The Kalman filter is the minimum-variance state estimator for linear dynamic systems with
Gaussian noise. Even if the noise is non-Gaussian, the Kalman filter is the best linear …

Humans are able to intuitively exploit the shape of an object and environmental constraints
to achieve stable grasps and perform dexterous manipulations. In doing that, a vast range of …

This article is concerned with the outlier-resistant state estimation problem for industrial pipe
networks (PNs). PN signals, eg, pressure and temperature, are modeled as low-pass time …

To improve smartphone GNSS positioning performance using extra inequality information,
an inequality constraint method was introduced and verified in this study. Firstly, the …

In transportation networks, vehicle motions are usually subject to the constraints arising from
the roads, preset sea-routes, or preset flight routes. Taking advantage of prior known …

Abstract The Global Positioning System (GPS) and an Inertial Navigation System (INS) are
two basic navigation systems. Due to their complementary characters in many aspects, a …

This paper develops Bayesian weighted instrumental variable (WIV) estimators under
equality and inequality speed constraints for the three-dimensional (3-D) bearings-only …

In this paper a global localization problem of a robot moving in a known environment is
considered. The environment is equipped with a relatively sparse set of passive RFID …

This paper considers nonlinear state estimation subject to inequality constraints in the form
of linear and linear-matrix inequalities. Rewriting the standard maximum likelihood objective …

The traditional design of tracking loop in global positioning system (GPS), known as the
combination of phase-locked loop and delay-locked loop, is fragile under complex …