Many information fusion solutions work well in the intended scenarios; but the applications, supporting data, and capabilities change. One example is weather data for electro-optical target trackers of which standards have evolved over decades. The operating conditions of: technology changes, sensor/target variations, and the contextual environment can inhibit performance if not included in the systems design. In this paper, we seek to define and categorize different types of contextual information. We describe five contextual information categories that support information fusion: (1) domain knowledge from a user to aid the information fusion process through selection, cueing, and analysis, (2) environment-to-hardware processing for sensor management, (3) known distribution of entities for situation/threat assessment, (4) historical traffic behavior for situation awareness patterns of life (POL), and (5) road information for target tracking and identification. Appropriate characterization and representation of contextual information is needed for future high-level information fusion systems design to take advantage of the large data content available for a priori knowledge algorithm construction, implementation, and application.
Overview of contextual tracking approaches in information fusion
SNIDARO, Lauro;
2013-01-01
Abstract
Many information fusion solutions work well in the intended scenarios; but the applications, supporting data, and capabilities change. One example is weather data for electro-optical target trackers of which standards have evolved over decades. The operating conditions of: technology changes, sensor/target variations, and the contextual environment can inhibit performance if not included in the systems design. In this paper, we seek to define and categorize different types of contextual information. We describe five contextual information categories that support information fusion: (1) domain knowledge from a user to aid the information fusion process through selection, cueing, and analysis, (2) environment-to-hardware processing for sensor management, (3) known distribution of entities for situation/threat assessment, (4) historical traffic behavior for situation awareness patterns of life (POL), and (5) road information for target tracking and identification. Appropriate characterization and representation of contextual information is needed for future high-level information fusion systems design to take advantage of the large data content available for a priori knowledge algorithm construction, implementation, and application.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
