Very high frequency active and passive integrated lightning positioning imaging detection system and method

Abstract

The invention relates to the technical field of lightning positioning, and particularly provides a very high frequency active and passive integrated lightning positioning imaging detection system and method, and the system comprises an active detection unit which is used for capturing an optical signal of lightning when the lightning occurs; the beacon receiver unit comprises a beacon transmitter and a non-directional receiver, the beacon transmitter transmits a very high frequency signal as a reference signal, and the non-directional receiver receives the reference signal for calibration; the fusion unit is used for performing time synchronization and position coordinate calibration on the active detection unit and the beacon receiver unit; the identification unit is used for synchronously analyzing the electromagnetic signal and the optical signal to identify time difference and signal characteristics, and generating lightning positioning data; and the imaging unit generates a lightning positioning image according to the lightning data flow. According to the invention, optical signals are actively acquired, electromagnetic signals are passively acquired, fusion analysis is carried out, and more comprehensive lightning positioning detection is provided.

Description

Technical Field

[0001] The present invention relates to the technical field of lightning location, and in particular to a very high frequency active and passive integrated lightning location imaging detection system and method. Background Art

[0002] Lightning location refers to the process of determining the specific location, time, intensity, polarity and other parameters of lightning discharge events through a series of technical means. Lightning location systems are widely used in meteorology, aviation safety, power system protection, scientific research and other fields, because lightning is not only a spectacular natural phenomenon, but also a potential threat to human activities and infrastructure.

[0003] In the prior art, a common method for lightning location is the time difference location method. When lightning occurs, the electromagnetic pulse released will propagate in the air. Since the speed of light is much greater than the speed of sound, the electromagnetic waves arrive almost instantly, while the sound takes a certain amount of time to propagate to the ground receiving point. The lightning location system uses multiple receiving stations to capture these electromagnetic waves and sound signals. By comparing the time difference between the signals received at different stations, the location of the lightning source can be calculated.

[0004] However, the speed of sound is affected by temperature, humidity and air pressure. Under different atmospheric conditions, the speed of sound will vary slightly, which may lead to errors in the calculation of time difference. In addition, electromagnetic waves and sound waves will encounter refraction and reflection when propagating in the atmosphere, especially in complex terrain or urban environments, which may make the signal path irregular and affect positioning accuracy. In addition, other electromagnetic signals and sound wave noise in the environment may interfere with the detection of lightning signals, especially in areas with complex electromagnetic environments.

[0005] Therefore, it is urgent to design a very high frequency active and passive integrated lightning location imaging detection system and method to solve the technical problem that the lightning location accuracy of the time difference positioning method is inaccurate due to various field conditions and noise. Summary of the invention

[0006] In view of this, the present invention proposes a very high frequency active and passive integrated lightning location imaging detection system and method, aiming to solve the technical problem in the prior art that the time difference positioning method is affected by various field conditions and noise and has inaccurate lightning location accuracy.

[0007] The present invention proposes a very high frequency active and passive integrated lightning location imaging detection system, comprising:

[0008] An active detection unit, used to capture the optical signal of lightning when lightning occurs, wherein the optical signal includes intensity information and the arrival time of lightning;

[0009] A beacon receiver unit, comprising a beacon transmitter and a non-directional receiver, wherein the beacon transmitter transmits a very high frequency signal as a reference signal, the non-directional receiver is distributed at a plurality of preset positions, and the non-directional receiver receives the reference signal for calibration;

[0010] A fusion unit is used to synchronize the time and calibrate the position coordinates of the active detection unit and the beacon receiver unit, and to obtain the electromagnetic signal of the lightning received by the non-directional receiver when the active detection unit receives the lightning optical signal;

[0011] The identification unit synchronously analyzes electromagnetic signals and optical signals to identify time differences and signal characteristics and generate lightning location data;

[0012] An imaging unit generates lightning location imaging according to the lightning data stream.

