CN112165368A - Time-synchronized real-time adaptive convergence estimation system - Google Patents

Time-synchronized real-time adaptive convergence estimation system Download PDF

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CN112165368A
CN112165368A CN202010877365.8A CN202010877365A CN112165368A CN 112165368 A CN112165368 A CN 112165368A CN 202010877365 A CN202010877365 A CN 202010877365A CN 112165368 A CN112165368 A CN 112165368A
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convergence
time
error
estimation
probability
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CN112165368B (en
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石繁荣
冉莉莉
张秋云
常志远
张静
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Southwest University of Science and Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J3/00—Time-division multiplex systems
    • H04J3/02—Details
    • H04J3/06—Synchronising arrangements
    • H04J3/0635—Clock or time synchronisation in a network
    • H04J3/0638—Clock or time synchronisation among nodes; Internode synchronisation
    • H04J3/0658—Clock or time synchronisation among packet nodes
    • H04J3/0661—Clock or time synchronisation among packet nodes using timestamps

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Abstract

The invention discloses a time-synchronized real-time adaptive convergence estimation system which comprises a synchronization error estimation unit, a synchronization error characteristic estimation model and a real-time convergence detection model. The method can be used in a distributed system or a wireless network with time synchronization requirements, is integrated into a time synchronization algorithm adopted by an application object, and further calculates the synchronization error convergence probability by using the time offset estimation obtained by the time synchronization algorithm. The synchronization error convergence probability obtained by the invention can be used as the basis for judging the system time synchronization precision and convergence state by other applications or time synchronization algorithms.

