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There are several steps which you can follow to implement a Kalman filter for real-time sensor data fusion in MATLAB for an autonomous navigation system which are:

1. Define system model (state-space equations).

2. Start with an initial state estimate and covariance.

3. Use the model to predict the state and update covariance.

4. Get sensor measurements.

5. Compute the Kalman gain.

6. Update state estimate and covariance using the measurements.

7. Keep repeating steps 3-6 in real-time.