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Artech House Bayesian Multiple Target Tracking - Radar Series Book

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Description

This comprehensive guide applies Bayesian inference frameworks to solve complex multiple target tracking problems across radar systems, multiple sensors, and multi-platform environments. The book presents mathematically rigorous algorithms for tracking scenarios where traditional methods fall short, including situations without direct contacts or data association. It covers non-linear Multiple Hypothesis Tracking and United Tracking theory as proven approaches for handling challenging tracking scenarios. Detailed worked examples throughout the text demonstrate practical implementation of developed concepts and algorithms. Readers learn to address tracking problems where observations are non-linear functions of target state, gaining the mathematical foundation and practical tools needed to develop robust tracking solutions for modern radar and sensor fusion applications.

Key Features

Bayesian inference framework provides mathematically sound foundation for designing multiple target tracking algorithms across complex radar systems.

Non-linear Multiple Hypothesis Tracking methods enable accurate target tracking without requiring direct contact or prior data association.

Theory of United Tracking offers robust solutions for multi-sensor and multi-platform environments in radar applications.

Detailed worked examples throughout the Bayesian Multiple Target Tracking book illustrate algorithm development and real-world implementation.

Covers non-linear observation models where measurements are complex functions of target location and state.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
31 July 1999
Listed Since
23 January 2007

Barcode

No barcode data available

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