Description

Time-synchronized real-time adaptive convergence estimation system
Technical Field
The invention relates to the technical field of time synchronization, in particular to a real-time self-adaptive convergence estimation system for time synchronization.
Background
According to the internal and external published papers, the related patent information, and the related protocols or standards such as NTP (network Time protocol), IEEE standard 1588v2, WIA-PA, ISA100.11a and WirelessHART, the prior art for large-scale wireless network Time synchronization mainly focuses on the aspects of Time information exchange, parameter estimation, implementation scheme and the like of a Time synchronization algorithm. However, no specific research is available for online estimation of the network time synchronization convergence state.
Disclosure of Invention
Aiming at the defects in the prior art, the time synchronization real-time self-adaptive convergence estimation system provided by the invention solves the problem that the prior art does not estimate the network time synchronization convergence state on line.
In order to achieve the purpose of the invention, the invention adopts the technical scheme that: a time synchronized real-time adaptive convergence estimation system, comprising:
a synchronization error estimation unit for obtaining a synchronization error estimation value;
the synchronous error characteristic estimation model is used for estimating the convergence probability, buffering the estimated value of the convergence probability and calculating the estimation of the current time synchronous error convergence probability according to the buffered estimated value of the convergence probability;
and the real-time convergence detection model is used for screening out the synchronous error estimated value meeting the convergence condition, buffering the synchronous error estimated value meeting the convergence condition, and calculating the synchronous error characteristic according to the buffered synchronous error estimated value meeting the convergence condition.
Further: the calculation formula of the synchronization error estimation value is as follows:
El[k]＝Li[k]-Lj[k]
in the above formula, El[k]For synchronization error estimation, Li[k]Is a node viTime stamp of Lj[k]Is a node vjTime stamp of, node viAnd node vjAre neighboring nodes.
Further: the real-time convergence detection model comprises a convergence probability estimator, a first buffer and a convergence probability calculation unit.
Further: the calculation formula of the convergence probability estimator is as follows:
Figure BDA0002653018010000021
in the above formula, out [ k ]]To estimate the convergence probability, El[k]For synchronization error estimation, EmaxUpper limit of synchronization error, Emax＝a2μ+b2σ，a1、a2、b1And b2Both are coefficients, μ and σ are the mean and standard deviation of the synchronization error estimates, and ξ is the fraction of ∈ (0, 1).
Further: the first buffer has a length of LpThe memory cell of (1).
Further: the convergence probability calculating unit is a weighted average filter, and the number of weighting coefficients of the weighted average filter is Lp。
Further: the synchronous error characteristic estimation model comprises a convergence decision logic unit, a second buffer and an error characteristic calculation unit.
Further: the convergence judgment logic unit comprises a convergence judgment subunit, a logic subunit and an enabling subunit;
the convergence judgment subunit is configured to judge whether the convergence judgment is true, specifically, when the convergence probability is greater than a preset convergence threshold, output the convergence judgment as true, otherwise, output the convergence judgment as false;
the logic subunit is used for screening out the synchronization error estimated value E meeting the convergence conditionl[k]。
Further: the second buffer has a length of LEThe memory cell of (1).
Further: the error characteristic calculating unit uses the buffered synchronous error estimated value El[k]A synchronization error signature is calculated, the error signature comprising a mean μ and a standard deviation σ of the error.
The invention has the beneficial effects that: the method can be used in a distributed system or a wireless network with time synchronization requirements, is integrated into a time synchronization algorithm adopted by an application object, and further calculates the synchronization error convergence probability by using the time offset estimation obtained by the time synchronization algorithm. The synchronization error convergence probability obtained by the invention can be used as a basis for judging the time synchronization precision and the convergence state of the system by other applications.
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FIG. 1 is a block diagram of the present invention.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.
As shown in fig. 1, a time-synchronized real-time adaptive convergence estimation system includes:
a synchronization error estimation unit for obtaining a synchronization error estimation value;
in the invention, the instantaneous clock offset between nodes is used as a synchronization error estimated value El[k]The specific implementation depends on the time synchronization algorithm and the clock offset estimation method thereof adopted in practical application. The clock offset estimation is an indispensable part of all relevant protocols or standards of the time synchronization algorithm, and the invention can directly utilize the clock offset estimation value in the time synchronization algorithm as the synchronization error estimation value El[k]. Therefore, the invention does not need additional communication overhead to obtain the time stamp of the node and does not need to separately calculate El[k]Meanwhile, the adopted time synchronization algorithm cannot be interfered and influenced. These advantages enable the present invention to be very easily embedded in a time synchronization algorithm for practical use, with extremely excellent extensibility.
The calculation formula of the synchronization error estimation value is as follows:
El[k]＝Li[k]-Lj[k]
in the above formula, El[k]For synchronization error estimation, Li[k]Is a node viTime stamp of Lj[k]Is a node vjTime stamp of (1)Point viAnd node vjAre neighboring nodes.
And the real-time convergence detection model is used for screening out the synchronous error estimated value meeting the convergence condition, buffering the synchronous error estimated value meeting the convergence condition, and calculating the synchronous error characteristic according to the buffered synchronous error estimated value meeting the convergence condition.
The real-time convergence detection model comprises a convergence probability estimator, a first buffer and a convergence probability calculation unit.
The calculation formula of the convergence probability estimator is as follows:
Figure BDA0002653018010000041
in the above formula, out [ k ]]To estimate the convergence probability, El[k]For synchronization error estimation, EmaxUpper limit of synchronization error, Emax＝a2μ+b2σ，a1、a2、b1And b2Both are coefficients, μ and σ are the mean and standard deviation of the synchronization error estimates, and ξ is the fraction of ∈ (0, 1).
Mu and sigma can be initialized to sufficiently large values depending on factors such as synchronization error of the time synchronization algorithm, performance of a hardware clock, and network environment. During the algorithm run, μ and σ are updated by the synchronization error feature estimation model.
The time synchronization algorithm can be initialized to a sufficiently large value, namely E, according to factors such as synchronization error of the time synchronization algorithm, performance of a hardware clock, network environment and the likemaxShould be significantly larger than the synchronization error after algorithm convergence; can also be selected from Emax＝a2μ+b2And sigma initializing. During the operation of the algorithm, EmaxAutomatically updated by mu and sigma, e.g. Emax＝a2μ+b2σ。
a1、a2、b1And b2Are all integers greater than 1, and a2＞＞a1，b2＞＞b1。
The convergence probability estimator completes each new El[k]And (4) estimating the convergence probability, wherein the output estimated value out enters a buffer cache. The out sample set in the buffer is used to calculate the current time synchronization error convergence probability estimate, i.e., the output of the real-time adaptive convergence estimation model.
The first buffer has a length of LpThe memory cell of (1). The buffer length setting has two effects on the whole model, LpThe relative delay affecting convergence estimation and actual convergence, i.e. LpThe larger the convergence estimate, the more delayed and actually converged; on the other hand LpAffecting the reliability and interference-looking capability of the convergence estimate, i.e. LpThe larger the output, the smoother the output and less susceptible to interference from a single synchronization error estimate disturbance. Therefore, L is set according to the requirements of smoothness and sensitivityp。
The convergence probability calculating unit is a weighted average filter, and the number of weighting coefficients of the weighted average filter is Lp. The invention proposes to set weighting coefficients for requirements of smoothness and sensitivity in application, wherein if sensitivity is set to be small first and then large first when priority is given to sensitivity, and the average value is set to be 1/L when smoothness is given priorityp。
The synchronous error characteristic estimation model is used for estimating the convergence probability, buffering the estimated value of the convergence probability and calculating the estimation of the current time synchronous error convergence probability according to the buffered estimated value of the convergence probability;
the convergence judgment logic unit comprises a convergence judgment subunit, a logic subunit and an enabling subunit;
the convergence judgment subunit is configured to judge whether the convergence judgment is true, specifically, when the convergence probability is greater than a preset convergence threshold, output the convergence judgment as true, otherwise, output the convergence judgment as false; the output of the convergence decision subunit reflects the convergence probability of the time synchronization error in a certain time range, the output out of the convergence probability estimator reflects the convergence probability of the current time synchronization error, and the two jointly enable the screening El[k]And (4) sampling.
The logic subunit is used for screening out the synchronization error estimated value E meeting the convergence conditionl[k]。
The second buffer has a length of LEThe memory cell of (1). Buffer length LEThe larger the error feature estimation sample, the richer the result is closer to the real situation.
The error characteristic calculating unit uses the buffered synchronous error estimated value El[k]A synchronization error signature is calculated, the error signature comprising a mean μ and a standard deviation σ of the error.