[0013] Preferably, the beacon receiver unit calculates the distance from the beacon transmitter to the xth non-directional receiver, wherein the local time of the beacon transmitter is recorded as t0, and records the arrival timestamp t of each non-directional receiver reference signal. x , calculate the arrival time difference Δt of each non-directional receiver:

[0014] t x -t0=Δt

[0015] Among them, t x is the arrival timestamp of the x-th non-directional receiver; t0 is the local time of the beacon transmitter, and x ≥ 3.

[0016] Preferably, the fusion unit calculates the distance from each beacon receiver to the xth non-directional receiver, that is, the signal transmission distance d x , through the signal transmission distance d x And the actual transmission distance d z Calibrate the position coordinates of the beacon transmitter, where the transmission distance d x , calculated by the following formula:

[0017] d x =Δt×c;

[0018] Where c is the speed at which the signal propagates in the air;

[0019] Calibrate the beacon transmitter and the non-directional receiver until the signal transmission distance d x And the actual transmission distance d z equal.

[0020] Preferably, the fusion unit fuses the reference signals received by each of the non-directional receivers, performs data fusion, and calculates the position of the beacon transmitter, including:

[0021] The TDOA algorithm is used to construct an overdetermined set of equations through the arrival time difference between different receivers to calculate the theoretical position of the beacon transmitter, and the theoretical position is compared with the actual position, and the beacon transmitter and the non-directional receiver are calibrated until the theoretical position of the beacon transmitter is the same as the actual position.

[0022] Preferably, the non-directional receiver generates the optical signal by dividing the electromagnetic signal of lightning into multiple scale and frequency components through discrete wavelet transform, wherein:

[0023] Use Daubechies wavelet as wavelet basis;

[0024] Decompose the signal into multiple layers, each layer contains low-frequency approximation and high-frequency detail.

[0025] De-noising each layer of signal, wherein high-frequency noise is removed by a preset soft threshold, wherein the preset soft threshold is calculated by VisuShrink or SURE method;

[0026] The processed high-frequency detail coefficients and low-frequency approximation coefficients are subjected to inverse wavelet transform to reconstruct the denoised signal.

[0027] Preferably, the identification unit synchronously analyzes the electromagnetic signal and the optical signal to identify the time difference and signal characteristics and generates lightning location data, including:

[0028] Extracting optical characteristics of lightning from optical signals, including time series, light intensity, spectral composition, duration and morphological changes;

[0029] Extract electromagnetic characteristics of lightning from electromagnetic signals, including time series, peak time, amplitude, frequency and duration;

[0030] Calculating a cross-correlation function between the optical signal and the electromagnetic signal to obtain a time offset corresponding to a maximum correlation, and determining that the optical signal and the electromagnetic signal are first correlated when the time offset is less than a preset time threshold;

[0031] When the optical signal and the electromagnetic signal are first correlated, the temporal correlation between the peak value of the optical characteristic light intensity and the peak value of the electromagnetic amplitude in the electromagnetic characteristic is checked. When the correlation is greater than a preset correlation threshold, it is determined that the optical signal and the electromagnetic signal are monitoring information of the same lightning.

[0032] Preferably, the identification unit calculates the time difference between the optical signal of lightning and the very high frequency reference signal to determine the time when lightning occurs, calculates the comparison time difference by the time when lightning occurs and the time when lightning arrives, and calculates the spatial coordinates of the lightning using the TDOA algorithm through the comparison time difference.

[0033] Preferably, the imaging unit generates lightning location imaging according to the lightning data stream, including:

[0034] The extracted features are mapped into two-dimensional or three-dimensional space to form a visual representation of the lightning event, where the spatial coordinates of the lightning are mapped to the corresponding location through ArcGIS Pro.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] Through the calibration of the beacon receiver unit and the calibration of the signal transmission distance and the real transmission distance of the fusion unit, the high-precision calibration of the position coordinates of the beacon transmitter and the non-directional receiver can be achieved, thereby improving the accuracy of positioning. Among them, the signal transmission distance and the real transmission distance are calibrated by the fusion unit, and the position of the beacon transmitter is calculated using the TDOA algorithm; the recognition unit can extract multiple features from the optical signal and the electromagnetic signal, and perform cross-correlation function analysis to achieve the recognition and monitoring of lightning, which helps to improve the real-time performance and accuracy of the system; the imaging unit maps the extracted features into a two-dimensional or three-dimensional space to form a visual representation of the lightning event, and maps the spatial coordinates of the lightning to the corresponding position through ArcGIS Pro, realizing the positioning imaging of the lightning.

