Detection of target trajectories using the Hough transform

Area of Science:

• Computer Vision
• Aerospace Engineering
• Signal Processing

Background:

• Accurate detection and tracking of multiple missile trajectories are crucial for defense systems.
• Traditional trajectory detection methods struggle with noise and missing data points.

Purpose of the Study:

• To adapt advanced Hough transform techniques for robust multitarget missile trajectory detection.
• To evaluate the performance of these techniques under realistic noisy and incomplete data conditions.

Main Methods:

• Application of recently developed Hough transform algorithms for curved object detection.
• Simulated multitarget missile trajectories with varying levels of noise and data gaps were used.
• Performance metrics focused on detection accuracy and trajectory reconstruction fidelity.

Main Results:

• The Hough transform method demonstrated significant capability in detecting curved missile trajectories.
• Robust detection was achieved even in the presence of substantial noise and missing trajectory data.
• The technique showed promise for distinguishing and tracking multiple overlapping trajectories.

Conclusions:

• Hough transform techniques offer a viable and effective solution for multitarget missile trajectory detection.
• The adaptability of these methods to noisy and incomplete data enhances their practical applicability in defense scenarios.
• Further research can refine these techniques for real-time operational deployment.