3. GPS/INS Positioning
The integration of GPS/INS can be performed at different levels and using different methods. GPSVisionTM technology benefits from the Kalman filter method, which is recognized as an industry standard. The state vector includes attitude, position, velocity, accelerometer biases and gyrodrifts. The Kalman filter consists of a sophisticated prediction and an update method.
Fig.3 The GPS/INS Integration Procedure
After establishing the dynamic model of the system, the Kalman prediction estimates the state vector and the covariance matrix of the system. Whenever a measurement is available, the Kalman update will use it to calculate a more accurate state vector and covariance. This will repeat until all data is processed. In the GPS/INS integration, the data from the INS is very accurate for a short period, so instead of using the Kalman prediction, INS positioning is used as the prediction module. To achieve the smoothest result, the Kalman filter is used in forward and backward directions.
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