Master’s in Land ISR and Multi-Sensor Fusion Engineering (Ethical/Legal)
Online master's programme of 1,900 hours in land ISR and multi-sensor fusion engineering with an ethical and legal focus, structured in 12 modules covering electro-optical, radar and acoustic sensors, multi-sensor fusion, image and video processing, responsible AI, exploitation and the legal and ethical framework, with an assigned technical tutor.
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What you will be able to do
Select electro-optical, radar and acoustic sensors according to requirements.
Apply multi-sensor fusion and multi-target tracking techniques.
Develop image and video processing algorithms.
Assess the robustness and bias of artificial intelligence models.
Integrate sensors into land platforms.
Analyse the legal and ethical framework of surveillance.
Measure system performance through testing and ROC curves.
Who it's for
- Sensor engineers working with electro-optical, radar or acoustic systems.
- Data fusion engineers developing tracking and multi-sensor solutions.
- Computer vision engineers applying detection and tracking to surveillance.
- Geospatial analysts who exploit ISR information.
- Responsible AI specialists auditing high-risk systems.
- Surveillance systems integration engineers.
- Engineering or science graduates aiming to enter the defence and security sector.
What you'll work with
- Regulation (EU) 2016/679 (General Data Protection Regulation, GDPR)
- Regulation (EU) 2024/1689 (Artificial Intelligence Act)
- Directive (EU) 2016/680 (data protection in law enforcement)
- STANAG 4609 (NATO digital motion imagery standard)
- STANAG 4559 (NATO Standard ISR Library Interface)
- Additional Protocol I to the Geneva Conventions (protection of victims of international armed conflicts)
- IEC 62676 (video surveillance systems)
- Stone Soup
- OpenCV
- MATLAB Sensor Fusion and Tracking Toolbox
- QGIS
- PyTorch
12 modules · 1900 h
1.1The ISR concept and the information cycle1.2Information requirements and priorities1.3Differences between surveillance and reconnaissance1.4Land sensor platforms1.5Surveillance of borders and civil perimeters1.6Legal framework for information gathering1.7Data protection and fundamental rights1.8Human control and accountability1.9Ethics of surveillance1.10Case study: legal analysis of a perimeter surveillance system
2.1Radiometry and spectral bands2.2CCD, CMOS and microbolometer detectors2.3MWIR and LWIR thermal cameras2.4Johnson criteria and recognition range2.5Optics and stabilisation2.6Multispectral sensors2.7Radiometric calibration2.8Atmospheric conditions and turbulence2.9Performance modelling with NVThermIP2.10Practical exercise: calculating detection ranges for a thermal camera
3.1Radar principles and the radar equation3.2Doppler ground surveillance radar3.3Short-range FMCW radar3.4Ground clutter and CFAR detection3.5Tracking of moving targets3.6Ground-based synthetic aperture radar3.7Ground-penetrating radar3.8Performance and limitations3.9Radar-optical integration3.10Lab: Doppler processing with FMCW data
4.1Acoustic sensors and source localisation4.2Seismic and vibration sensors4.3Magnetic sensors4.4Unattended ground sensor networks4.5Node energy management4.6Sensor network communications4.7Fusion of low-cost sensors4.8Civil monitoring applications4.9Deployment and maintenance4.10Case study: sensor network for infrastructure protection
5.1JDL data fusion model5.2Signal-, feature- and decision-level fusion5.3Bayesian theory and Dempster-Shafer5.4Kalman filters for tracking5.5Data association: GNN, JPDA and MHT5.6Distributed track fusion5.7Managing uncertainty and conflict5.8Spatial and temporal registration5.9Fusion metrics: OSPA and GOSPA5.10Practical exercise: multi-target tracking with Stone Soup
6.1Image enhancement and restoration6.2Motion detection and background subtraction6.3Object detection with deep learning6.4Multi-object visual tracking6.5Visible and thermal image fusion6.6Super-resolution and stabilisation6.7Video compression and STANAG 4609 metadata6.8Edge processing and accelerators6.9Algorithm evaluation6.10Lab: visible-thermal fusion with OpenCV
7.1Bias in datasets7.2Explainability of detection models7.3Robustness against adversarial examples7.4Uncertainty quantification7.5Model validation and verification7.6The EU AI Act and high-risk systems7.7Human oversight of automated analysis7.8Auditing AI systems7.9Model and data documentation7.10Workshop: model card and bias audit
8.1Surveillance masts and towers8.2Sensor-equipped reconnaissance vehicles8.3UAVs and aerostats as platforms8.4Mechanical and electrical integration8.5Stabilisation and pointing8.6Thermal management and environmental protection8.7Power supply and energy autonomy8.8Platform communications8.9Field maintenance8.10Case study: sensor integration on a vehicle
9.1The PED exploitation process9.2Geospatial analysis with GIS9.3Metadata and catalogue management9.4Information products9.5Secure dissemination and sharing9.6Common operational picture9.7Archiving and chain of custody9.8Information quality9.9Feedback into the cycle9.10Practical exercise: product catalogue in QGIS
10.1International humanitarian law10.2Human rights and surveillance10.3General Data Protection Regulation10.4Directive (EU) 2016/680 on law enforcement10.5Video surveillance and national legislation10.6Dual use and export controls10.7Proportionality and necessity10.8Governance and independent oversight10.9Ethics committees10.10Case study: data protection impact assessment
11.1Test ranges and scenarios11.2Detection metrics: probability and false alarms11.3ROC curves and performance analysis11.4Environmental testing11.5Interoperability testing11.6Synthetic sensor simulation11.7Validation with users11.8Equipment certification11.9Lessons learned11.10Lab: ROC analysis of a detector
12.1Definition of the surveillance scenario12.2State-of-the-art review12.3Sensor selection12.4Fusion architecture12.5Implementation and simulation12.6Performance evaluation12.7Ethical and legal analysis12.8Conclusions and future work12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so you can combine it with your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Stone Soup, OpenCV, MATLAB Sensor Fusion and Tracking Toolbox, QGIS and PyTorch, in free, academic or evaluation versions. Testing is studied through real procedures for multi-target tracking with sensor fusion, evaluation of detectors using ROC curves and fusion of visible and thermal imagery. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: Regulation (EU) 2016/679 (GDPR), Regulation (EU) 2024/1689, Directive (EU) 2016/680, STANAG 4609, STANAG 4559, Additional Protocol I to the Geneva Conventions, IEC 62676.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- Internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Stone Soup, OpenCV, MATLAB Sensor Fusion and Tracking Toolbox, QGIS and PyTorch, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A university degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the programme software, and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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