Passive IMU Timing via Skipped Sample Patterns
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Solution Overview
Problem
Inertial Measurement Units (IMUs) in vehicles often operate asynchronously with their associated computer systems, leading to time lag issues that introduce errors in attitude data integration, especially during dynamic movements, and existing synchronization methods are complex and bandwidth-intensive.
Innovation Solution
The implementation of a passive timing method using patterns of skipped and duplicate samples of IMU attitude data to estimate lag times between updates and samples, allowing for improved timing relationships without active synchronization mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If active synchronization methods (broadcast messages) are used to synchronize the satellite computer and IMU clocks, then timing accuracy is improved, but device complexity and bandwidth usage increase
Solution Approach 1:
The system uses the existing asynchronous data bus communication infrastructure to carry timing information passively. The IMU and satellite computer each maintain their own independent clocks without requiring active synchronization commands, achieving timing correlation through self-service operation of the asynchronous bus
Solution Approach 2:
The asynchronous data bus acts as an intermediary that naturally carries timing information between the IMU and satellite computer. By utilizing the bus transaction timing characteristics rather than implementing dedicated synchronization hardware or protocols, the system achieves timing accuracy without additional complexity
2Measurement precision
If active synchronization methods (broadcast messages) are used to synchronize the satellite computer and IMU clocks, then timing accuracy is improved, but bandwidth consumption increases
Solution Approach 1:
The system leverages the inherent timing information present in the asynchronous bus transactions themselves. Each data transfer naturally embeds timing characteristics that can be used for correlation, eliminating the need for separate synchronization messages and thus conserving bandwidth
Solution Approach 2:
The asynchronous data bus serves as a mediator that simultaneously performs data transmission and timing information transfer. By extracting timing data from the bus transaction metadata rather than adding dedicated synchronization traffic, the system achieves timing accuracy without increasing bandwidth consumption
3Measurement precision
If external synchronization lines are added to synchronize clocks, then timing accuracy is improved, but device complexity and points of failure increase
Solution Approach 1:
The system uses the existing data bus infrastructure to achieve timing correlation without adding external synchronization hardware. The asynchronous bus naturally provides timing information through its transaction protocol, allowing the system to maintain independent clocks while achieving synchronization through software-based timing extraction
Solution Approach 2:
The asynchronous data bus acts as an intermediary that replaces the need for external synchronization lines. By utilizing the bus's inherent timing characteristics and transaction metadata, the system achieves clock correlation without adding complex hardware synchronization interfaces or additional failure points
4Adaptability or versatility
If asynchronous operation is maintained between satellite computer and IMU, then system flexibility and independence are preserved, but timing accuracy deteriorates
Solution Approach 1:
Each component (IMU and satellite computer) maintains its own independent clock and operates autonomously without requiring active synchronization. The system achieves timing correlation by passively observing and recording the timing characteristics of data transfers over the asynchronous bus, allowing independent operation while maintaining measurement precision
Solution Approach 2:
The asynchronous data bus serves as a mediator that enables timing correlation between independently operating components. By extracting and recording timing information from bus transactions, the system maintains system independence and flexibility while achieving the timing accuracy needed for attitude data integration
Data Source
AI summary
Embodiments described herein provide for passive timing of asynchronous Inertial Measurement Unit (IMU) attitude data using information derived from a pattern of skipped and duplicate samples of attitude data generated by the IMU. One embodiment is an attitude controller for a vehicle that generates samples of attitude data at a first frequency (f1) from an IMU of the vehicle. The IMU updates the attitude data at a second frequency (f2). Each update of the attitude data includes a time stamp. The attitude controller is processes time stamps in the samples to identify a pattern of at least one of a skipped sample of an update to the attitude data and a duplicate sample of an update to the attitude data. The attitude controller estimates lag times between updates of the attitude data and samples of the attitude data based on the pattern and a relationship between f1 and f2.