Surface Vessel Detection Using GPS-Reflectometry

Supervisor Name/s: 
Dr Joon Wayn Cheong
Research field/s: 
Satellite Systems, Earth Observation, Space-based Systems

Intelligence, Surveillance, Reconnaissance (ISR), Electronic Warfare (EW), Space and Cyber” are the highest priority research and innovation streams for both the Defence Innovation Hub and the Next Generation Technology Fund in 2017/2018. High altitude sensor systems (HASS) represent an importance source of ISR. UNSW is developing a GPS-Reflectometry sensor (GPS-R Sensor) payload under DMTC funding that will permit passive and autonomous sea-state monitoring to occur using high-altitude UAVs, aircraft, and cubesat platforms using reflected GNSS/GPS signals. Application of this sensor to ISR applications will allow provide leverage of this existing funding.

The study aims to determine the feasibility of using GNSS-Reflectometry techniques to passively detect ocean vessels using the UNSW GPS-R Sensor (currently in development) when deployed on a high-altitude platform. The research will test the performance of such a system by applying newly developed STARE processing algorithms to the problem of target detection. The project will characterise the performance of such a system and make recommendations on how such a system can be improved. It will employ Kea GPS hardware that has been flight proven on the DST Buccaneer Risk Mitigation cubesat mission.

The methodology applied could be testing of the GPS-R Sensor may be carried out using a variety of airborne platforms. Flights carried out over the ocean will be tasked with searching for ocean vessels and positioning the sensor to record signals from targets that are known to be present. Postprocessing can then be employed to determine whether those targets were detected. Simulation software would be created to generate a list of possible GPS-R reflection modes given a target position (assuming a simplified vessel structure), a particular GPS constellation state, a GPS-R Sensor position and a given time instant.

As for outcomes of this projects, student will be able to resolve the following questions: whether ocean vessels can be detected using such technology, and if so, what are the limits on such detections; whether detections could be improved by making design changes to the system; whether autonomous detection of targets and appropriate display of that information to an operator would be required. Finally, blending detections with other sensors (such as optical or multispectral images) could be considered.