Is an INS/GNSS Kalman filter honest about its drift when accelerometer bias is flicker noise?

What it found

Tests whether a 1-D INS/GNSS Kalman filter reports its own error correctly when the accelerometer bias is 1/f noise (five Gauss-Markov processes, 1 to 10,000 s) on top of white noise of 70 µg/√Hz (ICM-42688-P product page). Bias instability is swept from 10 to 300 µg and GNSS drops out for 300 s. NEES per degree of freedom (1 is honest): a filter with no bias state scores 21 to 21,700; a random walk read off the Allan curve at 1 s or 10 s scores 0.06 to 0.16 at 300 s (too pessimistic) and at 100 s 0.9 to 2.3; the matched model scores 0.88 to 1.05. At 100 µg the 300 s position RMS is 66 m matched, 81 m tuned at 100 s and 103 m tuned at 10 s. The bias is synthetic with a swept (not sourced) instability, one axis, no attitude coupling, 400 Monte Carlo paths.

A figure from its own output

Paper, code and results

• README and method
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Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.