Gradient descent on the innovation loss converges to the Kalman gain under a nonstandard observability condition, with a geometric rate tied to observability and orthogonality violation.
Optimizing static linear feedback: Gradient method
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Interpretable Gradient Descent for Kalman Gain
Gradient descent on the innovation loss converges to the Kalman gain under a nonstandard observability condition, with a geometric rate tied to observability and orthogonality violation.