Research area leader: Associate Prof. Henk Wymeersch
Our researchers in Positioning and sensor fusion are listed below.
About the research area Positioning and sensor fusion
Positioning is useful for navigation and transportation, and currently represents a multi-billion dollar worldwide industry. Many of our investigations are motivated by the needs in active safety systems, indoor-outdoor navigation for pedestrians and ground target tracking using airborne sensors.
A classical example of positioning is target tracking using detections from a radar sensor (dealing with relative positions). Though the radar is still important, many modern systems rely more on GPS sensors, map data, cameras, laser scanners and the fusion of all the available information.
The objective of indoor navigation is to enable tracking of people and assets beyond the environments with GPS coverage. Considering that people spend up to 90% of their time indoors, indoor navigation is expected to have a significant impact on our daily lives. GPS signals are too weak to penetrate ceilings, walls, and tunnels, so that complementary technologies need to be considered. Our research involves the study of such technologies, with a focus on peer-to-peer computing.
Active safety functions will intervene in dangerous situations, e.g., by warning or braking. Due to lack of reliable information at an early stage, most of today’s systems do not act until an accident is unavoidable which means that accidents are not prevented, only mitigated. One of the goals with our research is to enable earlier interventions by fusing data from several sensors in order to significantly improve the positioning and the long-term predictions.
The goal of this project is to understand how the cooperative nature of future wireless networks can be leveraged to perform timekeeping, positioning, communication, and decision making, so as to obtain orders of magnitude performance improvements compared to current architectures...
The project is focusing on jointly developing technologies to reduce accident risks for both passenger cars and commercial vehicles and particularly addressing the situations at which today’s active safety systems are not yet sufficient...
In this project, we aim at designing robust and low complex algorithms for both cooperative and noncooperative positioning. We mainly focus on distance and received signal strength measurements and derive different algorithms...