Estimation with Applications to Tracking and Navigation: Theory Algorithms and Software - Hardcover

Über die Autorin bzw. den Autor

YAAKOV BAR-SHALOM, PhD, is Distinguished Professor in the Department of Electrical and Computer Engineering and Director of the Estimation and Signal Processing Lab at the University of Connecticut in Storrs.

X. RONG LI, PhD, is Associate Professor in the Department of Electrical Engineering at the University of New Orleans.

THIAGALINGAM KIRUBARAJAN, PhD, is Assistant Research Professor in the Department of Electrical and Computer Engineering and Associate Director of the Estimation and Signal Processing Lab at the University of Connecticut in Storrs.

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Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation

Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics.

The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include:
* Problems that apply theoretical material to real-world applications
* In-depth coverage of the Interacting Multiple Model (IMM) estimator
* Companion DynaEst(TM) software for MATLAB(TM) implementation of Kalman filters and IMM estimators
* Design guidelines for tracking filters

Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.

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Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation

Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics.

The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include:
* Problems that apply theoretical material to real-world applications
* In-depth coverage of the Interacting Multiple Model (IMM) estimator
* Companion DynaEst(TM) software for MATLAB(TM) implementation of Kalman filters and IMM estimators
* Design guidelines for tracking filters

Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.