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Signal Processing for Joint Radar Communications (Hardcover)
Loot Price: R3,094
Discovery Miles 30 940
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Signal Processing for Joint Radar Communications (Hardcover)
Series: IEEE Press
Expected to ship within 9 - 15 working days
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In the last five years, significant developments and applications
have been made within radar communications. Signal Processing for
Joint Radar-Communications delves into the recent advances within
the theory and applications of joint radar-communications (JRC) and
includes the challenges that are still faced today. Bringing
together newly written expert contributions from leading
researchers within the field of Joint Radar-Communications, the
book tackles key JRC signal processing challenges such as common
waveform design for both radar and communications systems, receiver
processing including interference mitigation methods, learning and
cognition, resource allocation, jamming and clutter, optimization
methods, and automotive JRC. It presents possible solutions to
these challenges and highlights some future research directions.
The goal of this book is to further contribute to the diffusion of
newly developed JRC tools into the radar and communications
communities and to illustrate recent successes in applying modern
signal processing theories to solving core problems in JRC. The
contributors present new results on algorithmic methods and
applications of JRC in diverse areas, which include autonomous
vehicles, waveform design, information theory, privacy, security,
beamforming, estimation theory, and sampling. This reflects the
increasing number of applications in signal processing and
communications. Research activities covered in the book include
recognizing and solving convex optimization problems that arise in
applications, deriving powerful algorithmic methods, utilizing the
theory of convex problems to characterize and gain insight into the
optimal solution and bounds on performance, developing techniques
for exploiting problem structure in interior-point methods for
large scale optimization, and convex relaxations of hard,
non-convex problems
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