CN107015064A - Lightning Location Method based on thunder and lightning multivariate data auto-correlation Shicha algorithm - Google Patents
Lightning Location Method based on thunder and lightning multivariate data auto-correlation Shicha algorithm Download PDFInfo
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Abstract
This application discloses a kind of Lightning Location Method based on thunder and lightning multivariate data auto-correlation Shicha algorithm, methods described includes：The electromagnetic wave signal monitored to each monitoring station carries out noise suppression preprocessing；Cut out the synchrodata of each monitoring station；Ask for the auto-correlation time difference t between the synchrodata；Thunder and lightning position calculating is carried out according to positioning using TDOA equation；Wherein, the positioning using TDOA equation is(x, y, z, t) represents position and the time of origin of radiation source generation, (xi,yi,zi) for the position of i-th observation station, tiThe time of the signal measured for i-th of observation station, c is propagation velocity of electromagnetic wave in air.The Lightning Location Method amount of calculation based on thunder and lightning multivariate data auto-correlation Shicha algorithm that the application is provided is small, and speed is fast, and flexibility is high, and positioning precision is high, there is very strong practical value in lightning intrusion field.
Description
Technical Field
The application relates to the technical field of lightning location, in particular to a lightning location method based on a self-correlation time difference algorithm of lightning multivariate data.
Background
The lightning may cause a lot of damages, for example, tripping of a power transmission line of a power grid may be caused, a dispatching center issues commands, a unit in a line responsibility area sends out a large number of line patrol maintenance personnel, and fault points are searched pole by pole along the power transmission line according to a manual protection fault location result. Frequent lightning areas are usually in mountainous areas, and patrol maintenance personnel waste time and labor when turning over mountains and passing hills. For faults of some key lines, serious consequences such as delaying power transmission, reducing the safety and stability level of a power grid and the like can be caused. In order to improve the troubleshooting efficiency of faults caused by thunder and lightning and reduce the consequences caused by the thunder and lightning, people continuously research the thunder and lightning location.
The existing lightning location technology comprises a magnetic orientation method, a very low frequency time arrival method, a very high frequency interferometer method and a thunder location method. The magnetic orientation method is to receive electromagnetic wave signals generated by thunder and lightning by placing orthogonal annular magnetic field antennas in the north-south direction and the east-west direction, so as to judge the direction of the thunder and lightning. The method has larger error and higher installation requirement on the antenna, and the error is larger when the distance is longer. The very low frequency time arrival method is divided into two-dimensional and three-dimensional forms, the principle is that the lightning position is positioned by utilizing the time difference generated when the lightning arrives at different measuring stations, and the error correction is generally carried out by matching with optimization methods such as a least square method and the like, so that the error is larger. The very high frequency interferometer method is to locate the lightning radiation with interferometer, and has the principle of adopting several antennas with enough wave path difference, so that when the electromagnetic wave produced by lightning is transmitted to the antennas from different directions, the signals received by the antenna elements produce different phase differences, and the lightning position is calculated based on the phase differences. The method has the characteristics that the cloud flashover and the ground flashover can be positioned at the same time, the approximate discharge process of the lightning can be known, but the detection distance is short, the business is difficult, and the method can only be used for scientific research work. The thunder positioning method utilizes the propagation speed of sound in the air and the propagation speed of light in the air, an observer can hear thunder after seeing the lightning process after lightning occurs, and the distance between the lightning occurrence position and the observer is estimated by utilizing the time difference.
Therefore, how to improve the accurate positioning of the lightning is a technical problem to be solved urgently by the technical personnel in the field.
Disclosure of Invention
The application provides a lightning location method based on a self-correlation time difference algorithm of lightning multivariate data, so that accurate calculation of lightning positions is carried out.
