Tracking and Kalman Filtering Made Easy
A unique, easy-to-use guide to radar tracking and Kalman filtering This book presents the first truly accessible treatment of radar tracking; Kalman, Swerling, and Bayes filters for linear and nonlinear ballistic and satellite tracking systems; and the voltage-processing methods (Givens, Householder, and Gram-Schmidt) for least-squares filtering to correct for computer round-off errors. Tracking and Kalman Filtering Made Easy emphasizes the physical and geometric aspects of radar filters as well as the beauty and simplicity of their mathematics. An abundance of design equations, procedures, and curves allows readers to design tracking filters quickly and test their performance using only a pocket calculator! The text incorporates problems and solutions, figures and photographs, and astonishingly simple derivations for various filters. It tackles problems involving clutter returns, redundant target detections, inconsistent data, track-start and track-drop rules, data association, matched filtering, tracking with chirp waveform, and more. The book also covers useful techniques such as the moving target detector (MTD) clutter rejection technique. All explanations are given in clear and simple terms, including: * The voltage-processing approach to least-squares filtering * The correlation between such procedures as discrete orthogonal Legendre polynomial (DOLP) and voltage processing * The mathematical sameness of tracking and estimation problems on the one hand, and sidelobe canceling and adaptive array processing on the other * The massively parallel systolic array sidelobe canceler processor * Important computational accuracy issues * An appended comparison between the Kalman and the Swerling filters, written by Dr. Peter Swerling Tracking and Kalman Filtering Made Easy is invaluable for engineers, scientists, and mathematicians involved in tracking filter design. Its straightforward approach makes it an excellent textbook for senior-undergraduate and first-year graduate courses.
Why Read This Book
You will get a concise, highly practical introduction to radar tracking and Kalman filtering that emphasizes geometric intuition and hands-on design rather than abstruse theory. The book's calculator-friendly design equations, worked examples, and focus on numerical stability (Givens, Householder, Gram‑Schmidt) let you design and test real tracking filters quickly and reliably.
Who Will Benefit
Practicing engineers and advanced students who need a practical, intuitive guide to designing and implementing radar tracking and Kalman filters for ballistic, satellite, and tactical applications.
Level: Intermediate — Prerequisites: Familiarity with linear algebra, basic probability and statistics, and elementary signals/systems; some exposure to radar concepts or control/estimation is helpful but not required.
Key Takeaways
- Understand the physical and geometric interpretation of the Kalman filter and how it applies to radar tracking
- Design and implement linear tracking filters using concise, calculator-friendly equations and procedures
- Apply numerical linear-algebra techniques (Givens, Householder, Gram‑Schmidt) to avoid round-off and improve least-squares stability
- Extend basic filters to nonlinear and specialized variants (EKF, Swerling/Bayes approaches) for ballistic and satellite tracking
- Analyze filter performance using covariance tools and practical design curves, and test performance with simple simulations or calculators
Topics Covered
- Introduction: What Is Tracking and Why It Matters
- Radar Measurements and Geometric/Physical Models
- Least Squares and Voltage-Processing Methods (Givens, Householder, Gram‑Schmidt)
- Kalman Filter: Intuition, Derivation, and Basic Forms
- Discrete Implementation and Numerical Stability Issues
- Extensions: Swerling, Bayes Filters, and Nonlinear Tracking (EKF)
- Ballistic and Satellite Tracking Applications
- Maneuvering Targets and Adaptive Filtering
- Filter Design Procedures, Curves, and Pocket‑Calculator Examples
- Performance Analysis: Covariance, Error Bounds, and Tuning
- Practical Issues: Initialization, Misalignment, and Measurement Errors
- Problems, Worked Examples, Figures, and Photographs
Languages, Platforms & Tools
How It Compares
More accessible and design-focused than Bar‑Shalom & Li's Estimation and Tracking, and less abstract than Maybeck's Stochastic Methods — Brookner emphasizes practical, calculator-ready procedures and numerical remedies.