[0037] In general, the VHF active-passive integrated lightning location imaging detection system of the present invention has high positioning accuracy, data processing capability, and multi-dimensional feature extraction and recognition capabilities, providing powerful technical support for the monitoring and research of lightning activities.

[0038] On the other hand, the present application also provides a very high frequency active and passive integrated lightning location imaging detection method, which is applied to the above-mentioned very high frequency active and passive integrated lightning location imaging detection system, comprising:

[0039] Capturing an optical signal of lightning when lightning occurs, wherein the optical signal includes intensity information and lightning arrival time;

[0040] A beacon transmitter transmits a very high frequency signal as a reference signal, and non-directional receivers are distributed at a plurality of preset positions, wherein the non-directional receivers receive the reference signal for calibration;

[0041] Performing time synchronization and position coordinate calibration, and acquiring the electromagnetic signal of lightning received by the non-directional receiver when the active detection unit receives the lightning optical signal;

[0042] Synchronously analyze electromagnetic signals and optical signals to identify time differences and signal characteristics, and generate lightning location data;

[0043] Generate lightning location imaging based on lightning data stream.

[0044] It can be understood that the very high frequency active and passive integrated lightning location imaging detection system provided in the present application and its corresponding method have the same beneficial effects, which will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0046] Figure 1 A functional block diagram of a very high frequency active and passive integrated lightning location imaging detection method provided by an embodiment of the present invention;

[0047] Figure 2 A flow chart of a very high frequency active and passive integrated lightning location imaging detection system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0049] See also Figure 1 As shown, this embodiment provides a very high frequency active and passive integrated lightning location imaging detection system, including:

[0050] An active detection unit, used to capture the optical signal of lightning when it occurs, the optical signal including the intensity information and the arrival time of lightning;

[0051] A beacon receiver unit includes a beacon transmitter and a non-directional receiver, wherein the beacon transmitter transmits a very high frequency signal as a reference signal, and the non-directional receiver is distributed at a plurality of preset positions, and the non-directional receiver receives the reference signal for calibration;

[0052] A fusion unit performs time synchronization and position coordinate calibration on the active detection unit and the beacon receiver unit, and obtains the electromagnetic signal of the lightning received by the non-directional receiver when the active detection unit receives the lightning optical signal;

[0053] The identification unit synchronously analyzes electromagnetic signals and optical signals to identify time differences and signal characteristics and generate lightning location data;

[0054] An imaging unit generates lightning location imaging according to the lightning data stream.

[0055] Specifically, the active detection unit includes a photoelectric sensor. In this embodiment, a diode or a photomultiplier tube is preferably used to capture the optical signal of lightning. A threshold trigger threshold is designed. Once the light intensity detected by the photoelectric sensor exceeds the trigger threshold, data collection is immediately started to ensure that data collection is only started when lightning occurs, avoiding the storage of a large amount of invalid data and improving system efficiency.

[0056] In some embodiments of the present application, the beacon receiver unit calculates the distance from the beacon transmitter to the xth non-directional receiver, where the local time of the beacon transmitter is recorded as t0, and the arrival timestamp of each non-directional receiver reference signal is recorded as t x , calculate the arrival time difference Δt of each non-directional receiver:

[0057] t x -t0=Δt

[0058] Among them, t x is the arrival timestamp of the x-th non-directional receiver; t0 is the local time of the beacon transmitter, and x ≥ 3.

