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Afstudeeropdracht - WO - Toegepaste Wiskunde, Elektrotechniek, Natuurkunde. Improvement of Multiple Hypotheses Tracking Algorithm

ID de l'offre R0064541 Date de publication 09/08/2019 Lieu: Hengelo, Overijssel, Netherlands
Full time, Stage
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Afstudeeropdracht - WO

Studierichting(en): Toegepaste Wiskunde, Elektrotechniek, Natuurkunde

Titel van de opdracht: Improvement of Multiple Hypotheses Tracking Algorithm

About us

With 80.000 talents working in 68 countries, we are one of the biggest high-tech employers in the field of safety and security. In the Netherlands, where 2000 employees are based, we are located in four cities: Huizen, Delft, Eindhoven and Hengelo (HQ). Together with an extensive ecosystem of knowledge partners, customers and suppliers, we work on radars for naval vessels, cyber security solutions, transportation systems, communication equipment for land forces, cryogenic cooling solutions, research & development for radar tech (in collaboration with TU Delft).

The cluster System Engineering is, among others, responsible for the development of signal and data processing techniques for radar and electro-optical sensors for naval applications.

About the assignment

Current radar systems gather a lot of information of the space around the system. These systems become more and more sensitive, which means that more targets are detected and that filtering becomes even more important. Our tracking algorithm, based on Extended Kalman filtering, provides the user tracks of targets that are seen by the radar.

In addition, this increasing number of detections leads to a more complex data association problem that can be solved using an assignment algorithm known from literature. A technique known as Multiple Hypotheses Tracking (MHT) provides a method to consider all possible assignments and decides which possibility is the best. However, mainly because of load reasons, MHT cannot consider the full decision tree that is made from all existing plots.

Over time, improvements of MHT have been developed. These extensions of MHT enable the tracking algorithm to maintain more hypotheses when needed in order to make the correct assignments. Recent experiences have shown that simply allowing more hypotheses does not always provide the correct outcome.

In this assignment you will study alternatives for making MHT smarter in order to handle a higher plot density.

Based on this investigation, an algorithm will be developed, implemented and evaluated such that the alternatives can be analyzed.


Assignment Algorithms, Operations Research, (Matlab) programming

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