Extended Kalman Clock Tracking for Timestamp-Free Node Synchronization
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Solution Overview
Problem
Current timestamp-free synchronization methods in wireless sensor networks fail to accurately track instantaneous clock offset due to nonlinearly varying clock skew, limiting their application in real-world scenarios.
Innovation Solution
A method using a first-order Gauss Markov model and extended Kalman filter to jointly track clock skew and offset, embedding synchronization into network data flow without dedicated timestamp exchange, utilizing a state equation and observation equation to model and correct clock parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If timestamp-free synchronization methods assume unchanged clock skew parameter, then the synchronization mechanism is simple and low power, but the instantaneous clock offset parameter cannot be tracked accurately
Solution Approach 1:
The patent transitions from static clock skew assumption to dynamic tracking by implementing an extended Kalman filter that continuously updates clock skew and offset parameters. The filter adapts to time-varying clock characteristics by modeling clock skew as a random walk process, enabling accurate tracking of instantaneous clock offset while maintaining computational efficiency suitable for low-power wireless sensor nodes.
Solution Approach 2:
The patent changes the parameter representation from fixed clock skew to time-varying clock skew modeled as a stochastic process. By representing clock skew as a random walk with process noise, the system can adapt to environmental changes and oscillator aging effects, improving offset tracking precision without requiring dedicated synchronization traffic.
2Measurement precision
If dedicated synchronization frames with timestamps are used, then clock parameter tracking is accurate, but communication bandwidth and energy are wasted
Solution Approach 1:
The patent makes existing data packets serve dual purposes: both data transmission and synchronization information carrying. By embedding synchronization functionality within regular network data flow, the system eliminates dedicated synchronization traffic while maintaining accurate clock tracking. The extended Kalman filter processes timing information from ordinary packet exchanges to update clock parameters.
Solution Approach 2:
The system uses its own data communication traffic to perform synchronization functions. Regular data packet exchanges between nodes provide the timing measurements needed for clock tracking, eliminating the need for separate synchronization mechanisms. The nodes self-sync by utilizing their existing communication patterns.
3Device complexity
If clock skew is modeled as time-invariant, then the synchronization algorithm is simple, but it cannot adapt to environmental changes and oscillator aging
Solution Approach 1:
The extended Kalman filter implements continuous feedback by constantly comparing predicted clock behavior with actual measurements from packet timing. The filter uses measurement updates to correct clock skew and offset estimates, adapting to environmental changes and oscillator drift. This feedback mechanism maintains accuracy while keeping computational complexity manageable through efficient matrix operations.
Data Source
AI summary
The present invention relates to a timestamp-free synchronization clock parameter tracking method based on extended Kalman filter, and belongs to the technical field of wireless sensor networks. With a first order Gauss Markov model and a clock model as a state equation, evolution processes of clock skew and instantaneous clock offset is described. Then an observation equation constituted by observation models of timestamp-free synchronization and instantaneous clock offset is established, and clock skew and instantaneous clock offset are jointly tracked by a tracking method based on extended Kalman filter to realize synchronization between a node to be synchronized and a reference clock node. The method can track two time-varying parameters simultaneously by following a network data flow without needing a dedicated synchronization frame to exchange synchronization information, which reduces energy consumption and improves synchronization precision.