TY - JOUR
T1 - Application of fast federated H∞ filtering in SINS/GPS integrated navigation system
AU - Zhang, Lei
AU - Wang, Bo
PY - 2009/8
Y1 - 2009/8
N2 - Because the effect of federal Kalman filtering in SINS/GPS integrated navigation depends on the system model and the statistical properties of noises, and the computing is complex, a new federal H∞ filtering is brought forward. The new formula of federal H∞ filtering is defined, the adaptive assignment principle of fusion information is advanced and the algorithm is simplified. It is no need to know the statistical properties of noises in H∞ filtering, so the new algorithm has strong robustness and improves the fault-tolerance capability of the system. The simulation result shows that the proposed method is better in stability and real-time characters.
AB - Because the effect of federal Kalman filtering in SINS/GPS integrated navigation depends on the system model and the statistical properties of noises, and the computing is complex, a new federal H∞ filtering is brought forward. The new formula of federal H∞ filtering is defined, the adaptive assignment principle of fusion information is advanced and the algorithm is simplified. It is no need to know the statistical properties of noises in H∞ filtering, so the new algorithm has strong robustness and improves the fault-tolerance capability of the system. The simulation result shows that the proposed method is better in stability and real-time characters.
KW - Adaptive information allocation
KW - Algorithm simplification
KW - Federal H filtering
KW - Integrated navigation
UR - http://www.scopus.com/inward/record.url?scp=70249112219&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:70249112219
SN - 1001-506X
VL - 31
SP - 1940
EP - 1943
JO - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
JF - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
IS - 8
ER -