[0059] It can be understood that by calculating the arrival time difference of each non-directional receiver, the distance from the beacon transmitter to each receiver can be obtained. This distance information can be used in subsequent algorithms to calculate the location of the beacon. By accurately calculating the distance from each receiver to the beacon, the accuracy of the positioning system can be improved. This distance information can help the system determine the location of the beacon more accurately, thereby improving the accuracy and reliability of positioning; by recording the arrival timestamp and local time, and calculating the arrival time difference, real-time beacon positioning can be achieved.

[0060] In some embodiments of the present application, the fusion unit calculates the distance from each beacon receiver to the xth non-directional receiver, that is, the signal transmission distance d x, through the signal transmission distance d x And the actual transmission distance d z The location coordinates of the calibrated beacon transmitter, where the transmission distance d x , calculated by the following formula:

[0061] d x =Δt×c;

[0062] Where c is the speed at which the signal propagates in the air;

[0063] Calibrate the beacon transmitter and non-directional receiver until the signal transmission distance d x And the actual transmission distance d z equal.

[0064] It can be appreciated that the accuracy of the positioning system can be improved by calibrating the location coordinates of the beacon transmitter, which can more accurately determine the location of the beacon, thereby improving the accuracy and reliability of positioning.

[0065] In some embodiments of the present application, the fusion unit fuses the reference signals received by each non-directional receiver, performs data fusion, and calculates the position of the beacon transmitter, including:

[0066] The TDOA algorithm is used to construct an overdetermined set of equations through the arrival time difference between different receivers to calculate the theoretical position of the beacon transmitter, and the theoretical position is compared with the actual position. The beacon transmitter and the non-directional receiver are calibrated until the theoretical position of the beacon transmitter is the same as the actual position.

[0067] Specifically, the TDOA algorithm relies on accurately measuring the time difference of signal arrival between different receivers. Assume there are three non-directional receivers, labeled A, B, and C. After the signal is transmitted from the beacon, it is transmitted at time t A ,t B and t C Arrives at these three non-directional receivers. Solve for the arrival time difference:

[0068] TDOA AB =t B -t A ;

[0069] TDOA AC =t C -t A ;

[0070] TDOA BC =t C -t B ;

[0071] By using these arrival time differences, an overdetermined system of equations is constructed, where the position of the non-directional receiver A is denoted by p A , the position of B is p B , the position of C is p C , then:

[0072] ||p A -p B ||-r·TDOA AB =0

[0073] ||p A -p C ||-r·TDOA AC =0

[0074] ||p B -p C ||-r·TDOA BC =0

[0075] Where r is the distance the signal travels, ||p A -p B ||, represents the distance between non-directional receivers A and B.

[0076] It is understood that the TDOA (Time Difference of Arrival) algorithm is a technology used to locate targets. It determines the location of the target based on the difference in arrival time of the target signal received by different sensors. This method is commonly used in sonar, radar, and positioning systems. Since the electromagnetic waves generated by lightning propagate relatively slowly in the atmosphere, when lightning occurs, the signals it generates will produce obvious time differences at receivers at different locations. By measuring these time differences, the TDOA algorithm can be used to determine the location of the lightning without measuring the arrival angle of the signal.

[0077] In some embodiments of the present application, the non-directional receiver generates an optical signal by dividing the electromagnetic signal of lightning into multiple scale and frequency components through discrete wavelet transform, wherein:

[0078] Use Daubechies wavelet as wavelet basis;

[0079] Decompose the signal into multiple layers, each layer contains low-frequency approximation and high-frequency detail.

[0080] De-noising is performed on each layer of the signal, where high-frequency noise is removed by a preset soft threshold, which is calculated by the VisuShrink or SURE method;

[0081] The processed high-frequency detail coefficients and low-frequency approximation coefficients are subjected to inverse wavelet transform to reconstruct the denoised signal.

