Which consequence results when a poorly conditioned Kalman filter diverges?

💡 Explanation

The state estimate diverges when the **innovation covariance** is underestimated; because an underestimation trusts the process model too much, therefore propagating errors rather than correcting them via new measurements, leading to unbounded errors.

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