Short Description: This research project aims to design and optimize a dedicated satellite constellation for real-time image streaming from space, focusing on advanced communication architectures and operational strategies. It emphasizes system-level considerations, including the use of optical inter-satellite links (OISL) for enhancing data throughput and minimizing latency. Applications will be considered on a first-come-first-served basis. This fully-funded doctoral project is expected to start in October 2025. 

Context (Joint PhD by TéSA, CNES, TAS; Co-led supervision) :

The demand for high-quality, real-time satellite imagery for various industries (e.g., environmental monitoring, agriculture, defense) requires innovative system-level approaches to overcome current satellite communication limitations. Traditional "store and forward" methods pose challenges in latency, data throughput, and operational efficiency.

A new approach involving a dedicated satellite constellation for continuous, high-bandwidth image streaming can address these challenges. This research will explore the use of LEO and MEO satellites with optical inter-satellite links (OISL) to enable efficient and low-latency data transmission.

Description:

The thesis will primarily focus on the system-level design, simulation, and optimization of a satellite constellation dedicated to image streaming. The key areas of investigation include:

Constellation Architecture Design:

Define the optimal number of satellites, orbital characteristics (LEO vs MEO), and configuration (e.g., 2x12 LEO with contrarotating orbital planes or 3x6 MEO).

Analyze trade-offs between LEO and MEO constellations in terms of coverage, latency, and data throughput.

Communication Technology:

Investigate the integration of optical inter-satellite links (OISL) to enhance data throughput and reduce reliance on onboard storage.

Determine the effectiveness of unidirectional (TMI) vs. bidirectional (TMTC) communication systems for the proposed constellation.

Operational Strategies:

Develop strategies for real-time, continuous connectivity between satellites and ground stations.

Explore advanced routing algorithms for dynamic optimization of data transmission to minimize latency while maximizing throughput.

Impact Analysis:

Compare the system's performance with existing solutions like IRIS2, focusing on technical feasibility, cost-effectiveness, and scalability.

Evaluate the potential environmental impact of deploying a large satellite constellation and propose mitigation strategies.

Technical Constraints:

Latency: Develop strategies to optimize the trade-offs between latency and throughput, particularly in LEO and MEO configurations.

Bandwidth and Compression: Ensure data compression techniques do not compromise image quality while managing storage requirements.

Communication Technology: Assess the feasibility and integration challenges of optical inter-satellite links within existing ground-based infrastructures.

Potential Technological Challenges:

Resilient Communication Links: Address challenges of maintaining robust communication in a dynamic space environment with intermittent satellite availability.

OISL Feasibility: Explore the practical viability, cost, and complexity of replacing RF technology with OISL systems.

Scalability: Assess the design's scalability for future demands of higher-resolution images and increased data volumes.

Final Objective:

The thesis aims to develop an optimized, system-level architecture for image streaming from space, ensuring low-latency, high-throughput communication. This work will advance space-based imaging technologies and provide real-time data for various applications.

Approach:

The research will involve designing and simulating a satellite constellation using advanced modeling tools. The candidate will also test communication protocols and work closely with CNES and TAS to validate the proposed solutions for real-world deployment.

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For more Information about the topics and the co-financial partner (found by the lab !); 

contact Directeur de thèse - riadh.dhaou@toulouse-inp.fr

Then, prepare a resume, a recent transcript and a reference letter from your M2 supervisor/ engineering school director and you will be ready to apply online  before March 14th, 2025 Midnight Paris time !