Multiple target information fusion matching algorithm based on a line laser and a single plane array camera

Area of Science:

• Optics and Photonics
• Weapon Systems Testing
• Computer Vision

Background:

• Existing optical testing methods struggle with simultaneous, spatially overlapping targets in dynamic weapon range scenarios.
• Accurate recognition and matching of multiple targets' spatial positions are critical for performance evaluation.
• Current limitations hinder comprehensive analysis of dynamic weapon system performance.

Purpose of the Study:

• To develop a new optical testing method for accurately recognizing and matching spatial positions of multiple, simultaneous targets.
• To establish a robust multiparameter calculation and recognition model for dynamic multitarget scenarios.
• To overcome occlusion and overlapping issues in optical testing of weapon ranges.

Main Methods:

• Integration of a line laser with a plane array camera for enhanced spatial detection.
• Development of a multiparameter calculation model based on optical axis intersection with laser screens.
• Implementation of a recognition model using time-space information constraints and fuzzy information fusion.
• Analysis of data fusion algorithms and solution methods for key correlation parameters.

Main Results:

• The proposed method effectively solves the spatial matching problem for occluded and overlapping multitargets.
• Experimental data collected at different target velocities validated the method's efficacy.
• The testing error was found to meet the required measurement standards.

Conclusions:

• The combined line laser and plane array camera approach provides a significant advancement in dynamic multitarget optical testing.
• This method enhances the accuracy and reliability of weapon range testing, particularly in complex scenarios.
• The developed models and algorithms offer a practical solution for real-world multitarget identification challenges.