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A novel centroid dynamic programming track-before-detect algorithm accurately tracks moving targets with unknown speeds. This method, enhanced with variable steps, effectively handles high accelerations, achieving below 2% velocity extraction error.

Area of Science:

Signal Processing
Control Systems Engineering
Optical Engineering

Background:

Tracking moving targets with unknown speeds presents significant challenges.
Existing track-before-detect algorithms struggle with targets exhibiting high accelerations.

Purpose of the Study:

To propose a novel centroid dynamic programming track-before-detect algorithm for enhanced moving target tracking.
To improve the tracking accuracy for targets with unknown speeds and large accelerations.

Main Methods:

Developed a centroid dynamic programming track-before-detect algorithm.
Implemented an experimental tracking system using inertialess scanning with an optical phased array.
Innovated the algorithm by incorporating a variable step to manage target acceleration.

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Main Results:

Successfully established an experimental tracking system with a maximum signal-to-noise ratio of 9.97 dB.
Demonstrated accurate tracking of targets in various motion states.
Achieved effective trajectory tracking with velocity extraction errors below 2%.

Conclusions:

The proposed algorithm provides effective trajectory tracking for moving targets with unknown speeds.
The variable step enhancement significantly improves the tracking of targets with large accelerations.
Numerical and experimental validations confirm the algorithm's accuracy and effectiveness.