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Locating, Classifying and Countering Agile Land Vehicles: With Applications to Command Architectures de David D. Sworder

Locating, Classifying and Countering Agile Land Vehicles: With Applications to Command Architectures

Autor David D. Sworder, John E. Boyd
en Limba Engleză Hardback – 7 aug 2015
This book examines real-time target tracking and identification algorithms with a focus on tracking an agile target. The authors look at several problems in which the tradeoff of accuracy and confidence must be made. These issues are explored within the context of specific tracking scenarios chosen to illustrate the tradeoffs in a simple and direct manner. The text covers the Gaussian wavelet estimator (GWE) which has a flexible architecture that is able to fuse uncommon sensor combinations with non-temporal structural constraints.
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Specificații

ISBN-13: 9783319194301
ISBN-10: 3319194305
Pagini: 290
Ilustrații: XIV, 290 p. 165 illus., 161 illus. in color.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.73 kg
Ediția:1st ed. 2015
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

A Model for Tracking and Classification.- Target Location Using the Extended Kalman Filter.- Tracking an Agile Target.- Intercept and Target Prediction.- Classification and Target Tempo.- Assurance Regions on a Road Grid.- ActionWindows with Resource Limits.- Serendipitous Events in Tracking and Classification.- Deceiving a Classifier.

Notă biografică

Dave Sworder is a Professor of ECE at UCSD
John Boyd is the Chief Scientist, Information Systems for Cubic Defense Applications.

Textul de pe ultima copertă

This book examines real-time target tracking and identification algorithms with a focus on tracking an agile target. The authors look at several problems in which the tradeoff of accuracy and confidence must be made. These issues are explored within the context of specific tracking scenarios chosen to illustrate the tradeoffs in a simple and direct manner. The text covers the Gaussian wavelet estimator (GWE) which has a flexible architecture that is able to fuse uncommon sensor combinations with non-temporal structural constraints. 
·         Discusses applied estimation and prediction of terrestrial targets
·         Covers fusion of heterogeneous sensor types and tracking with non-temporal engagement constraints
·         Examines confidence that the target will be captured and motion analysis of land vehicles

Caracteristici

Discusses applied estimation and prediction of terrestrial targets Covers fusion of heterogeneous sensor types and tracking with non-temporal engagement constraints Examines confidence that the target will be captured and motion analysis of land vehicles