Data Analysis and Data Fusion in System Identification and Measurements
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: 15 June 2025 | Viewed by 35
Special Issue Editors
Interests: Multi-source information fusion; estimation and filtering; target tracking
Interests: data fusion; multi-target tracking; sensor management; estimation and filtering
Special Issue Information
Dear Colleagues,
With the advent of the big data era, data has become an indispensable resource in modern society. In the field of system identification and measurement, how to effectively analyze and fuse data from different sources, formats, and qualities to improve the accuracy of system identification and measurement precision has become a current research hotspot. Data analysis is a core skill in the big data era. In system identification and measurement, data analysis techniques enable us to extract valuable information from massive datasets and reveal the inherent patterns and correlations within the data. Data fusion is a technology that integrates, optimizes, and utilizes data from different sources. In system identification and measurement, data fusion techniques can significantly enhance data reliability and accuracy, thereby improving the precision of system identification and measurement.
This Special Issue focuses on the theme of "Data Analysis and Data Fusion in System Identification and Measurements", aiming to explore the applications and advancements of data analysis and data fusion technologies in the field of system identification and measurement. Prospective authors are invited to submit their novel and original manuscripts on the theoretical underpinnings and the practical applications of these techniques. Potential topics of interest include, but are not limited to, the following:
- Multi-source information fusion;
- Bayesian estimation theory;
- Advanced signal and information processing;
- Target detection, recognition, and tracking;
- Cooperative localization and tracking;
- Sensor fusion in navigation systems;
- System identification;
- Simultaneous localization and target tracking;
- Networked estimation and filtering.
Dr. Guanghua Zhang
Prof. Dr. Hui Chen
Dr. Yulan Han
Guest Editors
Manuscript Submission Information
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Keywords
- data analysis
- data fusion
- system identification
- signal processing
- estimation and filtering
- target detection, recognition, and tracking
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