Claims (10)

1. A time synchronized real-time adaptive convergence estimation system, comprising:
a synchronization error estimation unit for obtaining a synchronization error estimation value;
the synchronous error characteristic estimation model is used for estimating the convergence probability, buffering the estimated value of the convergence probability and calculating the estimation of the current time synchronous error convergence probability according to the buffered estimated value of the convergence probability;
and the real-time convergence detection model is used for screening out the synchronous error estimated value meeting the convergence condition, buffering the synchronous error estimated value meeting the convergence condition, and calculating the synchronous error characteristic according to the buffered synchronous error estimated value meeting the convergence condition.
2. The time-synchronized real-time adaptive convergence estimation system of claim 1, wherein the synchronization error estimation value is calculated by the following formula:
El[k]＝Li[k]-Lj[k]
in the above formula, El[k]For synchronization error estimation, Li[k]Is a node viTime stamp of Lj[k]Is a node vjTime stamp of, node viAnd node vjAre neighboring nodes.
3. The time-synchronized real-time adaptive convergence estimation system of claim 1, wherein the real-time convergence detection model comprises a convergence probability estimator, a first buffer, and a convergence probability calculation unit.
4. The time-synchronized real-time adaptive convergence estimation system of claim 3, wherein the convergence probability estimator is calculated by the formula:
Figure FDA0002653015000000011
in the above formula, out [ k ]]To estimate the convergence probability, El[k]For synchronization error estimation, EmaxUpper limit of synchronization error, Emax＝a2μ+b2σ，a1、a2、b1And b2Both are coefficients, μ and σ are the mean and standard deviation of the synchronization error estimates, and ξ is the fraction of ∈ (0, 1).
5. The time-synchronized real-time adaptive convergence estimation system of claim 3, wherein the first buffer is of length LpThe memory cell of (1).
6. The time-synchronized real-time adaptive convergence estimation system of claim 3, wherein the convergence probability calculation unit is a weighted average filter having a number of weighting coefficients Lp。
7. The time-synchronized real-time adaptive convergence estimation system of claim 1, wherein the synchronization error characterization estimation model comprises a convergence decision logic unit, a second buffer, and an error characterization calculation unit.
8. The time-synchronized real-time adaptive convergence estimation system of claim 7, wherein the convergence decision logic unit comprises a convergence decision subunit, a logic subunit, and an enable subunit;
the convergence judgment subunit is configured to judge whether the convergence judgment is true, specifically, when the convergence probability is greater than a preset convergence threshold, output the convergence judgment as true, otherwise, output the convergence judgment as false;
the logic subunit is used for screening out the synchronization error estimated value E meeting the convergence conditionl[k]。
9. The time-synchronized real-time adaptive convergence estimation system of claim 7, wherein the second buffer is of length LEThe memory cell of (1).
10. The time-synchronized real-time adaptive convergence estimation system of claim 7, wherein the error characterization calculation unit utilizes the buffered synchronization error estimate El[k]A synchronization error signature is calculated, the error signature comprising a mean μ and a standard deviation σ of the error.
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