The Interacting Multiple Model (IMM) estimator is a suboptimal hybrid filter that has been
shown to be one of the most cost-effective hybrid state estimation schemes. The main …

This is the fifth part of a series of papers that provide a comprehensive survey of techniques
for tracking maneuvering targets without addressing the so-called measurement-origin …

Existing multiple-model (MM) estimation algorithms have a fixed structure, ie they use a fixed
set of models. An important fact that has been overlooked for a long time is how the …

Industrial implementation of model-based control methods, such as model predictive control,
is often complicated by the lack of knowledge about the disturbances entering the system. In …

Correct knowledge of noise statistics is essential for an estimator or controller to have
reliable performance. In practice, however, the noise statistics are unknown or not known …

Target tracking is a hybrid estimation problem involving both continuous and discrete
uncertainties [31]. In the prevailing approaches to target tracking, the modeling of the target …

A unique and comprehensive collection of submarine landslide data from different tectonic
environments in the North Atlantic, based on published literature and industry sources, is …

The interacting multiple model (IMM) algorithm has been shown to be one of the most cost-
effective estimation schemes for hybrid systems. Its performance, however, could only be …

Although bus passenger demand prediction has attracted increased attention during recent
years, limited research has been conducted in the context of short‐term passenger demand …

For pt. IV see ibid., vol. 35, no. 1, p. 242-254 (1999). A multiple-model (MM) estimator with a
variable structure, called likely-model set (LMS) algorithm, is presented, which is generally …