Download PDF by Melvin M. Weiner: Adaptive Antennas and Receivers

By Melvin M. Weiner

ISBN-10: 084933764X

ISBN-13: 9780849337642

In our smooth age of distant sensing, instant communique, and the approximately unending checklist of alternative antenna-based purposes, complicated difficulties require more and more refined options. traditional antenna platforms are not any longer fitted to high-noise or low-signal purposes similar to intrusion detection. Detailing powerful ways to non-Gaussian susceptible sign detection, Adaptive Antennas and Receivers presents an authoritative creation to cutting-edge study at the modeling, trying out, and alertness of those applied sciences. Edited by way of cutting edge researcher and eminent professional Melvin M. Weiner, this publication is the 1st to combine 3 complex methods to non-Gaussian susceptible 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 popular specialists similar to Donald D. Weiner and Ronald Fante, every one bankruptcy explores the thoughts, theoretical foundation, and purposes of the strategy lower than dialogue. The ebook considers sign detection within the presence of exterior noise akin to muddle residue, interference, atmospheric noise, jammers, exterior thermal noise, in vivo surrounding tissue, and camouflaging fabric, making it perfect to be used throughout a vast spectrum of purposes. This authoritative reference offers greater than 750 figures and tables, 1460 equations, and 640 references. Adaptive Antennas and Receivers is a perfect source for bettering functionality in surveillance, conversation, navigation, synthetic intelligence, machine tomography, neuroscience, and intrusion detection structures, to call just a couple of.

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In the radar detection problem considered in this research, it is assumed that, the signal environment is unknown a priori, even though mathematical models, for various signals that can arise, are assumed to be known. , Gaussian receiver, LODs, GLRT) is straightforward. The difficult problem addressed by the IPUS architecture deals with the use of measured data to identify suitable mathematical models, for approximating the various signals received from the unknown environment. © 2006 by Taylor & Francis Group, LLC A New Approach to Radar Detection 23 The algorithms employed in the IPUS architecture to identify mathematical models for approximating the received signals, are referred to as signal processing algorithms (SPAs).

Since the data collected from the environment is random, it is not possible to carry out an exact probability distribution identification using a reasonably small amount of data. Consequently, it is better to think about the probability distribution identification problem as an approximation problem, where we expect to select PDFs and their parameters, which result in good approximations to the underlying probability distributions. 4. Also, reprocessing of the data is not allowed by the feedforward configuration.

Associated with the disturbance in the region, where the test cell is located. In practice, Ozturk’s algorithm may indicate that, several different PDFs are suitable for approximating a particular disturbance. When this is the case, it may be desirable to implement several LODs and fuse the results. Hence, descriptors should be allocated to each cell for describing one or more joint PDFs in terms of their types, scales, locations, and shape parameters. 3. TARGET D ETECTION Indexing of the Cells Target Detection Step 2: Target detection Preprocessor Mapping of the Space Step 1: Classification of the test cells As mentioned previously, the type of detector depends upon whether the detection problem has been classified as a strong signal case (SSC), weak signal case (WSC), or intermediate signal case (ISC).

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Adaptive Antennas and Receivers by Melvin M. Weiner


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