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In the picture above SIGMA95® Inertial Navigation Unit by SAFRAN®

 

REal Time Inertial Navigation Adaptive Correction (RETINAC™) - Inertial navigation is a self-contained navigation technique in which measurements provided by accelerometers and gyroscopes are used to track the position and orientation of an object relative to a known starting point, orientation and velocity. A major disadvantage of using INUs (Inertial Navigation Units) for navigation is that they typically suffer from accumulated error. Because the guidance system is continually integrating acceleration with respect to time to calculate velocity and position, any measurement errors, however small, are accumulated over time. This leads to 'drift' that is an ever-increasing difference between where the system thinks it is located and the actual location. Due to integration a constant error in acceleration results in a linear error growth in velocity and a quadratic error growth in position. A constant error in attitude rate (gyro) results in a quadratic error growth in velocity and a cubic error growth in position.

There are currently navigation systems that integrate GPS/GLONASS and INU navigation systems so that INU only operates when GPS/GLONASS signals are not available. A state-of-the-art INU like SIGMA95® from SAFRAN® has very high levels of precision and reliability. However, there is still an INU accuracy problem when this situation continues for too long a time. There is also the possibility that the INU error is not systematic and may vary due to the different acceleration sequences in the three axes and also due to unavoidable variations in the operation of the device over time.

The RETINAC™ system adaptively and continuously adjusts the accuracy of INU through Machine Learning algorithms that operate in real time by comparing GPS/GLONASS and INU information for tens of thousands of acceleration patterns. When GPS/GLONASS is running, the MYTHOS™ adaptive machine learning algorithm continuously learns the errors generated by INU for specific acceleration sequences. When the GPS/GLONASS signal is not available, the MYTHOS algorithm operates in inference by correcting the positioning data coming from the INU.

 

 

 

 

 

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