Inertial Navigation System Roll Gyro Scale Factor Correction
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Solution Overview
Problem
Inertial navigation systems for projectiles face challenges in maintaining accurate roll angle calculations due to high roll rates and low-grade MEMS gyroscope scale factor errors, which lead to significant navigation errors, especially when using inexpensive sensors with scale factor accuracy of several thousand parts per million.
Innovation Solution
An inertial measurement system that uses a first roll gyro oriented parallel to the spin axis, along with second and third gyros to define a three-dimensional coordinate system, computes attitude and velocity vectors, and applies roll gyro scale factor corrections through a Kalman filter by synthesizing pseudo-velocity measurements to directly observe and correct cross-track velocity errors, thereby stabilizing roll angle and scale factor estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If low-grade MEMS gyroscopes are used to reduce cost, then device complexity and cost are reduced, but measurement precision deteriorates due to scale factor errors of several thousand ppm
Solution Approach 1:
The patent implements a feedback mechanism where the navigation system continuously monitors position errors and uses these errors to update and correct the roll gyro scale factor estimate in real-time through the Kalman filter. This closed-loop feedback allows the system to compensate for the inherent inaccuracies of low-grade MEMS gyroscopes, maintaining navigation precision while using cost-effective sensors.
Solution Approach 2:
The system performs self-calibration of the roll gyro scale factor by utilizing its own navigation errors as calibration data. The Kalman filter automatically adjusts the scale factor estimate based on observed position discrepancies, enabling the system to self-correct without external intervention or additional expensive sensors.
2Measurement precision
If additional aiding sensors are added to improve measurement precision, then navigation accuracy is improved, but device complexity increases
Solution Approach 1:
The system uses its existing inertial sensors and navigation algorithm to self-calibrate the roll gyro scale factor by analyzing its own navigation errors. This self-service approach eliminates the need for additional aiding sensors while maintaining navigation accuracy, thereby avoiding increased device complexity.
Solution Approach 2:
The Kalman filter serves multiple functions simultaneously: it performs standard navigation state estimation and also conducts roll gyro scale factor calibration. This multi-functionality allows the system to achieve both navigation accuracy and sensor calibration using the same computational resources and existing sensors, without adding hardware complexity.
3Measurement precision
If roll gyro scale factor accuracy is increased to less than 5 ppm to maintain navigation accuracy during high roll rates, then measurement precision is improved, but cost and device complexity increase significantly
Solution Approach 1:
The patent implements continuous feedback-based calibration where navigation position errors are fed back to update the roll gyro scale factor estimate in real-time. This feedback mechanism allows the use of low-accuracy sensors (several thousand ppm error) while achieving high navigation accuracy through dynamic compensation, avoiding the need for expensive <5 ppm gyroscopes.
Solution Approach 2:
The system dynamically changes the roll gyro scale factor parameter during flight based on observed navigation errors. Instead of relying on a fixed high-precision sensor, the scale factor is continuously adjusted as a variable parameter through Kalman filter processing, enabling accurate navigation with cost-effective sensors.
Data Source
AI summary
An inertial measurement system for a spinning projectile comprising: first (roll), second and third gyros with axes arranged such that they define a three dimensional coordinate system; at least a first linear accelerometer; a controller, arranged to: compute a current projectile attitude comprising a roll angle, a pitch angle and a yaw angle; compute a current velocity vector from the accelerometer; combine a magnitude of said velocity vector with an expected direction for said vector to form a pseudo-velocity vector; provide the velocity vector and the pseudo-velocity vector to a Kalman filter that outputs a roll gyro scale factor error calculated as a function of the difference between the velocity vector and the pseudo-velocity vector; and apply the roll gyro scale factor error from the Kalman filter as a correction to the output of the roll gyro.