Many applications of unmanned systems require the acquisition and processing of data from a variety of sensors, e.g., radar, sonar, lidar, or video. Powerful algorithms for analyzing data from individual sensors are typically already available. However, it remains a challenge to merge information from multiple diverse types of sensors. Naively merging data from multiple sensors may often deteriorate the results in practice. Consequently, it is crucial to carefully design algorithms for data fusion. If done properly, the benefit of multiple diverse sensors can be fully exploited, leading to more accurate detection and tracking of targets.
We aim to develop efficient and scalable algorithms to consolidate data from multiple heterogeneous sensors. These algorithms will allow us to detect and track targets more accurately, as they make full use of the information available in the sensors at hand. The proposed algorithms are generic, in the sense that they can be applied to any kind of sensor signals; therefore, they are expected to find use in a wide range of applications.
More specifically, in this project we have the following aims:
• Algorithms for target detection using data from diverse sensors. The algorithms will be assessed in terms of specificity and sensitivity.
• Algorithms for tracking a single target using data from diverse sensors. The algorithms will be assessed in terms of tracking error (mean squared error), .
• Algorithms for tracking multiple targets using data from diverse sensors (TRL 6). The algorithms will be assessed in terms of tracking error (mean squared error) and association errors.
• Optimized and tested code and system, packaged into API. User document.
The research fellow will assist in conducting this research, writing journal publications, and preparing grant applications.
The candidate should have a PhD degree in Electrical Engineering, Industrial Engineering or Statistics
Required skills include:
• Signal processing
• Machine learning
• Data modelling
• Design of unmanned vehicles
Interested applicants may send his/her CV and supporting information to:
Asst Prof Justin Dauwels
School of Electrical & Electronic Engineering
Nanyang Technological University
50 Nanyang Avenue
E-mail Address for E-mailed Applications: JDAUWELS@ntu.edu.sg
Electronic submission of application is highly encouraged.
Only short-listed candidates will be notified for interview. Application closes when the positions are filled.