[0082] The Daubechies wavelet is compactly supported, that is, it has a finite length of support in the time domain. This means that outside a certain range, the value of the Daubechies wavelet is zero. This property enables it to better describe short-time signal characteristics in signal processing. In addition, the Daubechies wavelet can implement multi-resolution analysis, that is, it can decompose the signal into components of different scales, so as to capture the local and overall characteristics of the signal. Since lightning signals usually have the characteristics of strong instantaneousness and large frequency span, the compact support of the Daubechies wavelet enables it to better describe such instantaneous signal characteristics. At the same time, multi-resolution analysis can decompose lightning signals into components of different scales, so as to better capture the local and overall characteristics of the signal, which helps to analyze and identify lightning signals more accurately.

[0083] VisuShrink (Visual Thresholding) is a simple and effective wavelet threshold denoising method. It is based on the wavelet coefficients of the signal and achieves signal denoising by setting the coefficients less than the threshold to zero. The threshold of the VisuShrink method is usually determined based on the signal-to-noise ratio or specific statistical properties. The advantages of the VisuShrink method are that it is simple to understand, easy to implement, and suitable for many signal processing tasks; SURE (Stein's Unbiased Risk Estimate) method is a wavelet threshold denoising method based on risk estimation. It uses Stein estimation to determine the optimal threshold to minimize the mean square error between the denoised signal and the true signal. The SURE method can determine the threshold more accurately by considering the unknown properties of the true signal, thereby improving the denoising effect. The SURE method usually requires certain assumptions about the statistical properties of the signal, so more prior knowledge may be required in some scenarios. As wavelet threshold denoising techniques, VisuShrink and SURE methods are also of great significance for denoising and feature extraction of lightning signals. By applying these methods, the noise in lightning signals can be effectively reduced and effective information in the signals can be extracted, so that lightning location and identification can be performed more accurately. The VisuShrink method is simple to understand and easy to implement, which gives it certain advantages in lightning signal processing. The SURE method can determine the threshold more accurately and improve the denoising effect, which is especially suitable for the fine processing of lightning signals.

[0084] Specifically, the following code is used to illustrate the implementation of this embodiment:

[0085] import numpy as np

[0086] import pywt

[0087] import matplotlib.pyplot as plt

[0088] #Generate the original signal of the example lightning (where the original signal is transient)

[0089] def generate_lightning_signal(t):

[0090] return np.sin(2*np.pi*50*t)*np.exp(-30*(t-0.5)**2)

[0091] #Add noise

[0092] def add_noise(signal,noise_level=0.5):

[0093] noise=noise_level*np.random.randn(len(signal))

[0094] return signal+noise

[0095] # Wavelet denoising function

[0096] def wavelet_denoising(signal,wavelet='db4',level=4,method='soft',threshold_method='VisuShrink'):

[0097] #wavelet decomposition

[0098] coeffs=pywt.wavedec(signal,wavelet,level=level)

[0099] #Threshold selection

[0100] if threshold_method=='VisuShrink':

[0101] sigma=np.median(np.abs(coeffs[-1])) / 0.6745

[0102] threshold=sigma*np.sqrt(2*np.log(len(signal)))

[0103] elif threshold_method=='SURE':

[0104] def sure_shrink(x):

[0105] n = len(x)

[0106] sorted_x = np.sort(np.abs(x))

[0107] risks = (n - 2 * np.arange(n) + np.cumsum(sorted_x ** 2)) / n

[0108] best = np.argmin(risks)

[0109] return sorted_x[best]

[0110] threshold = sure_shrink(np.concatenate(coeffs[1:]))

[0111] # Threshold processing

[0112] denoised_coeffs = []

[0113] for i in range(len(coeffs)):

[0114] if i == 0:

[0115] denoised_coeffs.append(coeffs[i])

[0116] else:

[0117] if method =='soft':

[0118] denoised_coeffs.append(pywt.threshold(coeffs[i], threshold, mode='soft'))

[0119] elif method == 'hard':

[0120] denoised_coeffs.append(pywt.threshold(coeffs[i], threshold, mode='hard'))

[0121] # Signal reconstruction

[0122] denoised_signal = pywt.waverec(denoised_coeffs, wavelet)

