Radio signal-based lightning protection detection method for meteorological station

Abstract

The invention relates to the technical field of meteorological monitoring and lightning protection, and discloses a radio signal-based lightning protection detection method for a meteorological station, which comprises the following steps of: receiving electromagnetic wave signals generated by lightning discharge in real time through radio receiving equipment of a plurality of meteorological stations, and acquiring characteristic data of time, frequency and intensity of the signals; an effective light velocity model is adopted to correct the influence of the propagation velocity of the lightning signal in the atmosphere, and the effective propagation velocity of the lightning signal is calculated by considering the ionospheric and atmospheric refraction effects; the position of the lightning power supply is estimated by measuring the arrival time difference and the time difference of lightning signals received by different sites and utilizing the geometric positions of the multiple sites. The positioning precision of the lightning power supply is greatly improved by adopting the cooperative work of the radio receiving equipment of a plurality of meteorological stations and combining the technologies of accurate lightning signal propagation speed correction, time synchronization error correction, geometric precision optimization and the like.

Description

Technical Field

[0001] The invention relates to the technical field of meteorological monitoring and lightning protection, and in particular to a method for performing lightning protection detection based on radio signals in a meteorological station. Background Art

[0002] With climate change and the increase in extreme weather events, the frequency and intensity of lightning disasters are also increasing year by year, posing a serious threat to people's lives and property safety, agricultural production and infrastructure. Therefore, how to effectively monitor, predict and prevent lightning disasters has become an urgent problem to be solved in many fields such as meteorology, disaster prevention and electricity.

[0003] At present, traditional lightning monitoring and lightning protection detection methods mainly rely on ground lightning monitoring equipment, such as radar, lightning detectors, etc. These devices obtain relevant information about lightning activities by detecting electromagnetic waves or current signals of lightning, and judge the occurrence, location and intensity of lightning based on this. However, these devices usually have the following shortcomings:

[0004] Traditional lightning location methods usually rely on relatively simple geometric principles and time difference methods to estimate the location of the lightning source. However, these methods are often affected by factors such as inconsistent signal transmission speed, changes in topography, ionosphere, and meteorological conditions in practical applications, resulting in low positioning accuracy, which in turn affects the accuracy and reliability of the lightning protection system. In practical applications, lightning signals are often affected by other electromagnetic interference sources (such as power facilities, communication signals, etc.), resulting in reduced accuracy in receiving and processing lightning signals. The inadequacy of traditional equipment in anti-interference capabilities often affects the accuracy and timeliness of lightning signals, which in turn affects the effectiveness of lightning protection detection. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a method for lightning protection detection based on radio signals in a meteorological station, which solves the deficiencies of the existing lightning monitoring methods in terms of positioning accuracy, signal processing, anti-interference capability and multi-site coordination.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A method for lightning protection detection based on radio signals in a weather station, comprising the following steps:

[0007] Through the radio receiving equipment of multiple weather stations, the electromagnetic wave signals generated by lightning discharge are received in real time, and the characteristic data of the time, frequency and intensity of the signals are obtained;

[0008] The effective light speed model is used to correct the influence of lightning signal propagation speed in the atmosphere, and the effective propagation speed of lightning signal is calculated by considering the refraction effect of ionosphere and atmosphere;

[0009] By measuring the arrival time difference and time difference of lightning signals received at different sites, the location of lightning sources can be estimated using the geometric positions of multiple sites;

[0010] Based on the error propagation theorem, the time synchronization error of multiple sites is corrected and the location of the lightning source is accurately calculated;

[0011] By calculating the geometric dilution of precision factor, the layout of multiple sites is optimized to minimize the positioning error;

[0012] Adopt adaptive filtering algorithm to suppress noise of received signals and improve signal quality;

[0013] Dynamically adjust signal processing strategies and site coordination strategies through reinforcement learning algorithms.

[0014] The present invention provides a method for lightning protection detection based on radio signals in a weather station, which has the following beneficial effects:

[0015] 1. The present invention greatly improves the positioning accuracy of lightning sources by using the radio receiving equipment of multiple meteorological stations to work together, combined with accurate lightning signal propagation speed correction, time synchronization error correction and geometric accuracy optimization. In particular, by correcting the ionosphere and atmospheric refraction effects of signal propagation, the positioning error caused by propagation speed differences is effectively reduced. Through multi-site data fusion and time synchronization correction, the accuracy of the lightning source location is further ensured, providing more reliable data support for lightning protection detection.