The application provides a thunder and lightning location method based on a self-correlation time difference algorithm of thunder and lightning multivariate data, which is characterized in that the method comprises the following steps:
carrying out denoising pretreatment on electromagnetic wave signals monitored by each monitoring station;
cutting out synchronous data of each monitoring station;
obtaining the autocorrelation time difference t between the synchronous data;
calculating the lightning position according to the time difference positioning equation; wherein,
the equation of the time difference location is(x, y, z, t) represents the position and time of the radiation source (x)i,yi,zi) Indicating the position of the ith observation station, tiAnd c is the propagation speed of electromagnetic waves in the atmosphere.
Optionally, in the method, the performing denoising preprocessing on the electromagnetic wave signals monitored by each monitoring station includes:
and filtering clutter of the electromagnetic wave signals by adopting a filter.
Optionally, in the method, the performing denoising preprocessing on the electromagnetic wave signals monitored by each monitoring station includes:
and fitting the electromagnetic wave signal by using a 50Hz sine signal, and subtracting the fitted sine signal from the electromagnetic wave signal.
Optionally, in the method, after cutting out the synchronization data of each monitoring station, the method further includes:
and carrying out linear interpolation processing on the synchronous data.
Optionally, in the foregoing method, after the obtaining the autocorrelation time difference t between the synchronization data, the method further includes:
obtaining a correlation coefficient of the synchronous data corresponding to the time difference;
if the correlation coefficient reaches above 0.5, the time difference is considered to be effective; wherein,
the correlation coefficient is calculated by the formula
xnAnd ynRepresents any two sets of synchronized data, denoted complex conjugates, and m represents the location of the data movement.
Optionally, in the foregoing method, the calculating the lightning position according to the time difference location equation specifically includes:
and (4) iteratively calculating the lightning positions by a Levenberg-Marquardt algorithm according to the time difference positioning equation.
According to the lightning positioning method based on the self-correlation time difference algorithm of the lightning multivariate data, denoising pretreatment is carried out on electromagnetic wave signal data monitored by each monitoring station, synchronous data in the electromagnetic wave signal data are cut out, the self-correlation time difference of the synchronous data is calculated, the lightning position is calculated according to the self-correlation time difference, and finally the lightning position coordinate is obtained. The lightning location method based on the self-correlation time difference algorithm of the lightning multivariate data is small in calculated amount, high in speed, high in flexibility and high in location precision, and has strong practical value in the field of lightning research. The three-dimensional positioning algorithm can invert the lightning generation process and the tree-shaped structure, and has important significance for refined lightning detection.
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In order to more clearly explain the technical solution of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without any creative effort.
FIG. 1 is a structural flow chart of a lightning location method based on a self-correlation time difference algorithm of lightning multivariate data according to an embodiment of the present application;
fig. 2 is a denoising pre-processing by a filtering method according to an embodiment of the present application;
FIG. 3 illustrates a synchronized data clipping provided by an embodiment of the present application;
FIG. 4 is a correlation time difference calculation for the synchronization data provided by an embodiment of the present application;
fig. 5 is a schematic diagram of time difference positioning provided in an embodiment of the present application.
Detailed Description
One lightning discharge process can generally locate hundreds to thousands of radiation sources, can obtain a three-dimensional fine structure of lightning discharge and lightning VLF radiation source energy, and can invert important physical characteristics and physical parameters such as a thunderstorm cloud charge structure. The lightning VLF radiation source three-dimensional positioning process is actually a process of solving an over-determined equation set containing four unknowns (t, x, y and z) by using the arrival time ti of the lightning VLF radiation source detected by each detection antenna distributed in the same region and combining the spatial position coordinates (xi, yi and zi) of each station accurately positioned by using a high-precision GPS clock, wherein t is the starting time of the lightning VLF radiation source, and (x, y and z) are the space-time position coordinates of the VLF radiation source. The calculation of the coordinates of the lightning radiation source is an important component of the lightning location.
Referring to fig. 1, fig. 1 shows a structural flow chart of a lightning location method based on a lightning multivariate data autocorrelation time difference algorithm provided in the present application, where the method specifically includes the following steps:
s100: and (3) carrying out denoising pretreatment on the electromagnetic wave signals monitored by each monitoring station.
