Recognition of 3d objects in a monostatic laser location system via intelligent analysis of pulsed reflectance profiles

Labunets, L.V., Borzov, A.B., Akhmetov, I.M.

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For Russian citation (Opticheskii Zhurnal):

Лабунец Л.В., Борзов А.Б., Ахметов И.М. Распознавание 3D объектов в однопозиционной системе лазерной локации методами интеллектуального анализа импульсных отражательных характеристик // Оптический журнал. 2022. Т. 89. № 4. С. 40–51. http://doi.org/ 10.17586/1023-5086-2022-89-04-40-51 Labunets L.V., Borzov AB, Akhmetov I.M.Recognition of 3d objects in a monostatic laser location system via intelligent analysis of pulsed reflectance profiles [in Russian] // Opticheskii Zhurnal. 2022. V.89. № 4. P. 40-51. http://doi.org/10.17586/1023-5086-2022-89-04-40-51

For citation (Journal of Optical Technology):

L. V. Labunets, A. B. Borzov, and I. M. Akhmetov, "Recognition of 3D objects in a monostatic laser location system via intelligent analysis of pulsed reflectance profiles," Journal of Optical Technology. 89(4), 217-224 (2022). https://doi.org/10.1364/JOT.89.000217

Abstract:

Subject of study. A physics-based expert model of initial features for the recognition of anthropogenic 3D objects in a monostatic laser location system is proposed. Method. The model is based on an intelligent analysis of data obtained using digital simulation modeling of temporal profiles of pulsed reflectance profiles of the object. Informative features are formed using the method of principal components. Main results. A cluster structure in the space of principal features is demonstrated and investigated. The parameters of several algorithms for the clustering and classification of 3D objects are identified using machine learning methods and their quality is tested in an informative space. Practical significance. The stages of solving the clustering and classification tasks for anthropogenic objects by a monostatic laser location system are described in chronological order.

Keywords:

simulation digital modeling, impulse effective scattering area of 3D object, informative features, clustering and classification algorithms, machine learning methods

OCIS codes: 070.5010

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