Aerial target spatial-spectral discrimination for imaging spectrometer based on the acousto-optic tunable filter

Area of Science:

• Optics and Photonics
• Remote Sensing
• Signal Processing

Background:

• Jamming poses a significant challenge for aerial target identification systems.
• Traditional methods struggle to effectively discriminate targets from jamming signals.
• A need exists for advanced imaging and discrimination techniques for aerial surveillance.

Purpose of the Study:

• To propose an acousto-optic tunable filter (AOTF)-based imaging spectrometer system.
• To develop a spatial-spectral discrimination method to overcome jamming.
• To enable fast decision-making for aerial target identification under jamming conditions.

Main Methods:

• An AOTF-based imaging spectrometer capable of staring imaging and electronic tunability was developed.
• A spatial-spectral discrimination method was designed to leverage unique target signatures.
• Kalman filtering was employed to predict target spectral brightness and update target state estimation.
• Synthetic spatial-spectral information was used for final target state updates.

Main Results:

• The proposed AOTF system provides spatial location and distinguishable spectral features.
• Kalman filtering effectively predicted spectral brightness for frame-based AOTF operation.
• The spatial-spectral discrimination method demonstrated superior performance against jamming.
• The developed method is more targeted in solving jamming problems compared to traditional energy discrimination.

Conclusions:

• The AOTF-based imaging spectrometer and spatial-spectral discrimination method effectively address jamming issues in aerial target identification.
• The system's ability to combine spatial and spectral information enables robust and rapid target detection.
• This approach offers a significant advancement over traditional methods for aerial surveillance in complex environments.