[0123] return denoised_signal

[0124] # Example lightning signal generation

[0125] t = np.linspace(0, 1, 1024)

[0126] original_signal = generate_lightning_signal(t)

[0127] noisy_signal = add_noise(original_signal)

[0128] # Denoising

[0129] denoised_signal = wavelet_denoising(noisy_signal, method='soft', threshold_method='VisuShrink')

[0130] # Plot the results

[0131] plt.figure(figsize=(14, 8))

[0132] plt.subplot(3, 1, 1)

[0133] plt.plot(t, original_signal)

[0134] plt.title('Original Lightning Signal')

[0135] plt.subplot(3, 1, 2)

[0136] plt.plot(t, noisy_signal)

[0137] plt.title('Noisy Lightning Signal')

[0138] plt.subplot(3, 1, 3)

[0139] plt.plot(t, denoised_signal)

[0140] plt.title('Denoised Lightning Signal(Soft,VisuShrink)')

[0141] plt.tight_layout;

[0142] It can be understood that the denoising effect after wavelet transform and soft threshold processing is: wherein the original signal of lightning shows the ideal characteristics of the original signal, the noisy lightning signal, wherein the signal after adding Gaussian noise is used to illustrate the denoising effect of this embodiment; wherein the denoised lightning signal is used to illustrate the signal after wavelet transform and soft threshold processing of this embodiment, the noise is removed while the main characteristics of the lightning signal are retained; in addition, the soft threshold method can smoothly remove noise and retain the transient characteristics and high-frequency components of the signal, and is an effective method for processing lightning signals.

[0143] In some embodiments of the present application, the identification unit synchronously analyzes the electromagnetic signal and the optical signal to identify the time difference and signal characteristics and generates lightning location data, including:

[0144] Extracting optical characteristics of lightning from optical signals, including time series, light intensity, spectral composition, duration and morphological changes;

[0145] Extract electromagnetic characteristics of lightning from electromagnetic signals, including time series, peak time, amplitude, frequency and duration;

[0146] Calculating a cross-correlation function between the optical signal and the electromagnetic signal to obtain a time offset corresponding to a maximum correlation, and determining that the optical signal and the electromagnetic signal are first correlated when the time offset is less than a preset time threshold;

[0147] When the optical signal and the electromagnetic signal are first correlated, the temporal correlation between the peak value of the optical characteristic light intensity and the peak value of the electromagnetic amplitude in the electromagnetic characteristic is checked. When the correlation is greater than a preset correlation threshold, the optical signal and the electromagnetic signal are judged to be monitoring information of the same lightning.

[0148] In some embodiments of the present application, the identification unit calculates the time difference between the optical signal of the lightning and the very high frequency reference signal to determine the time when the lightning occurs, calculates and compares the time difference by the time when the lightning occurs and the time when the lightning arrives, and calculates the spatial coordinates of the lightning by using the TDOA algorithm by comparing the time difference.

[0149] Specifically, the calculation is similar to that in the above implementation method.

[0150] In some embodiments of the present application, the imaging unit generates lightning location imaging according to the lightning data stream, including:

[0151] The extracted features are mapped into two-dimensional or three-dimensional space to form a visual representation of the lightning event, where the spatial coordinates of the lightning are mapped to the corresponding positions through ArcGIS Pro.

[0152] It is understandable that ArcGIS Pro is a professional geographic information system (GIS) software developed by Esri. ArcGIS Pro provides a wealth of spatial analysis tools that can analyze the spatial coordinates of lightning events, such as calculating the density, clustering, and spatial correlation of lightning events. These spatial analysis results provide an in-depth understanding of the distribution characteristics of lightning events and provide support for related research and decision-making. By mapping the spatial coordinates of lightning events to ArcGIS Pro, the location of lightning events can be intuitively displayed on the map. Using ArcGIS Pro's drawing and marking tools, the spatial coordinates of lightning events can be visualized on the map in the form of points, heat maps, etc., to help users intuitively understand the distribution of lightning events.

