Global Positioning Systems, Inertial Navigation, and Integration
John Wiley & Sons, 5 apr. 2004 - 416 pagina's
The only comprehensive guide to Kalman filtering and its applications to real-world GPS/INS problems Written by recognized authorities in the field, this book provides engineers, computer scientists, and others with a working familiarity with the theory and contemporary applications of Global Positioning Systems (GPS), Inertial Navigational Systems, and Kalman filters. Throughout, the focus is on solving real-world problems, with an emphasis on the effective use of state-of-the-art integration techniques for those systems, especially the application of Kalman filtering. To that end, the authors explore the various subtleties, common failures, and inherent limitations of the theory as it applies to real-world situations, and provide numerous detailed application examples and practice problems, including GPS-aided INS, modeling of gyros and accelerometers, and WAAS and LAAS. Drawing upon their many years of experience with GPS, INS, and the Kalman filter, the authors present numerous design and implementation techniques not found in other professional references, including original techniques for: * Representing the problem in a mathematical model * Analyzing the performance of the GPS sensor as a function of model parameters * Implementing the mechanization equations in numerically stable algorithms * Assessing computation requirements * Testing the validity of results * Monitoring GPS, INS, and Kalman filter performance in operation In order to enhance comprehension of the subjects covered, the authors have included software in MATLAB, demonstrating the workings of the GPS, INS, and filter algorithms. In addition to showing the Kalman filter in action, the software also demonstrates various practical aspects of finite word length arithmetic and the need for alternative algorithms to preserve result accuracy.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
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3 Signal Characteristics and Information Extraction
4 Receiver and Antenna Design
5 GPS Data Errors
6 Inertial Navigation
7 Kalman Filter Basics
8 Kalman Filter Engineering
A-code acceleration accelerometer accuracy algorithm alignment angle antenna AOR-W applications axes bandwidth baseband bias C/A-code calculated carrier frequency carrier phase chip Cholesky factor clock steering code tracking components coordinate transformation corrections correlation covariance matrix deﬁned deﬁnite derivatives despreading differential Differential GPS Doppler dynamic earth ECEF effect ellipsoid ephemeris estimate Filter ﬁrst GDOP gimbal Global Positioning System GLONASS GPS receiver GPS satellite GPS signal gyroscope host vehicle illustrated in Fig implementation inertial navigation input axis integration ionospheric ionospheric delay Kalman ﬁlter Kalman gain likelihood function linear m-ﬁle MATLAB measurement sensitivity matrix modulation MTSAT multipath noise orbit orthogonal oscillator output P-code parameters performance position propagation pseudolite pseudorange pseudorange measurements quaternion radius reference reference ellipsoid Riccati equation rotation rate rotation vector scale factor sensor signiﬁcantly speciﬁed stations strapdown subframe triangular update user’s variables velocity WAAS waveform zero