Vardøy Field · Block 24/6 · North Sea

AI Position Reference Management

Every connected position reference continuously evaluated for quality, integrity, availability and suitability — then Kalman-fused into one optimal station-keeping solution.

DP Normal — Green Sensor control

DP GREEN — Autopos Active

Fused solution

AI Sensor Fusion Engine

INS (Navigation Grade)

10.7%

INS + GNSS (Tightly Coupled)

9.2%

GPS (L1/L2/L5)

9.0%

Multi-GNSS Solution

7.3%

INS + DVL

7.0%

Doppler Velocity Log

6.1%

DGPS (IALA / Fugro)

5.5%

PPP (Marinestar / Atlas)

4.9%

Galileo

4.6%

Locata Network

4.5%

RadaScan View

4.2%

FOG Gyro

4.2%

GLONASS

3.5%

Fanbeam

2.9%

84.4%

Position Confidence

13%

Mission Risk

Live outcome

Fused position quality

Compliance

DP class & reference independence

Independent PRS groups online

Reference diversity index

100%

Common mode failure risk

Position reference independence

95%

Recommended DP capability

DP Class 2 capable

DP alert status

DP Normal — Green

Estimator

Kalman filter — fused position state

A recursive Kalman estimator predicts the position error forward using the vessel's process model, then weights the incoming fused measurement by its own noise. Innovation is what the references said minus what the model expected; a sustained NIS above the χ² gate means a reference is feeding an inconsistent solution and should be demoted.

GNSS integrity

Spoofing & jamming assessment

Elevated GNSS anomaly signature

GNSS vs independent divergence

1.85 m

Carrier-to-noise (C/N₀)

40 dB-Hz

GNSS share of fusion

34.8%

GNSS-independent share

55.8%

Spoof resistance (avg)

26%

Jam resistance (avg)

17%

Continue as configured — GNSS integrity monitoring nominal, cross-checks agree within tolerance.

Comparative performance

Average position keeping & confidence across connected references

Best position keeping

0.14 m

PPP (Marinestar / Atlas)

Weakest position keeping

32 m

Satelles STL (Iridium)

Highest confidence

96.8%

FOG Gyro

Average by technology family (vs fleet average 78.1%)

GNSS (6)

87.3% · 1.48 m · w 34.8%

Inertial Systems (4)

92.4% · 0.54 m · w 31.1%

Laser PRS (3)

70.6% · 0.34 m · w 9.4%

Doppler Velocity Log (1)

78.8% · 0.53 m · w 6.1%

Locata (1)

86.5% · 0.21 m · w 4.5%

Hydroacoustic PRS (2)

68.4% · 1.79 m · w 4.3%

Radar PRS (2)

76.3% · 5.22 m · w 4.2%

Vision Positioning (3)

57.7% · 0.95 m · w 2.4%

LiDAR (1)

62.8% · 0.24 m · w 1.5%

Satelles STL (1)

79.1% · 32.00 m · w 1.5%

Continuous reasoning

AI Decision Engine — why the weighting is changing

Precipitation and visibility reducing laser PRS performance — laser confidence 67%. Weighting shifted toward RadaScan and radar correlation.
Environment
Strong multipath detected on GNSS near the structure — GNSS family weighting reduced, INS + DVL elevated.
GNSS
Locata ground network available with 5 transmitters — GNSS-independent redundancy secured.
Locata