Many information fusion solutions work well in the intended scenarios; but the applications, supporting data, and capabilities change over varying contexts. 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 initial systems design. In this chapter, we seek to define and categorize different types of contextual information. We describe five contextual information categories that support target tracking: (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 designs to take advantage of the large data content available for a priori knowledge target tracking algorithm construction, implementation, and application.

Contextual Tracking Approaches in Information Fusion

SNIDARO, Lauro;
2016-01-01

Abstract

Many information fusion solutions work well in the intended scenarios; but the applications, supporting data, and capabilities change over varying contexts. 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 initial systems design. In this chapter, we seek to define and categorize different types of contextual information. We describe five contextual information categories that support target tracking: (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 designs to take advantage of the large data content available for a priori knowledge target tracking algorithm construction, implementation, and application.
2016
978-3-319-28969-4
File in questo prodotto:
File Dimensione Formato  
Chapter03_Blasch_ContextAwareTracking_Fomatted_v1.pdf

non disponibili

Tipologia: Documento in Pre-print
Licenza: Non pubblico
Dimensione 923.68 kB
Formato Adobe PDF
923.68 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1107229
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 4
social impact