree is equal
to the DMA order. Therefore, the fundamental and core problem of
differential beamforming boils down to the design of beampatterns
with orthogonal polynomials. But certain constraints also have to
be considered so that the resulting beamformer does not seriously
amplify the sensors' self noise and the mismatches among sensors.
Accordingly, the book subsequently revisits several performance
criteria, which can be used to evaluate the performance of the
derived differential beamformers. Next, differential beamforming is
placed in a framework of optimization and linear system solving,
and it is shown how different beampatterns can be designed with the
help of this optimization framework. The book then presents several
approaches to the design of differential beamformers with the
maximum DMA order, with the control of the white noise gain, and
with the control of both the frequency invariance of the
beampattern and the white noise gain. Lastly, it elucidates a joint
optimization method that can be used to derive differential
beamformers that not only deliver nearly frequency-invariant
beampatterns, but are also robust to sensors' self noise.
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