Frenel Imaging provides a polarimetric LWIR drone detection system that enhances object differentiation by analyzing the polarization of thermal radiation. This technology improves the ability to distinguish drones from other objects, even in challenging conditions like fog and smoke, for short and mid-range surveillance applications.
Funding
Funding not disclosed
Founders
Product
Problem
Conventional thermal imaging struggles to differentiate between objects with similar thermal signatures, especially in cluttered environments or adverse weather conditions like fog and smoke. This limitation hinders accurate drone detection, as distinguishing between drones and other objects like birds, or identifying drones obscured by environmental factors, remains a significant challenge.
Solution
Frenel Imaging offers a polarimetric LWIR drone detection system designed for short and mid-range applications, enhancing object differentiation through the analysis of thermal radiation polarization. This technology utilizes polarization filters to measure the polarization state of emitted thermal radiation, providing data on material properties that complements temperature-based information. By leveraging polarization, the system can effectively distinguish between various object types, such as drones and birds, even when their thermal signatures are comparable. Furthermore, polarimetric thermal imaging maintains its efficacy in environments with high background noise, fog, or smoke, as the polarization state of thermal radiation is less affected by these conditions than intensity alone. This approach overcomes the limitations of conventional thermal imaging, enabling more reliable detection and identification in challenging operational scenarios.
Target Audience
The primary customers are providers of drone countermeasure solutions and security organizations requiring advanced drone detection capabilities for short to mid-range surveillance.
Features
- Polarimetric LWIR sensor array for enhanced thermal radiation analysis
- Polarization filters to measure the polarization state of emitted thermal radiation
- Algorithms for differentiating objects based on material properties and polarization signatures
- Improved performance in high background noise, fog, and smoke conditions
- Capability to distinguish between drones and other objects with similar thermal signatures
- Designed for short and mid-range drone detection applications