Some remarks on Kalman filters for the multisensor fusion

Information Fusion

Volumn 3, Issue 3, 2002, Pages 191-201

  Gao, J B ^a   Harris, C J ^b  

^a UNIVERSITY OF NEW ENGLAND   (Australia)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; KALMAN FILTERING; SENSORS; STATE ESTIMATION;

DATA SOURCES;

SENSOR DATA FUSION;

EID: 0036720244     PISSN: 15662535     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1566-2535(02)00070-2     Document Type: Article

References (18)

1. The effect of the common process noise on the two-sensor fused-track covariance
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3. On optimal track-to-track fusion
4. Performance evaluation of track fusion with information filter
5. Kalman filtering with real-time applications
6. Multisensor data fusion in defense and aerospace
7. Distributed fusion architectures and algorithms for target tracking
8. Multisensor integration and fusion in intelligent systems
9. Data fusion and tracking using HMMS in a distributed sensor network
10. Comparison of two-sensor tracking methods based on state vector fusion and measurement fusion
11. Precise matching of 3d target models to multisensor data
12. Multimodel adaptive Kalman filter design for manoeuvring target tracking
13. Kalman filter algorithms for a multi-sensor system