The book starts from the basic conceptual solution of a nonlinear estimation problem and provides an in depth coverage of (i) various Gaussian filters such as the unscented Kalman filter, cubature and quadrature based filters, Gauss-Hermite filter and their variants and (ii) Gaussian sum filter, in both discrete and continuous-discrete domain. Further, a brief description of filters for randomly delayed measurement and two case-studies are also included.
Features:
- The book covers all the important Gaussian filters, including filters with randomly delayed measurements.
- Numerical simulation examples with detailed matlab code are provided for most algorithms so that beginners can verify their understanding.
- Two real world case studies are included: (i) underwater passive target tracking, (ii) ballistic target tracking.
The style of writing is suitable for engineers and scientists. The material of the book is presented with the emphasis on key ideas, underlying assumptions, algorithms, and properties. The book combines rigorous mathematical treatment with matlab code, algorithm listings, flow charts and detailed case studies to deepen understanding.
The book starts from the basic conceptual solution of a nonlinear estimation problem and provides an in depth coverage of (i) various Gaussian filters such as the unscented Kalman filter, cubature and quadrature based filters, Gauss-Hermite filter and their variants and (ii) Gaussian sum filter, in both discrete and continuous-discrete domain. Further, a brief description of filters for randomly delayed measurement and two case-studies are also included.
Features:
- The book covers all the important Gaussian filters, including filters with randomly delayed measurements.
- Numerical simulation examples with detailed matlab code are provided for most algorithms so that beginners can verify their understanding.
- Two real world case studies are included: (i) underwater passive target tracking, (ii) ballistic target tracking.
The style of writing is suitable for engineers and scientists. The material of the book is presented with the emphasis on key ideas, underlying assumptions, algorithms, and properties. The book combines rigorous mathematical treatment with matlab code, algorithm listings, flow charts and detailed case studies to deepen understanding.

Nonlinear Estimation: Methods and Applications with Deterministic Sample Points
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