Objective:

To develop an imaging system that combines terahertz time-domain spectroscopy (THz-TDS) with deep learning for the identification of explosives and chemicals concealed under opaque coverings.

Key Findings:

• Achieved an average accuracy of 99.42% in blind tests for eight chemicals.
• Maintained 88.83% accuracy for detecting explosives hidden under paper.
• The system operates with a peak dynamic range of 96 dB and a detection bandwidth of 4.5 THz.

Interpretation:

The approach effectively addresses limitations of traditional terahertz sensing by focusing on individual pulse shapes, enhancing robustness against variations in sample conditions.

Limitations:

• Performance may vary under different operational conditions.
• Future improvements depend on faster terahertz detectors and larger training datasets.

Conclusion:

The developed system represents a significant advancement in stand-off, non-contact chemical imaging, leveraging terahertz radiation and deep learning for enhanced detection capabilities.