£140.37

Springer Non-Cooperative Target Tracking and Fusion Book

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Description

Non-Cooperative Target Tracking, Fusion and Control: Algorithms and Advances provides a concise and comprehensive overview of tracking, fusion, and control methods. Published by Springer as part of the Information Fusion and Data Science series, this work focuses on practical algorithms for non-cooperative targets, such as air and space-borne targets, rather than just theoretical frameworks. The text explores advanced techniques including Gaussian mixture cardinalized probability hypothesis density (CPHD) filters, optimization on manifold, the construction of filter banks and tight frames, and structured sparse representation. With a variety of illustrative and computational examples, this book serves as a technical resource for understanding modern approaches to target tracking and data science.

Key Features

This Springer publication provides a comprehensive overview of non-cooperative target tracking, fusion, and control.

The text focuses on practical algorithms for non-cooperative targets including air and space-borne targets.

Explore advanced technical methods such as Gaussian mixture cardinalized probability hypothesis density (CPHD) filters.

Learn about complex processes including optimization on manifold and the construction of filter banks and tight frames.

The book includes structured sparse representation and various illustrative and computational examples for technical application.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
10 January 2019
Listed Since
09 January 2019

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No barcode data available

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