The thunder and lightning multivariate data refers to thunder and lightning data of different thunder and lightning detection devices and thunder and lightning data of different frequency bands received by the same device. And monitoring lightning electric field signals and magnetic field signals around the monitoring station by lightning monitoring equipment in the monitoring station.
The lightning electromagnetic field measurement is often interfered by various factors, and if the interference source is simple and regular, the interference source can be processed by adopting a certain digital signal processing method, so that the data quality is greatly improved. The method comprises the steps of conducting denoising preprocessing on electromagnetic wave signals monitored by each monitoring station, specifically, for the purpose of denoising data, the data are mainly used for removing power frequency noise of 50Hz and removing some environmental noise as far as possible, and a filtering method or a fitting method can be adopted.
The filtering method can be realized by adopting a Butterworth filter, and the method can remove 50Hz power frequency interference, filter low-frequency components of thunder and lightning and remove bump waveforms on waveform signals. The fitting method uses a 50Hz sine signal to fit the noise part of the signal, expands the fitting result to the whole data, and cuts off the fitted sine signal from the original data to obtain the signal without power frequency noise. As shown in fig. 2, the original signal monitored by the monitoring station, the fitted power frequency noise and the noise-removed result are given, and it can be seen that the interference of the power frequency noise can be well removed by using the fitting method, where in fig. 2, the filtered signal is shifted in order to better distinguish the original signal from the filtered signal.
S200: and cutting out the synchronous data of each monitoring station.
The cropping of the synchronization data is mainly to facilitate finding the time difference between the synchronization data. Since the instrument uses triggered recording, the data range of the same set of synchronization data recorded by each station is different, and in order to perform the following time difference calculation, the data must be cut and the common part of the signals received by each station in the set of data is taken out.
As shown in fig. 3, which shows an example of the clipping of the synchronous data in the present application, the signals are shifted in the direction of the voltage axis in order to better distinguish the station data. The method provides monitoring data of a measuring station 1, a measuring station 2 and a measuring station 3, and a synchronous data section 2 is synchronous data and processing results of the 3 measuring stations. It can be seen that for a given three of these data segments, the data segment 2 is a signal common to 3 stations, and the remaining two data segments can be compared with other data to verify that there is other synchronisation data.
In order to improve the time difference calculation accuracy in the embodiment of the present application, in the specific implementation process of the present application, a data difference is performed on the obtained synchronization data, and the resolution of the time difference calculation can be improved by performing the data difference. The synchronous data is interpolated to a proper sampling rate by linear interpolation, and the precision of the calculated time difference can reach microsecond magnitude. For example, when the sampling rate is 1MHz, the time interval between adjacent data points is 1 microsecond, which means that the resolution of the time difference calculated next step is 1 microsecond, and in order to improve the accuracy of time difference calculation, it is necessary to interpolate the processed data of each sync segment, in the present invention, linear interpolation is adopted to interpolate the data to the sampling rate of 10MHz, so that the accuracy of the calculated time difference will reach 0.1 microsecond.
And preprocessing and cutting the data to obtain synchronous data sections with good signal-to-noise ratio and high time resolution, wherein one group of data sections is used for subsequent time difference calculation and lightning position positioning.
S300: and solving the autocorrelation time difference t between the synchronous data.
In the autocorrelation time difference calculation between the synchronous data, the synchronous data segment needs to be divided according to the window size and the sliding step length, and the division can be performed according to 300 microseconds, 400 microseconds, 600 microseconds and the like. In the specific embodiment of the present application, the window size is 400 microseconds, and the synchronous data segment is divided into a plurality of segments with the length of 400 microseconds, where the data segments are the minimum data units for time difference calculation and positioning. And continuously moving the data of each station in the data unit, recording the corresponding moving distance when the data of each station is moved to the position with higher matching degree, and multiplying the moving distance by the time resolution ratio to obtain the autocorrelation time difference between the synchronous data.
