Clock Skew Tracking With Weighted Fusion in Sensor Networks
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Solution Overview
Problem
Existing clock skew tracking methods in wireless sensor networks under timestamp-free interaction are inadequate as they rely on single communication pairs, leading to oversize tracking errors and instability due to multiple pairs of messages being overheard with large time errors.
Innovation Solution
A clock skew tracking method using weighted observation fusion and extended Kalman filtering algorithms to combine multiple observed values from multiple active nodes, reducing energy consumption and improving robustness by performing timestamp-free relative skew fusion tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple pairs of communication messages are overheard by the implicit node, then the tracking data can be improved, but the tracking error increases and stability deteriorates
Solution Approach 1:
The patent combines multiple observed values from multiple communication message pairs using a weighted fusion algorithm. The implicit node collects observations from L different communication pairs and fuses them with weights wk[n] to produce a unified tracking result, thereby improving data completeness while managing error through weighted combination
Solution Approach 2:
The patent introduces dynamic weight parameters wk[n] that are adjusted based on the quality and reliability of each observation. By changing the weight parameters according to tracking error characteristics, the system optimizes the fusion result to minimize overall tracking error while maintaining stability
2Reliability
If multiple pairs of communication messages are used for tracking, then the robustness can be improved, but the energy consumption increases
Solution Approach 1:
The implicit node performs listening synchronization by passively overhearing communication messages between the reference node and active nodes without transmitting any messages itself. The node processes and fuses the overheard observations locally, achieving robust tracking while minimizing energy consumption through self-service operation
Solution Approach 2:
The system uses multiple pairs of communication messages (excessive action) to improve robustness, but the implicit node only processes the necessary portion by selecting and fusing L observations from the available messages, avoiding the full energy cost of processing all possible message pairs
3Use of energy by moving object
If timestamp-free interaction is used, then the energy consumption is reduced, but the tracking stability deteriorates due to large time errors
Solution Approach 1:
The patent implements a feedback mechanism through the extended Kalman filtering algorithm that continuously updates the clock skew estimate based on new observations. The algorithm uses the tracking error feedback to adjust the state estimate and covariance, thereby maintaining stability even with timestamp-free interaction and large time errors
Solution Approach 2:
The system uses the covariance matrixPk[n] to predict and cushion against future tracking errors. By maintaining and updating the error covariance information beforehand, the system prepares for potential large time errors in timestamp-free interaction, allowing it to maintain stability through proactive error management
Data Source
AI summary
The present invention relates to a clock skew tracking method based on weighted observation fusion and timestamp-free interaction, and belongs to the technical field of wireless sensor networks. The method comprises performing listening synchronization by an implicit node S within an overlapping communication range between a reference node and multiple active nodes, and after multiple pairs of timestamp-free communication messages are successfully overheard, using multiple extended Kalman filtering algorithms to perform weighted fusion of multiple observed values on multiple obtained tracking results based on a scalar weighted linear minimum variance information fusion criterion, thus realizing timestamp-free relative skew fusion tracking of the implicit node. The present invention can not only dynamically track a relative clock skew on the basis of sending no message, but also reduce influence of a node with a relatively large tracking error on a listening node, thus robustness of skew tracking of the listening node is increased.