DocumentCode
2981332
Title
Advanced Sensor Models: Benefits for Target Tracking and Sensor Data Fusion
Author
Koch, Wolfgang
Author_Institution
Res. Inst. for Inf. Process., Commun., & Ergonomics, FGAN
fYear
2006
fDate
Sept. 2006
Firstpage
565
Lastpage
570
Abstract
Modern sensor systems are typically characterized by advanced signal processing techniques which have direct impact on the quantitative and qualitative properties of the sensor data produced. This makes a more advanced modeling of the statistical characteristics of the sensor output inevitable. Via constructing appropriate likelihood functions based on these models the performance of Bayesian tracking and sensor data fusion techniques can be much improved. The proposed paper discusses the benefits by selected examples from various applications
Keywords
Bayes methods; sensor fusion; statistical analysis; target tracking; Bayesian tracking; advanced sensor models; advanced signal processing techniques; sensor data fusion; statistical characteristics; target tracking; Bayesian methods; Brain modeling; Intelligent sensors; Intelligent systems; Predictive models; Radar tracking; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Multisensor Fusion and Integration for Intelligent Systems, 2006 IEEE International Conference on
Conference_Location
Heidelberg
Print_ISBN
1-4244-0566-1
Electronic_ISBN
1-4244-0567-X
Type
conf
DOI
10.1109/MFI.2006.265652
Filename
4042069
Link To Document