Kalman Filter (KF) that is also known as linear quadratic estimation filter estimates current
states of a system through time as recursive using input measurements in mathematical …

This survey of model-based fault diagnosis focuses on those methods that are applicable to
aerospace systems. To highlight the characteristics of aerospace models, generic non-linear …

Vehicle trajectory prediction helps automated vehicles and advanced driver-assistance
systems have a better understanding of traffic environment and perform tasks such as …

Lithium-ion batteries have become an integral part of our lives, and it is important to find a
reliable and accurate long-term prognostic scheme to supervise the performance …

We tackle the problem of exploiting Radar for perception in the context of self-driving as
Radar provides complementary information to other sensors such as LiDAR or cameras in …

For an intelligent transportation system, multiple object tracking (MOT) is more challenging
from the traditional static surveillance camera to mobile devices of the Internet of Things …

Most newcomers to the field of linear stochastic estimation go through a difficult process in
understanding and applying the theory. This book minimizes the process while introducing …

The prominence of finite mixture modelling is greater than ever. Many important statistical
topics like clustering data, outlier treatment, or dealing with unobserved heterogeneity …

In this self-contained survey/review paper, we systematically investigate the roots of
Bayesian filtering as well as its rich leaves in the literature. Stochastic filtering theory is …

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 …