VAILLAUD Hugo Nicolas

PhD student at Sorbonne University
Team : RO
https://lip6.fr/Hugo-Nicolas.Vaillaud

Supervision : Claire HANEN

Co-supervision : Emmanuel HYON

Algorithms for the Search of a Moving Air Target with a Radar Onboard an Airborne Platform

In the current context of aerial missions, pilots and operators aboard airborne platforms are facing increasingly complex tactical situations. Apart from managing the aircraft's trajectory, they must also use multiple sensors to complete various essential tasks for a comprehensive representation of the tactical situation. These tasks range from surveillance and tracking of targets to target identification and fire control. They must also deal with new, harder-to-detect targets that are networked and capable of more efficient coordination. During high-intensity missions, performing all these tasks simultaneously can be challenging due to the need for complex decision-making within very short timeframes. The work presented in this manuscript is driven by the need to enhance and evaluate air-to-air surveillance planning with an onboard radar. A significant portion of this thesis is dedicated to adapting a general target search model and the Forward And Backward (FAB) algorithm for the specific task of air-to-air surveillance using radar. New algorithms are also introduced. The study extends to the gradual integration of radar technology features into the target search model. For instance, research efforts are allocated to observation cones to represent radar beam shape. Initially, disjoint observation cones are considered, and the model is further enriched by incorporating overlapping observation cones to enhance the quality of computed plans. The detection model is also progressively refined to accurately reflect radar operation.
A robust framework for evaluating radar pointing strategies is proposed. The algorithm evaluation tool allows for both the comparison of different algorithms based on clearly defined criteria and the measurement of their optimality against theoretical performance bounds. Through this experimental framework, we validate the superiority of the proposed algorithms over a heuristic from the open literature used in the industry, thus providing a new benchmark in the field of air-to-air surveillance. Through experiments, the effectiveness of these algorithms is confirmed, particularly by exploring the trade-offs between solution quality and computation time to accommodate real-time execution constraints.
Ultimately, this research represents a step forward in optimizing air-to-air surveillance with onboard radar. The proposed algorithms demonstrate superior performance compared to existing heuristics, and a robust evaluation framework is introduced for systematic comparison. These contributions serve as the basis for future studies in more complex scenarios, envisioning the use of multiple onboard sensors across various platforms, coordinated to perform diverse tasks simultaneously. This work aligns with a broader objective of developing tools to reduce the cognitive load on operators, allowing them to focus on the critical operational aspects of their missions.

Defence : 12/15/2023

Jury members :

M. André ROSSI Université Paris Dauphine - PSL [Rapporteur]
Mme Hind CASTEL Télécom SudParis [Rapporteur]
Mme Claire HANEN Sorbonne Université et Université Paris Nanterre
M. Emmanuel HYON Sorbonne Université et Université Paris Nanterre
Mme Alix MUNIER-KORDON Sorbonne Université
M. Ludovic GRIVAULT Thales DMS
M. Cyrille ENDERLI Thales DMS

Departure date : 11/30/2023

2022-2023 Publications