This paper presents an indoor localization system that is based on the fusion of two complementary technologies: 1) Inertial integration and 2) RFID-based trilateration. The Inertial subsystem uses an IMU (Inertial Measurement Unit) mounted on the foot of the person. The IMU approach generates a very accurate estimate of the user’s trajectory shape (limited by the drift in yaw). However, being ...

One of the most widespread applications of the Global Positioning System (GPS) is vehicular navigation. Improving the navigation accuracy continues to be a focus of research, commonly answered by the use of additional sensors. A sensor commonly fused with GPS is the inertial measurement unit (IMU). Due to the fact that the requirements of commercial systems are low cost, small size, and power c...

Low cost inertial sensors are often promoted as the solution to indoor navigation. However, in reality, the quality of the measurements is poor, and as a result, the sensors can only be used to navigate for a few seconds at a time before the drift becomes too large to be useful. Therefore, it is necessary to regularly update the sensors with measurements from external systems such as GPS or oth...

The poses of base station antennas play an important role in cellular network optimization. Existing methods of pose estimation are based on physical measurements performed either by tower climbers or using additional sensors attached to antennas. In this paper, we present a novel non-contact method of antenna pose measurement based on multi-view images of the antenna and inertial measurement u...

Three dimension data are in great demand for the various applications such as 3D GIS, navigation, digital archive, simulation, computer games, and so on. In order to represent space in details, it is indispensable to acquire 3D shape and texture together. However, there still lacks a reliable, quick, and handy method of acquiring three dimension data at higher resolution. In this research, we p...

In this pilot study fusion motion capture (FMC) has been used to capture 3-D kinetics and kinematics of alpine ski racing. The new technology has overcome the technological difficulties associated with athlete performance monitoring in an alpine environment. FMC is a general term to describe motion capture when several different streams of data are fused to measure athlete motion. In this artic...

State estimation is the most critical capability for MAV (Micro-Aerial Vehicle) localization, autonomous obstacle avoidance, robust flight control and 3D environmental mapping. There are three main challenges for MAV state estimation: (1) it can deal with aggressive 6 DOF (Degree Of Freedom) motion; (2) it should be robust to intermittent GPS (Global Positioning System) (even GPS-denied) situat...

This research tested different ways of tuning the process noise covariance matrix of a GPS/IMU extended Kalman filter. This Kalman filter was developed for a retrofit robot driver. Because of the constraints of this application, the Kalman filter had no process model for the outputs of the robot’s controller. In this situation, a significant proportion of the process noise would be caused by th...