Which accuracy risk increases when asynchronous sensor data streams are combined in a Kalman filter?

💡 Explanation

Sensor fusion-induced bias becomes more prominent if asynchronous data has inconsistent delays. This is because the Kalman filter's estimation relies on statistical consistency provided expected synchronization, therefore introduced timing skews correlate into systematic errors rather than converging.

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