DocumentCode :
2950341
Title :
Multi Sensor Data Fusion Methods Using Sensor Data Compression and Estimated Weights
Author :
Bardwaj, A. Anand ; Anandaraj, M. ; Kapil, K. ; Vasuhi, S. ; Vaidehi, V.
Author_Institution :
Anna Univ., Chennai
fYear :
2008
fDate :
4-6 Jan. 2008
Firstpage :
250
Lastpage :
254
Abstract :
When data fusion is performed in a distributed environment, it improves accuracy but the constraints are limited communication bandwidth and limited processing capability at the fusion center. So, it is crucial to compress the data at the fusion center. This is accomplished by reducing the dimension of the data. Based on the Linear Estimation and weighted least square fusion results, a method is presented for compressing data at each local sensor to improve the accuracy of the fused estimates. Another method for multi sensor data fusion with estimated weights is also suggested in this paper which also improves the accuracy of the fused estimates.
Keywords :
data compression; sensor fusion; fusion center; multisensor data fusion methods; sensor data compression; Covariance matrix; Data compression; Equations; Filters; Noise measurement; Performance evaluation; Radar tracking; Sensor fusion; Sensor systems; Target tracking; Multi sensor data fusion; covariance matching method; singular value decomposition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, Communications and Networking, 2008. ICSCN '08. International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4244-1924-1
Electronic_ISBN :
978-1-4244-1924-1
Type :
conf
DOI :
10.1109/ICSCN.2008.4447198
Filename :
4447198
Link To Document :
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