Transcript FKF-Helsinki-ITS-2014

Measuring the true
Integrity of Navigation
in Real-Time
Antti A. I. Lange PhD
www.FKF.net
Overview:
• Integrity of Optimal Kalman filtering
• Helmert-Wolf blocking (HWB) of Geodesy
• the Fast Kalman Filtering (FKF) uses HWB
• Measuring the true integrity by
C.R.Rao’s MINQUE with FKF
• Concluding remarks
Integrity of Optimal Kalman Filtering:
Fast Kalman processing
Minimum-Norm-Quadratic-UnbiasedEstimation (MINQUE) theory:
The measuring accuracies of
many correlated observations
was solved reliably in1970 by
C.R.Rao’s MINQUE
that optimally exploits internal
consistency of the GNSS and
other supporting data
Concluding remarks:
• The Fast Kalman Filtering (FKF) using the HWb method
extends the precision of Real-Time-Kinematic (RTK) and VirtualRefence-Station (VRS) surveying to all GNSS engineering and
precision navigation applications
• The real-time precision of the FKF navigation depends
crucially on local information density which is a function of
both speed of the vehicle and the number of available GNSS
signals and frequencies including INS and other signals
• Ultra-reliable accuracy estimates of the GNSS and other
signals including IMU are operationally computable only using
the Minimum-Norm-Quadratic-Unbiased-Estimation (MINQUE)
methods with the help of the patented FKF (PCT/FI2007/00052)
Concluding remarks cont'd:
• Early warnings of tsunamis, earth quakes, shaking buildings and
collapsing bridges etc. become now possible with GPS, Glonass,
Galileo, Beidou, IRNSS, DORIS, QZSS, SBAS, GBAS and other
positioning methods exploiting all available combinations for
absolutely the best possible results
• Project proposals for expedient implementation of the FKF
processing are now welcome for ultra-reliable precision piloting
and navigation for all safety-critical ITS applications
• Please contact directly the inventor of FKF:
Mr. Antti A. I. Lange Ph.D., +358400373182 or +35891355450,
[email protected], www.FKF.net, skype: kalmanfilter.