Tracking Filter Engineering: The Gauss-Newton and Polynomial Filters

The book provides a complete theoretical background, and then discusses in detail the Gauss-Newton filters. Of particular interest is a new approach to the tracking of maneuvering targets that is made possible by these filters. The book also covers the expanding and fading memory polynomial filters based on the Legendre and Laguerre orthogonal polynomials, and how these can be used in conjunction with Gauss-Newton.

Fourteen carefully constructed computer programs cover the theoretical background, and also demonstrate the power of the Gauss-Newton and polynomial filters. Two of these programs include Kalman, Swerling and Gauss-Newton filters, all three processing identical data. These demonstrate Kalman and Swerling instability to which Gauss-Newton is immune, and also the fact that if an attempt is made to forestall Kalman and Swerling instability by the use of a Q matrix, then they are no longer Cramér-Rao consistent and become noticeably less accurate than the always Cramér-Rao consistent Gauss-Newton filters.

This book will be of interest to filter engineering practitioners, to graduate-level newcomers wishing to learn about Gauss-Newton and polynomial filters and to university lecturers who might wish to include material on the Gauss-Newton and polynomial filters in graduate-level courses on tracking filter engineering.