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| Part Ⅰ Theory 1 ORDINARY DIFFERENTIAL EQUATIONS AND STABILITY Difierential Equations StabilityTheory 2 RANDOM PROCESSES AND STOCHASTIC MODELS IntroductiOn Random Variables and Processes Random Difrerential Equations Linear Models Dynamical Models 3 0BSERVABILITY AND CONTROLLABILITY IntrOductiOn Observability and Controllability Canonical Forms Stochastic Modeling 4 FILTERING THEORY IntrOduction The Minimum Variance Unbiased Estimator Function Space Integrals for the Conditional Distribution Alternative Approaches for the Linear Estimation Problem Linear and NonLinear Filtering in Discrete Time- “WideSense”Solution of the Linear Filtering Problem Problems 5 GLOBAL THEORY OF FILTERING IntrOduction Properties of the Riccati Equation Exponential Stability Examples and Problems Effects of Errors in Optimal Gains- A Table of Results for the Asymptotic Theory 6 STOCHnSHC STABILITY Information and Filtering 7 OPTIMAL FILTERING FOR CORRELATED NOISE Processes Introduction Filtering for Colored Noise 8 APPROXIMATE OP~MAL NON—LINEAR FILTERING The Separation Principle Numerical Solution of the Riccati Equation Equilibrium Solutions ofthe Riccati Equarion Numerical Methods 9 OPTIMUM FILTING RING FOR DISCREfE TIME RANDOM PR0cEssEs 10 STOCIiASTIC CONTROL Markov Processes and SemiGroups 11 OPEN QuEsItONS AND Historical Comments Open Questions Historical Comments Part Ⅱ Applications 12 APPLICA FION TO NAVIGATION The Application ofa MathematicalTheory Modeling Computationat Solution 13 APPLICATIONS OF FILTER THEORY AND MODELING TECHNIQUES Equation Formulation and Notation Advantages ofthe Sequential Estimator Curve Fitting Sequential（Kalman Bury）Filtering Comparisort ofCurve Fitting and Sequcntial Flitefing Application to Space Navigation Linearization Noise and Error Terms The Randora Disturbance 14 FREE FLIGHT AND POWERED FLIGHT NAVIGATION 15 ERROR ANALYSES AND SUB-OPTIMAL MODELING 16 ERRORS IN THE FILTERING PROCESS APPENDIX A LEAST SQUARES CURVE FITTING APPENDIX B PROBABILITY REVIEW REFERENCES INDEX |
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