An application of the correlation method for moving object identification using velocimeter data

• Date: 2026
• Main Authors: Манько, Д. Ю., Беляк, Є. В., Косяк, І. В.
• Format: Article
• Language: Ukrainian
• Published: Інститут проблем реєстрації інформації НАН України 2026
• Subjects: correlation method; velocimeter; moving object identification; seismic portrait; signal differentiation; cross-correlation
• Online Access: https://drsp.ipri.kiev.ua/article/view/358585
• Journal Title: Data Recording, Storage & Processing

The study investigates the applicability of the correlation method for the identification of moving objects using velocimetric seismic measurements in tasks of engineering monitoring and detection of transport-related events. In practical monitoring systems, seismic “portraits” of characteristic events are often formed using displacement signals, whereas field measurements are commonly obtained from velocimeters that record ground velocity. This difference in physical representation may reduce the correlation agreement between the reference signal and measured data due to spectral distortions introduced by differentiation. The work analyzes the theoretical relationship between the cross-correlation functions of displacement and velocity signals under the assumptions of bounded and ergodic processes and demonstrates that correlation portraits can be consistently transferred between these signal representations when appropriate preprocessing is applied. A discrete procedure for constructing a “virtual velocimeter” using finite-difference differentiation is proposed, enabling the transformation of displacement signals into velocity form suitable for streaming data processing. On this basis, a correlation identification algorithm designed for continuous monitoring is developed. The algorithm implements a template-matching scheme in which a reference seismic portrait of a characteristic event is sequentially compared with fragments of the incoming data stream using normalized cross-correlation. Experimental verification was carried out using seismic records of freight train passages, which represent a typical example of technogenic vibration sources relevant for infrastructure monitoring. A reference seismic portrait of the train passage was extracted from measured data and used as a template to search for similar events in a long-duration seismic record. The experiments included two processing regimes: correlation analysis based on displacement signals and correlation analysis using velocity signals obtained by discrete differentiation. The results demonstrate that the correlation peaks corresponding to train passages remain clearly identifiable in both representations of the signal, confirming the robustness of the proposed approach. At the same time, differentiation was shown to modify the spectral balance of the signal and to increase sensitivity to high-frequency noise, which may affect the sharpness and stability of correlation peaks. The study therefore proposes several practical measures for improving detection stability, including spectral band selection, consistent preprocessing of template and data signals, detrending procedures, smoothing before differentiation, and adaptive thresholding of correlation peaks. The obtained results confirm the temporal stability of seismic portraits and demonstrate the feasibility of transferring correlation templates between different physical signal representations and sensor types. The proposed approach can be effectively applied in automated systems for engineering seismic monitoring, long-term observation of technogenic vibration sources, and detection of moving transport objects using velocimetric measurements. Fig.: 4. Refs: 24 titles.