Damage effect evaluation of CCD irradiated by laser based on multi-source information fusion

Area of Science:

• Optical Engineering
• Materials Science
• Sensor Technology

Background:

• Charge-coupled devices (CCDs) are susceptible to laser-induced damage.
• Accurate and timely assessment of CCD damage is crucial for operational reliability in high-energy environments.
• Existing damage assessment methods may lack comprehensive data integration.

Purpose of the Study:

• To develop and validate an advanced approach for assessing laser-induced damage in CCDs.
• To leverage multi-source and multi-feature information fusion for improved damage detection accuracy.
• To enable online and real-time evaluation of CCD damage states.

Main Methods:

• Established an experimental system to simulate laser damage on CCDs.
• Collected diverse data: 'cat's eye' effect echo, plasma flash, and surface images.
• Utilized a probabilistic neural network (PNN) for multi-source and multi-feature data fusion.

Main Results:

• Multi-feature analysis within single sources improved accuracy over single-feature evaluations.
• Combined data fusion reduced error rates to 0.85% from individual source errors (e.g., 7.17% for surface images).
• Evaluation time achieved was under 60 milliseconds.

Conclusions:

• The multi-source, multi-feature fusion method is highly effective for online, real-time CCD damage evaluation.
• This approach significantly enhances the operational reliability and safety of devices exposed to high-energy environments.
• The PNN-based fusion technique offers a robust solution for advanced sensor damage assessment.