Multi-sensor data fusion technology is forming hot spots. It was formed in the 1980s. It differs from general signal processing and also differs from single or multiple sensor monitoring and measurement. It is based on measurement results based on multiple sensors. High-level integrated decision-making process. In view of the miniaturization and intelligentization of sensor technology, based on the information acquisition, multiple functions are further integrated, resulting in an inevitable trend. Multi-sensor data fusion technology also promotes the development of sensor technology.
The definition of multi-sensor data fusion is summarized: the local data resources provided by multiple sensors of the same type or different types distributed in different positions are integrated and analyzed by computer technology to eliminate possible redundancy between multi-sensor information and Contradictions are complemented to reduce uncertainty, and a consistent interpretation and description of the measured objects is obtained, thereby improving the speed and correctness of the system's decision-making, planning, and response so that the system can obtain fuller information.
Integration of their information at different levels of information appears, including the data layer (layer pixel) fusion, feature level fusion, decision-making (evidence level) integration. Because it has the following advantages over single sensor information, that is, fault tolerance, complementarity, real-time, and economy, it has been gradually applied. In addition to military applications, the application field has been applied to automation technology, robotics, marine surveillance, seismic observation, construction, air traffic control, medical diagnosis, and remote sensing technology.
The definition of multi-sensor data fusion is summarized: the local data resources provided by multiple sensors of the same type or different types distributed in different positions are integrated and analyzed by computer technology to eliminate possible redundancy between multi-sensor information and Contradictions are complemented to reduce uncertainty, and a consistent interpretation and description of the measured objects is obtained, thereby improving the speed and correctness of the system's decision-making, planning, and response so that the system can obtain fuller information.
Integration of their information at different levels of information appears, including the data layer (layer pixel) fusion, feature level fusion, decision-making (evidence level) integration. Because it has the following advantages over single sensor information, that is, fault tolerance, complementarity, real-time, and economy, it has been gradually applied. In addition to military applications, the application field has been applied to automation technology, robotics, marine surveillance, seismic observation, construction, air traffic control, medical diagnosis, and remote sensing technology.
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