Predicting and Assessing Collateral Damage in Operational Scenarios for LIDAR- and Laser-based C-sUAS Systems

The use of Counter-small Unmanned Aircraft Systems (C-sUAS) systems may induce collateral damage during operation. This study examines the potential sources of collateral damage throughout the entire kill chain, from active sensors to effectors in the optronics domain, and includes consideration of the drone itself and its payload. The analysis combines multiple factors related to the environment, sUAS targets, sensors, and effectors in a parametric framework, facilitating easy scenario configuration and repeatability. Qualitative risk assessments are performed using user-defined collateral damage risk matrices, and these are integrated with specific models to generate quantitative results, thereby enhancing decision-making and improving the understanding of collateral damage across different operational scenarios. Simulations are conducted to illustrate the prediction and assessment of the impact of collateral damage across different scenarios, specifically with a LIDAR-based system for detection and tracking, and a High Energy Laser (HEL) as the neutralisation effector.