Self-adaptive clock synchronization method with high robustness

Abstract

The invention belongs to the field of signal processing, and provides a self-adaptive clock synchronization method with high robustness for defects of the existing Kalman estimation clock synchronization method. The method provided by the invention comprises the steps that the topology model of a wireless sensor network is established; network nodes are divided into multiple levels; a subsequent clock synchronization method is carried out only between adjacent levels; progressive synchronization ultimately develops into global clock synchronization; a network node clock model and a transport model between nodes are established; an H infinity estimation filter is used to carry out relative clock parameter estimation on the nodes of adjacent levels; clock synchronization of adjacent levels is realized; and global clock synchronization is realized. According to the invention, H infinity estimation has the advantage of high robustness; and an H infinity clock synchronization method does not need the priori information of clock model noise, a transmission delay autocorrelation matrix and the like.

Description

technical field [0001] The invention belongs to the field of signal processing, and relates to a method for realizing clock synchronization based on a signal processing method, in particular to a highly robust self-adaptive clock synchronization method. Background technique [0002] Clock synchronization technology is an important part of wireless sensor networks, which provides a unified time scale for the local clocks of nodes in the network. Since all hardware clocks are imperfect, the local clocks of the sensor nodes have certain deviations from each other. A unified time scale is necessary for sensor nodes that need to work together. In addition, some special applications of sensor networks, such as data fusion of sensor nodes, sleep-wake-up energy-saving mechanism, MAC protocol based on TDMA scheduling mechanism and mobile node positioning, etc., have put forward new requirements for clock synchronization in the network. [0003] Classified from the perspective of ne...

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Problems solved by technology

However, limited by the inherent limitations of the Kalman filter itself, such as the Kalman algorithm requires the autocorrelation matrix of the clock model and delay noise to be known, which makes the performance of the Kalman estimation algorithm change once the clock model or delay model changes. Deterioration, and even divergence

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