Inertial Navigation Error Correction via Kalman Filtering
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Solution Overview
Problem
Inertial navigation systems suffer from errors in measurement due to inaccuracies in gyroscopes and accelerometers, leading to misalignments and incorrect calculations of vehicle position, velocity, and orientation, which are not effectively corrected by existing methods.
Innovation Solution
The use of Kalman filtering to correct errors by determining the difference between independent measurements and estimates of vehicle position, velocity, or acceleration relative to an inertial coordinate frame, and employing doubly integrated higher accuracy accelerometer measurements to refine these calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard inertial navigation systems are used, then continuous navigation data is provided, but measurement errors accumulate leading to position drift
Solution Approach 1:
The patent implements feedback by using GPS measurements to detect position errors in the inertial navigation system and feeding this error information back through a Kalman filter to correct the inertial system's estimates. The Kalman filter continuously updates the system state based on the difference between inertial predictions and GPS measurements, reducing error accumulation while maintaining continuous navigation capability.
Solution Approach 2:
The patent introduces a Kalman filter as an intermediary that processes and reconciles data from both the inertial navigation system and GPS. This intermediary component combines the continuous data from the inertial system with the periodic but accurate GPS measurements, producing a corrected navigation solution that maintains continuity while reducing drift errors.
2Measurement precision
If GPS is used to correct inertial navigation errors, then position accuracy improves, but system complexity increases
Solution Approach 1:
The patent makes the inertial navigation system multi-functional by enabling it to operate independently for continuous navigation while also being correctable by GPS when available. The Kalman filter manages multiple operational modes (inertial-only, GPS-corrected, transition states) within a unified framework, allowing the system to adapt to different operational conditions without requiring separate systems.
Solution Approach 2:
The patent dynamically changes system parameters through the Kalman filter, which adjusts the weighting and confidence levels of inertial versus GPS data based on signal quality, availability, and estimated error levels. This parameter adaptation allows the system to optimize performance under varying conditions without fixed architectural complexity.
3Measurement precision
If high accuracy accelerometers are used, then measurement precision improves, but cost and device complexity increase
Solution Approach 1:
The patent uses lower-cost inertial sensors that would normally drift but are periodically 'reset' or corrected using GPS measurements. Instead of investing in expensive high-precision inertial sensors, the system accepts drift from cheaper sensors and corrects it using the more accurate but intermittent GPS data, achieving high overall accuracy without the cost of premium inertial components.
Solution Approach 2:
The Kalman filter serves as an intermediary that compensates for the limitations of lower-cost inertial sensors by processing their output alongside GPS data. This intermediary processing recovers accuracy that would otherwise require expensive hardware, effectively trading computational complexity for reduced sensor cost.
Data Source
AI summary
Methods and apparatus for: (a) the correction of one or more elements determined from a first set of continuous gyro and accelerometer measurements comprising using a second set of discontinuously measured higher accuracy accelerometer measurements doubly integrated in an inertial coordinate system, (b) determining relative movement of a vehicle using a first set of acceleration measurements that do not include components of acceleration caused by the Earth's gravitational field, and a second set of acceleration measurements that do include components of acceleration caused by the Earth's gravitational field; and (c) correcting errors in an inertial navigation system positioned in a vehicle comprising using independently measured changes in position of the vehicle relative to an inertial coordinate frame.