Jin Xue-Bo, Sun Shuli, Wei Hong, Yang Feng-Bao
School of Computer Information and Engineering, Beijing Technology and Business University, Beijing 100048, China.
School of Electronics Engineering, Heilongjiang University, Harbin 150080, China.
Sensors (Basel). 2018 Apr 11;18(4):1162. doi: 10.3390/s18041162.
The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor. Multi-sensor information fusion has been a key issue in sensor research since the 1970s, and it has been applied in many fields. For example, manufacturing and process control industries can generate a lot of data, which have real, actionable business value. The fusion of these data can greatly improve productivity through digitization. The goal of this special issue is to report innovative ideas and solutions for multi-sensor information fusion in the emerging applications era, focusing on development, adoption, and applications.
信息融合技术可以整合大量表示同一现实世界对象的数据和知识，并获得该对象一致、准确且有用的表示。这些数据可能是独立的或冗余的，并且可以由不同传感器在同一时间或不同时间获取。与单个传感器相比，合适的调查方法组合可以大幅提高信息收益。自20世纪70年代以来，多传感器信息融合一直是传感器研究中的关键问题，并且已在许多领域得到应用。例如，制造和过程控制行业可以生成大量具有实际可操作商业价值的数据。这些数据的融合可以通过数字化极大地提高生产力。本期特刊的目标是报道新兴应用时代多传感器信息融合的创新理念和解决方案，重点关注开发、采用和应用。
