Optimal Estimation Methods
|
This course serves to teach traditional concepts and recent advances in estimation,
and to relate these concepts to modern dynamic systems found in aerospace disciplines.
This course stresses modeling of physical problems into mathematical terms. Examples
will be given from both spacecraft and aircraft systems.
TEXT: “Optimal Estimation of Dynamic Systems,” by J.L. Crassidis and
J.L. Junkins, Chapman & Hall/CRC, Boca Raton, FL, 2004.
Review of Statistics
Random Variables
Gaussian Processes
Covariance and Correlation Function
Maximum Likelihood
Least Squares Estimation
Linear Batch Estimation
Linear Sequential Estimation
Nonlinear Estimation
Examples
Vehicle Attitude Determination
GPS Navigation
State Estimation
Review of State-Space Systems
Response to Gaussian Inputs
Linear Kalman Filter
Neighboring-Optimal Linear Estimator
Extended Kalman Filter for Nonlinear Systems
Examples
Position and Velocity Tracking
Review of Attitude Dynamics
Attitude Estimation Using Dynamics
Bias Estimation and Calibration of Gyros
Advanced Topics
Covariance Decompositions
Smoothing Algorithms