[0153] Compared with the prior art, the beneficial effects of this embodiment are:

[0154] By integrating the active detection unit and the beacon receiver unit, the system can achieve precise positioning and imaging of lightning. The fusion analysis of optical and electromagnetic signals can improve the precision and accuracy of lightning location and characteristics. By calculating the arrival time difference of each non-directional receiver to obtain the reference signal, the system can achieve real-time beacon positioning and calibration. This helps to improve the system's real-time tracking and accuracy of the beacon position, thereby improving the accuracy and reliability of lightning positioning; by calculating the signal transmission distance and the actual transmission distance, the system can calibrate the position coordinates of the beacon transmitter. This helps to improve the system's accuracy of the beacon position, thereby further improving the accuracy and reliability of lightning positioning. By recording the arrival timestamp and local time, and calculating the arrival time difference, the system can improve the accuracy and reliability of the positioning system. This is very critical for lightning monitoring and early warning systems, and can help the system more accurately identify and locate lightning activities.

[0155] See also Figure 2 As shown, this embodiment also provides a very high frequency active and passive integrated lightning location imaging detection method, which is applied to the above-mentioned very high frequency active and passive integrated lightning location imaging detection system, including:

[0156] Step S1: capturing an optical signal of lightning when lightning occurs, the optical signal including intensity information and lightning arrival time;

[0157] Step S2: transmitting a very high frequency signal as a reference signal through a beacon transmitter, distributing non-directional receivers at a plurality of preset positions, and the non-directional receivers receive the reference signal for calibration;

[0158] Step S3: performing time synchronization and position coordinate calibration, and acquiring the electromagnetic signal of lightning received by the non-directional receiver when the active detection unit receives the lightning optical signal;

[0159] Step S4: synchronously analyzing the electromagnetic signal and the optical signal to identify the time difference and signal characteristics, and generating lightning location data;

[0160] Step S5: Generate lightning location imaging according to the lightning data stream.

[0161] It can be understood that the very high frequency active and passive integrated lightning location imaging detection system provided in the present application and its corresponding method have the same beneficial effects, which will not be repeated here.

[0162] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0163] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0164] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0165] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0166] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A very high frequency active and passive integrated lightning location imaging detection system, characterized in that: include: An active detection unit, used to capture the optical signal of lightning when lightning occurs, wherein the optical signal includes intensity information and the arrival time of lightning; A beacon receiver unit, comprising a beacon transmitter and a non-directional receiver, wherein the beacon transmitter transmits a very high frequency signal as a reference signal, the non-directional receiver is distributed at a plurality of preset positions, and the non-directional receiver receives the reference signal for calibration; A fusion unit is used to synchronize the time and calibrate the position coordinates of the active detection unit and the beacon receiver unit, and to obtain the electromagnetic signal of the lightning received by the non-directional receiver when the active detection unit receives the lightning optical signal; The identification unit synchronously analyzes electromagnetic signals and optical signals to identify time differences and signal characteristics and generate lightning location data; An imaging unit generates lightning location imaging according to the lightning data stream.

2. The VHF active-passive integrated lightning location imaging detection system according to claim 1, characterized in that: The beacon receiver unit calculates the distance from the beacon transmitter to the xth non-directional receiver, where the local time of the beacon transmitter is recorded as t0, and records the arrival timestamp t of each non-directional receiver reference signal. x , calculate the arrival time difference Δt of each non-directional receiver: t x -t0=Δt Among them, t x is the arrival timestamp of the x-th non-directional receiver; t0 is the local time of the beacon transmitter, and x ≥ 3.

3. The VHF active-passive integrated lightning location imaging detection system according to claim 2, characterized in that: The fusion unit calculates the distance from each beacon receiver to the xth non-directional receiver, that is, the signal transmission distance d x , through the signal transmission distance d x And the actual transmission distance d z Calibrate the position coordinates of the beacon transmitter, where the transmission distance d x , calculated by the following formula: d x =Δt×c; Where c is the speed at which the signal propagates in the air; Calibrate the beacon transmitter and the non-directional receiver until the signal transmission distance d x And the actual transmission distance d z equal.