Because the occurrence time of thunder and lightning is uncertain, and the thunder and lightning monitoring station is detecting the work all the time, consequently when not taking place the thunder and lightning, there is not the thunder and lightning signal in the measured data. In order to calculate the autocorrelation time difference more accurately, it is necessary to determine whether the synchronization data is valid before the autocorrelation time difference calculation. Specifically, an electromagnetic wave signal threshold is set, when a signal in the synchronous data is greater than the threshold, the synchronous data is judged to be valid, otherwise, the synchronous data is invalid, and invalid data units are directly discarded without participating in subsequent calculation.
The degree of matching of moving data is usually determined by using a correlation coefficient calculated by the following formulaxnAnd ynRepresents any two sets of synchronized data, denoted complex conjugates, and m represents the location of the data movement.
And continuously moving the data of each station in the data unit, calculating a correlation coefficient between two groups of moved data, and finally, taking a corresponding moving distance when the correlation coefficient is maximum, and multiplying the distance by the time resolution of the data to obtain the final time difference. In the actual calculation, in order to ensure the positioning accuracy, only when the normalized correlation coefficient between two data reaches above 0.5, the two data are considered to be correlated, and the time difference is recorded as the autocorrelation time difference and used in the time difference positioning calculation. For example, when the number of the mobile data points is-19, the correlation coefficient between the synchronization data of one monitoring station and the synchronization data of the other monitoring station reaches 0.933, and the time difference between the two data is calculated to be-1.9 microseconds (-19 × 0.1 microseconds), see fig. 4, (a) the synchronization data of the measuring station 1 and the measuring station 2 in fig. 4, and (b) the correlation coefficient between the synchronization data in the measuring station 1 and the measuring station 2.
S400: and calculating the lightning position according to the time difference positioning equation.
Referring to fig. 5, the principle of lightning location in an embodiment of the application is illustrated.
The equation for the time difference location is:
wherein (x, y, z, t) represents the position and time of the radiation source (x)i,yi,zi) Indicating the position of the ith observation station and the arrival time of the signal measured by it is tiAnd c is the propagation speed of electromagnetic waves in the atmosphere.
In the invention, a Levenberg-Marquardt algorithm is mainly adopted to iteratively solve the position of the radiation source. The Levenberg-Marquardt algorithm, as a least squares fitting algorithm, is commonly used in the solution of optimization problems. In order to reduce the iteration steps in actual positioning and quickly solve the three-dimensional position of the radiation source, a good iteration initial value is necessary, a large amount of calculation time and complexity can be saved, and the positioning efficiency is improved. The specific method for calculating the initial iteration value is as follows:
expanding the formula (1) to obtain a formula (2),
order toAnd r2≡x2+y2+z2And substituting them into formula (2), then
Subtracting the ith equation and the 1 st equation in the series of equation (3) yields:
let ti1≡ti-t1,xi1≡xi-x1,yi1≡yi-y1,zi1≡zi-z1Then equation (4) can be written as:
equation (5) represents a linear system of equations for the unknowns (x, y, z, t), and the position and time of occurrence of the radiation source can be solved by at least 5 stations.
Substituting the obtained initial value into a Levenberg-Marquardt iterative algorithm to solve the accurate radiation source position, wherein the iterative optimization target is as follows:
wherein: n is the number of the measuring stations participating in positioning, i is the ith measuring station,andobserved and fitted times, △ t, respectively, for the ith stationrmsAn error indicator is measured for the time of the detection system. The above equation, also known as goodness-of-fit, can be used to evaluate the effect of each localization.
