Air Data Aided IMU Error Correction
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Solution Overview
Problem
Inertial measurement units (IMUs) face challenges in accurately compensating for sensor errors, particularly stochastic errors such as turn-on to turn-on biases and scale factor errors, which affect the accuracy of vehicle navigation systems, especially when using cost-effective MEMS sensors.
Innovation Solution
An IMU incorporating a plurality of accelerometers and rate gyroscopes, along with a Kalman estimator module, applies error compensation values to sensed acceleration and rotational rates, utilizing air data parameters like true airspeed and angle of attack to determine and correct for bias and scale factor errors, thereby producing error-corrected outputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If MEMS sensors are used for measuring acceleration forces and rotational position changes in IMUs, then cost is reduced, but measurement accuracy is sacrificed
Solution Approach 1:
The system uses feedback from air data sensors (pitot-static system) to continuously monitor true airspeed and uses this information to detect and correct drift in MEMS accelerometer readings through a Kalman filter, allowing the low-cost MEMS sensors to maintain accuracy comparable to expensive reference sensors
Solution Approach 2:
The patent introduces air data parameters (true airspeed from pitot-static system) as an intermediary to bridge the gap between low-cost MEMS measurements and accurate navigation, using the airspeed data as a reference to correct MEMS sensor errors without requiring expensive FOG or RLG sensors
2Adaptability or versatility
If integration techniques are used to determine position and orientation from IMU outputs, then navigation capability is provided, but sensor errors are compounded over time
Solution Approach 1:
The Kalman filter implements feedback by continuously comparing integrated accelerometer position with position derived from air data integration, detecting drift and generating correction values that are applied back to the accelerometer readings to prevent error accumulation
Solution Approach 2:
The system performs preliminary correction of accelerometer readings using air data information before integration, preventing error accumulation from occurring in the first place rather than attempting to correct it after integration
Data Source
AI summary
An inertial measurement unit (IMU) includes an inertial sensor assembly including a plurality of accelerometers and a plurality of rate gyroscopes, an inertial sensor compensation and correction module, and a Kalman estimator module. The inertial sensor compensation and correction module is configured to apply a set of error compensation values to sensed acceleration and rotational rate to produce a compensated acceleration and a compensated rotational rate of the IMU. The Kalman estimator module is configured to determine a set of error correction values based on a difference between a change in integrated acceleration of the IMU and a change in true airspeed of the IMU. The inertial sensor compensation and correction module is further configured to apply the set of error correction values to each of the compensated acceleration and the compensated rotational rate to output an error-corrected acceleration and an error-corrected rotation rate.