Measuring the true Integrity of Navigation in Real-Time

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Measuring the true Integrity of Navigation in
Real-Time
Antti A. I. Lange PhD www.FKF.net
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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.Raos MINQUE with FKF Concluding
remarks
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Integrity of Optimal Kalman Filtering
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Fast Kalman processing
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Minimum-Norm-Quadratic-Unbiased-Estimation
(MINQUE) theory The measuring accuracies of
many correlated observations was solved
reliably in1970 by C.R.Raos MINQUE that
optimally exploits internal consistency of the
GNSS and other supporting data
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Concluding remarks The Fast Kalman Filtering
(FKF) using the HWb method extends the precision
of Real-Time-Kinematic (RTK) and
Virtual-Refence-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)
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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, lange_at_fkf.net,
www.FKF.net, skype kalmanfilter.