PhD projects
Title: Detection and identification of objects in advanced radar images
Student: Paul Jacques Connetable
Funding: DTU
Description: The aim of the project is to study techniques for the detection and identification of man-made objects, such as vehicles or buildings, using polarimetric SAR images. The core of the project consists in finding parameters and data behaviors which highlight the sought objects as opposed to natural backgrounds, as well as ways this information can help identifying them. The research also includes investigation and development of the statistical tools which can be used for the detection and classification processes, particularly statistical hypothesis testing, image analysis, machine learning, and artificial neural networks, and the comparison of their performance.
Title: MIMO radar for drone detection
Student: Lasse Lehmann
Funding: Terma industrial PhD
Description: Airborne drones pose tremendous challenge to common surveillance systems such as radars. Multiple-input multiple-output (MIMO) radar has been suggested as a suitable technology to enable wide-area surveillance, capturing small targets in high-resolution with the ability to track several targets at any given time. This is performed without mechanically rotating the antenna, instead relying on digital signal processing to scan the covered search-volume. In my project I investigate algorithms and signal processing to enable optimal MIMO radar operation, resolving targets at fine angular resolution and exploiting micro-Doppler signatures of drones to affirm detection and perform classification.
Title: MIMO radar Systems and Algorithms
Student: Ricard Llado Grove
Funding: Thomas B. Thriges Fond
Description: Multiple-Input-Multiple-Output (MIMO) radar builds upon the principle of superposition, where several transmitters simultaneously radiate independent waveforms. Separating the waveforms in each receiver and forming a virtual array from the combinations of transmit and receive channels, provides a higher diversity than that of the conventional phased array radar. On the other hand, imperfections of multichannel systems will degrade the performance of such systems drastically. Hence, this project will mainly focus on the impact of imperfections for MIMO radar systems, and not least the calibration of the effects. Furthermore, the design of suitable waveforms in terms of application and scalability will be investigated along direction-of-arrival algorithms.
Title: Artic sea ice climate data records and the consistency between SST and sea ice satellite products
Student: Pia Nielsen-Englyst
Funding: DMI/DTU
Description: Accurate global sea surface temperature (SST) observations are important for climate monitoring, understanding of air–sea interactions, and numerical weather prediction. SST has been retrieved from infrared (IR) satellite observations since 1981, but these are limited by clouds, and biased from aerosols. Passive microwave (PMW) observations are not prevented by non-precipitating clouds and the bias by aerosols is small. The aim of the PhD is to improve the algorithms to retrieve SST from PMW satellite observations, including an assessment of the impact of using different channel selections in the retrieval algorithms, and finally to assess how SST observations can be integrated with sea ice parameters in a multi-sensor gap free SST and sea ice product for the Arctic.
Title: Synthetic Aperture Radar TOPS-mode Interferometry for Ice Velocity Retrieval
Student: Jonas Kvist Andersen
Funding: DTU
Description: The project aims to improve polar ice velocity retrievals from space-borne Synthetic Aperture Radar, specifically the EU Copernicus Sentinel-1 satellites. Currently, only amplitude-based velocity measurements are being routinely generated. Interferometric (i.e. phase-based) velocity retrievals are of significantly higher resolution and accuracy. However, due to complications introduced by the Sentinel-1 TOPS acquisition mode, interferometry is not straightforward to apply in scenes with motion in the along-track direction. This project seeks to solve the challenges of TOPS interferometry on ice sheets. Additionally, methods of combining amplitude- and phase-based measurements in a highly automated fashion will be investigated.