Download e-book for kindle: Adaptive Antennas and Receivers by Melvin M. Weiner
By Melvin M. Weiner
In our smooth age of distant sensing, instant verbal exchange, and the approximately never-ending checklist of alternative antenna-based functions, advanced difficulties require more and more refined strategies. traditional antenna structures aren't any longer fitted to high-noise or low-signal purposes corresponding to intrusion detection. Detailing powerful ways to non-Gaussian susceptible sign detection, Adaptive Antennas and Receivers offers an authoritative creation to cutting-edge study at the modeling, trying out, and alertness of those applied sciences. Edited via cutting edge researcher and eminent specialist Melvin M. Weiner, this booklet is the 1st to combine 3 complex ways to non-Gaussian vulnerable sign detection right into a unmarried reference: homogeneous partitioning of the surveillance quantity, adaptive antennas, and adaptive receivers. Comprising self-contained chapters contributed by means of well known specialists corresponding to Donald D. Weiner and Ronald Fante, each one bankruptcy explores the innovations, theoretical foundation, and purposes of the strategy below dialogue. The publication considers sign detection within the presence of exterior noise resembling muddle residue, interference, atmospheric noise, jammers, exterior thermal noise, in vivo surrounding tissue, and camouflaging fabric, making it excellent to be used throughout a vast spectrum of functions. This authoritative reference provides greater than 750 figures and tables, 1460 equations, and 640 references. Adaptive Antennas and Receivers is a perfect source for making improvements to functionality in surveillance, conversation, navigation, synthetic intelligence, desktop tomography, neuroscience, and intrusion detection structures, to call just a couple of.
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Extra resources for Adaptive Antennas and Receivers
Let the Doppler bins be indexed by kD, 1 # kD # M. The resolution cell corresponding to kR ¼ j, kA ¼ k, and kD ¼ m is referred to as the jkmth range – azimuth – Doppler (R/A/D) cell. The total number of R /A/D cells is given by J £ K £ M. The temporal data magnitudes and FFT coefﬁcient magnitudes are used by the mapping processor to enable classiﬁcation of the R /A/D cells into BN cells and CL cells.
For each condition being violation and each SOU that could have caused the violation, an additional output data hypothesis is posted which describes the condition being violated and the SOU that could have caused the violation. The SOUs, which fail to produce some particular support evidence for a single input signal or fail to result in any valid explanation for a combination of input signals, are classiﬁed as negative evidence SOUs. The hypothesis concerning the violation-type discrepancy and each of the additional hypotheses are then connected by a negative evidence link and are labeled as VIOLATIONNEGATIVE EVIDENCE SOU.
1 for an LOD. 1 Power function for a locally optimum detector. 2 Illustration of non-optimality of locally optimum detector when u . uc. , u p 1) is to ﬁnd that receiver which maximizes the slope of the power function at u ¼ 0. 2. Consequently, the LOD is identical to that receiver which maximizes the slope of power function at u ¼ 0: As a result, the LOD will maximize PD for u sufﬁciently small. However, other receivers may yield larger values of PD when u becomes large. 2, for u . uc another receiver is shown to out-perform the LOD.
Adaptive Antennas and Receivers by Melvin M. Weiner