Infrared small target energy distribution model for subpixel motion.

Area of Science:

• Optics and Photonics
• Infrared Technology
• Signal Processing

Background:

• Dim small target detection is crucial for infrared (IR) searching and tracking systems.
• Current IR detection methods often fail due to inaccurate target energy distribution models.
• Subpixel motion significantly impacts target energy distribution, complicating detection.

Purpose of the Study:

• To propose a new Infrared Small Target Energy Distribution (NSTED) model that accounts for subpixel motion.
• To improve the accuracy of energy distribution modeling for dim small targets in IR systems.
• To enhance the performance of IR searching and tracking systems.

Main Methods:

• Developed a novel NSTED model considering subpixel motion effects on energy distribution.
• Simulated target energy distribution using the proposed NSTED model.
• Compared NSTED model performance against Gaussian and hyperbolic secant models.

Main Results:

• The NSTED model accurately describes energy distribution variations for subpixel moving targets.
• Simulations show NSTED yields a superior output signal-to-noise ratio (SNR) compared to existing models.
• NSTED improved output SNR by at least 17.9% over Gaussian and 20.7% over hyperbolic secant models.

Conclusions:

• The proposed NSTED model offers a significant advancement in accurately modeling IR small target energy distribution.
• This model enhances the effectiveness of IR detection algorithms, particularly for targets exhibiting subpixel motion.
• The improved SNR achieved by NSTED is vital for reliable dim small target detection in challenging IR scenarios.