Improving the estimation of satellite altimetric parameters (2020/21)

A satellite altimeter is a nadir viewing radar that emits regular pulses and records the travel time, the magnitude and the shape of each return signal after reflection on the Earth's surface. This technology is used to measure the effects on the oceanic surface of physical phenomena such as global warming, earthquakes, allowing a better understanding of their evolution. A great challenge is how to improve the estimation of physical parameters such as the sea-wave-height (SWH), the wind speed (Pu) and the satellite-surface range (τ) from the measured signals in order to extract better information. This is the core of this project whose objectives are:
- Review, implement and compare of existing methods to improve the estimation of altimetric parameters
- Explore modelling and/or denoising of altimetric signal using neural network architectures with Matlab or Python
- Accelerate existing Matlab codes by converting them to the C language, and evaluate performance

This is a computational based project. No data collection is required as data is already available. The project might involve collaborations with the supervisor's French industrial partners (Collecte Localisation Satellite-CLS or CNES). The interested students are invited to contact the supervisor to discuss their interests and adapt the project accordingly (if possible).

1. A. Halimi, C. Mailhes, J.-Y. Tourneret and H. Snoussi, "Bayesian Estimation of Smooth Altimetric Parameters: Application to Conventional and Delay/Doppler Altimetry," IEEE Trans. Geoscience and Remote Sensing, vol. 54, no. 4, 2015
2. A. Halimi, G. Buller, S. McLaughlin, and P. Honeine,"Denoising Smooth Signals Using a Bayesian Approach: Application to Altimetry," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 4, April 2017.

Supervisor name: 
Abderrahim Halimi
Supervisor and Deputy email addresses: