Statistical Orbit DeterminationStatistical Orbit Determination presents fundmentals of orbit determination--from weighted least squares approaches (Gauss) to today's high-speed computer algorithms that provide accuracy within a few centimeters. Numerous examples and problems are provided to enhance readers' understanding of the material.
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Contents
1 | |
17 | |
Chapter 3 Observations | 93 |
Chapter 4 Fundamentals of Orbit Determination | 159 |
Chapter 5 Square Root Solution Methods | 285 |
Chapter 6 Consider Covariance Analysis | 387 |
Appendix A Probability and Statistics | 439 |
Appendix B Review of Matrix Concepts | 473 |
Appendix E Analytical Theory for NearCircular Orbits | 493 |
Appendix F Example of State Noise and Dynamic Model Compensation | 499 |
Appendix G Solution of the Linearized Equations of Motion | 511 |
Appendix H Transformation between ECI and ECF Coordinates | 517 |
Bibliography Abbreviations | 523 |
Bibliography | 525 |
Author Index | 537 |
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Common terms and phrases
ˆxk accuracy algorithm altimeter applications Assume axis Cholesky Cholesky decomposition clock components computed consider covariance consider parameters constant coordinate system covariance matrix defined density function derived described deviation diagonal differential equations dynamic Earth ephemeris epoch equations of motion error covariance matrix estimation error covariance example expressed filter fist frequency given by Eq GPS satellites gravitational Hence Householder transformation initial conditions integration ionosphere laser least squares linear mass measurement update node normal normal matrix Note observation errors obtained orbit determination orbit elements orthogonal transformations performance index perturbation position and velocity positive definite priori information process noise propagation pseudorange random variable range receiver represents residuals rotation Section semimajor axis sequential estimation signal solution square root Tapley tion TOPEX/Poseidon tracking transition matrix upper triangular variance yields zero