Estimation of Time-Varying Human Manual Control Behaviour in Preview Tracking Tasks Using a Dual Extended Kalman Filter

This research applied a Dual Extended Kalman Filter (DEKF) to time-varying human operator (HO) parameter estimation in preview tracking tasks. The preview time parameter was of particular interest, as the amount of preview can be highly variable in practical situations. The filter was centered around a linear cybernetic HO model with six...

Time-series analysis to estimate aquifer parameters, recharge, and changes in the groundwater regime

The objective of this thesis is twofold: to develop time series analysis methods for the estimation of aquifer parameters and recharge to be used in groundwater models and to develop time series analysis methods for the identification and quantification of a regime change.<br/>In Chapter 2, a pumping test is replaced by time series analysis of...

Jump Markov Nonlinear System Identification in Multi-Sensor Target Tracking: A Novel Approach for Multiple Model Joint Tracking and Behavior Classification

The detection of unusual behavior plays a crucial role in the prevention of illegal and harmful activities such as smuggling, piracy, arms trading, human trafficking and illegal immigration. Also for military applications, it is useful to detect anomalous behavior to provide an alert for potential threats, especially with the more recent...

Effects of Preview Time in Manual Tracking Tasks

In manual control tasks, preview of the target trajectory ahead is often limited by poor lighting, objects, or display edges. This paper investigates the effects of limited preview, or preview time, in manual tracking tasks with single- and double-integrator controlled element dynamics. A quasi-linear human controller model is used to predict...

Maximum Likelihood Estimation of Linear Time-Varying Pilot-Vehicle System Parameters

Finite-Sample Bias Propagation in Autoregressive Estimation With the Yule–Walker Method

The Yule-Walker (YW) method for autoregressive (AR) estimation uses lagged-product (LP) autocorrelation estimates to compute an AR parametric spectral model. The LP estimates only have a small triangular bias in the estimated autocorrelation function and are asymptotically unbiased. However, using them in finite samples with the YW method for AR...