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    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.