Distributed Multi-Target Tracking in Autonomous Sensor Networks
Masterarbeit, Proseminar, Studienarbeit, Bachelorarbeit
The problem of tracking multiple targets at once is becoming increasingly important in many defense and civilian applications such as air and ground traffic control, harbor surveillance, maritime traffic control, or video communication and surveillance. Distributed sensor networks offer a desirable platform for multi-target tracking applications due to their low cost and ease of deployment, their lack of a single point of failure, as well as their inherent redundancy and fault-tolerance.
We investigate distributed multi-target tracking in networks that are autonomous in the sense that the sensor nodes communicate with their neighbors in order to collaboratively detect and track targets in the region of interest. In addition, all of the sensors are equipped with a signal processing unit, allowing them to form decisions without a fusion center, i.e., a central processing and decision unit. That way, the network can autonomously react to events such as the detection of an intruder without relying on a network operator. mobile sensor nodes would enable reactions such as target pursuit or escape.
Students participating in this project will learn about detection and estimation theory, adaptive filters and diffusion algorithms, particle filtering and the probability hypothesis density.