The specific process of the Levenberg-Marquardt algorithm for iteratively solving the position of the radiation source is as follows:
the following expression is constructed according to equation (6):
in the above formula, x is the vector formed by the four variables, tiThe time when the signal is received by the ith station. Since f is conductive, so:
f(x+h)＝f(x)+J(x)h+ο(||h||2) (9)
wherein J (x) is a Jacobian matrix formed by fi(x) The first derivative of (d) constitutes:
according to the Levenberg-Marquardt algorithm, the iteration step h is the samelmThis can be obtained according to the following equation:
(JTJ+μI)hlm＝-g (11)
wherein g ═ JTf, μ is a damping coefficient and is greater than 0. The damping coefficient is used to adjust the size and direction of the iteration step, when the estimated value is far from the true value, it is equivalent to the steepest descent method, and when the estimated value is near to the true value, it is equivalent to the Gauss-Newton method, so the method has the advantages of both methods, and can solve the extreme value of the function by fast iteration.
According to the thunder and lightning positioning method based on the self-correlation time difference algorithm of the thunder and lightning multivariate data, denoising pretreatment is carried out on electromagnetic wave signal data monitored by each monitoring station, synchronous data in the electromagnetic wave signal data are cut out, the time difference of the synchronous data is calculated, the thunder and lightning position is calculated according to the time difference, and the thunder and lightning position coordinate is finally obtained. The lightning location method based on the self-correlation time difference algorithm of the lightning multivariate data is small in calculated amount, high in speed, high in flexibility and high in location precision, and has strong practical value in the field of lightning research. The three-dimensional positioning algorithm can invert the lightning generation process and the tree-shaped structure, and has important significance for refined lightning detection.
The above-described embodiments of the present invention do not limit the scope of the present invention. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
It should be noted that, in this document, terms such as "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. A lightning positioning method based on a self-correlation time difference algorithm of lightning multivariate data is characterized by comprising the following steps:
carrying out denoising pretreatment on electromagnetic wave signals monitored by each monitoring station;
cutting out synchronous data of each monitoring station;
obtaining the autocorrelation time difference t between the synchronous data;
calculating the lightning position according to the time difference positioning equation; wherein,
the equation of the time difference location is(x, y, z, t) represents the position and time of the radiation source (x)i,yi,zi) Indicating the position of the ith observation station, tiAnd c is the propagation speed of electromagnetic waves in the atmosphere.
2. The method of claim 1, wherein the denoising pre-processing of the electromagnetic wave signals monitored by each monitoring station comprises:
and filtering clutter of the electromagnetic wave signals by adopting a filter.
3. The method of claim 1, wherein the denoising pre-processing of the electromagnetic wave signals monitored by each monitoring station comprises:
and fitting the electromagnetic wave signal by using a 50Hz sine signal, and subtracting the fitted sine signal from the electromagnetic wave signal.
4. The method of claim 1, wherein said tailoring the synchronization data of said monitoring stations further comprises:
and carrying out linear interpolation processing on the synchronous data.
5. The method of claim 1, wherein said determining the autocorrelation time difference t between said synchronized data further comprises:
obtaining a correlation coefficient of the synchronous data corresponding to the time difference;
if the correlation coefficient reaches above 0.5, the time difference is considered to be effective; wherein,
the correlation coefficient is calculated by the formula
xnAnd ynRepresents any two sets of synchronized data, denoted complex conjugates, and m represents the location of the data movement.
6. The method of claim 1, wherein the calculating the lightning location according to the equation of the time difference location is specifically:
and (4) iteratively calculating the lightning positions by a Levenberg-Marquardt algorithm according to the time difference positioning equation.
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| CN112986698B (en) * | 2020-10-22 | 2022-07-05 | 南京信息工程大学 | Three-dimensional lightning positioning method |
| CN116106638A (en) * | 2023-04-11 | 2023-05-12 | 中国人民解放军96901部队 | Long-baseline strong electromagnetic pulse anti-interference positioning method and system |
| CN116106638B (en) * | 2023-04-11 | 2023-07-18 | 中国人民解放军96901部队 | Long-baseline strong electromagnetic pulse anti-interference positioning method and system |
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