4. The VHF active-passive integrated lightning location imaging detection system according to claim 3, characterized in that: The fusion unit fuses the reference signals received by each of the non-directional receivers, performs data fusion, and calculates the position of the beacon transmitter, including: The TDOA algorithm is used to construct an overdetermined set of equations through the arrival time difference between different receivers to calculate the theoretical position of the beacon transmitter, and the theoretical position is compared with the actual position, and the beacon transmitter and the non-directional receiver are calibrated until the theoretical position of the beacon transmitter is the same as the actual position.

5. The VHF active-passive integrated lightning location imaging detection system according to claim 4, characterized in that: The non-directional receiver generates the optical signal by dividing the electromagnetic signal of lightning into multiple scale and frequency components through discrete wavelet transform, wherein: Use Daubechies wavelet as wavelet basis; Perform multi-layer decomposition on the signal, each layer contains low-frequency approximation and high-frequency detail; De-noising each layer of signal, wherein high-frequency noise is removed by a preset soft threshold, wherein the preset soft threshold is calculated by VisuShrink or SURE method; The processed high-frequency detail coefficients and low-frequency approximation coefficients are subjected to inverse wavelet transform to reconstruct the denoised signal.

6. The VHF active-passive integrated lightning location imaging detection system according to claim 1, characterized in that: The identification unit synchronously analyzes the electromagnetic signal and the optical signal to identify the time difference and signal characteristics and generate lightning location data, including: Extracting optical characteristics of lightning from optical signals, including time series, light intensity, spectral composition, duration and morphological changes; Extract electromagnetic characteristics of lightning from electromagnetic signals, including time series, peak time, amplitude, frequency and duration; Calculating a cross-correlation function between the optical signal and the electromagnetic signal to obtain a time offset corresponding to a maximum correlation, and determining that the optical signal and the electromagnetic signal are first correlated when the time offset is less than a preset time threshold; When the optical signal and the electromagnetic signal are first correlated, the temporal correlation between the peak value of the optical characteristic light intensity and the peak value of the electromagnetic amplitude in the electromagnetic characteristic is checked. When the correlation is greater than a preset correlation threshold, it is determined that the optical signal and the electromagnetic signal are monitoring information of the same lightning.

7. The VHF active-passive integrated lightning location imaging detection system according to claim 6, characterized in that: The identification unit calculates the time difference between the optical signal of lightning and the very high frequency reference signal to determine the time when lightning occurs, calculates the comparison time difference through the time when lightning occurs and the time when lightning arrives, and calculates the spatial coordinates of lightning by using the TDOA algorithm through the comparison time difference.

8. The VHF active-passive integrated lightning location imaging detection system according to claim 7, characterized in that: The imaging unit generates lightning location imaging according to the lightning data stream, including: The extracted features are mapped into two-dimensional or three-dimensional space to form a visual representation of the lightning event, where the spatial coordinates of the lightning are mapped to the corresponding location through ArcGIS Pro.

9. A very high frequency active and passive integrated lightning location imaging detection method, applied to the very high frequency active and passive integrated lightning location imaging detection system as claimed in any one of claims 1 to 8, characterized in that: include: Capturing an optical signal of lightning when lightning occurs, wherein the optical signal includes intensity information and lightning arrival time; A beacon transmitter transmits a very high frequency signal as a reference signal, and non-directional receivers are distributed at a plurality of preset positions, wherein the non-directional receivers receive the reference signal for calibration; Performing time synchronization and position coordinate calibration, and acquiring the electromagnetic signal of lightning received by the non-directional receiver when the active detection unit receives the lightning optical signal; Synchronously analyze electromagnetic signals and optical signals to identify time differences and signal characteristics, and generate lightning location data; Generate lightning location imaging based on lightning data stream.

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