[0016] 2. The present invention uses an adaptive filtering algorithm to suppress noise on received lightning signals, which can effectively filter out interference such as environmental noise and equipment noise, and improve signal quality. When the lightning signal is weak or the signal quality is poor, the system can automatically adjust the filter parameters to enhance the effective components of the signal and ensure accurate reception and processing of the signal. This advantage enables the method to maintain high signal processing performance under complex environmental conditions.

[0017] 3. The present invention dynamically adjusts the coordination strategy between sites through a reinforcement learning algorithm, and can automatically optimize the site coordination mode according to the received signal quality and geographical location of different sites, thereby maximizing positioning accuracy and reducing error propagation. This adaptive mechanism enables the system to adjust and maintain the best coordination effect in real time under different lightning events or different environmental conditions, enhancing the flexibility and response capabilities of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flow chart of the method of the present invention; DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Example:

[0021] Please see attached Figure 1 The embodiment of the present invention provides a method for performing lightning protection detection based on radio signals at a weather station, comprising the following steps:

[0022] S1. Receive electromagnetic wave signals generated by lightning discharge in real time through radio receiving equipment at multiple weather stations, and obtain characteristic data of signal time, frequency and intensity;

[0023] In the present invention, the step of receiving lightning signals is one of the cores of the lightning protection detection method. The goal of this step is to obtain the electromagnetic wave signals generated by lightning discharge in real time through the radio receiving equipment of the meteorological station, and extract the characteristic data such as time, frequency, intensity, etc. of these signals to provide necessary information for subsequent lightning source location and analysis. Through this step, it can be ensured that the received signal data has sufficient accuracy and stability to support high-precision lightning source location and lightning protection warning.

[0024] In this embodiment, the process of receiving lightning signals first depends on the configuration and arrangement of the radio receiving equipment of the weather station. In order to accurately capture lightning signals, each weather station is equipped with a high-sensitivity broadband radio receiving device, which can receive electromagnetic waves generated by lightning discharge and has a wide frequency response range. Specifically, the receiving device can capture signals with a frequency range from several thousand hertz (kHz) to several hundred megahertz (MHz). This frequency range covers low-frequency and high-frequency electromagnetic waves generated during lightning discharge.

[0025] Specifically, each weather station is equipped with a wide-band antenna designed to efficiently receive electromagnetic radiation, including electromagnetic waves and lightning discharge signals. To ensure signal integrity and high-precision reception, the antenna system usually uses a multiple receiving array configuration to ensure that the received signal can cover a wide spatial area and avoid signal attenuation or distortion caused by environmental noise or multipath effects.

[0026] In each weather station, the received signal is first amplified by a radio frequency amplifier and then converted into a digital signal by an analog-to-digital converter (ADC). After that, the digital signal is transmitted to the central data processing system, which records the signal strength, frequency and time data in real time. In particular, time data is crucial for the subsequent lightning source location, because the propagation time difference of the lightning signal is a key factor in calculating the lightning source location.

[0027] It should be noted that the signal collection process requires a high degree of timeliness and accuracy. In order to ensure the timing of the received signal is accurate, the signal receiving equipment of all meteorological stations is synchronized to a unified time reference, usually through the Global Positioning System (GPS) or other precise time synchronization methods. This synchronization ensures the precise alignment of time data between multiple sites and avoids errors caused by time deviation in subsequent data processing.

[0028] In one possible implementation, when receiving signals, the system records the arrival time of each signal, specifically the instantaneous timestamp of the received signal. The timestamp format can adopt a unified time zone standard (such as UTC time) to ensure the timing consistency between different weather stations. By comparing the signal time data collected by different weather stations, the signal arrival time difference (TDOA) or arrival time (TOA) between each station can be calculated.

[0029] As an option, in order to further improve the accuracy of signal acquisition, the system can adopt a multi-channel receiving method, that is, each weather station not only receives lightning signals, but also processes signals in multiple frequency ranges at the same time. This multi-channel receiving method enables the system to distinguish different types of lightning signals and to preliminarily classify the intensity and type of lightning by the signal frequency characteristics. For example, low-frequency signals may come from a relatively close lightning source, while high-frequency signals may come from distant lightning discharges.

[0030] For example, after receiving the lightning signal, each weather station records and pre-processes the signal strength, frequency and time information in real time based on the characteristics of different frequency bands. These data will be uploaded to the central server for further signal analysis and processing. In order to reduce the delay that may occur during data transmission, the system usually uses high-bandwidth, low-latency wireless network technology (such as LTE or 5G network) for data transmission.

[0031] In the present invention, the time, frequency and intensity data of the received lightning signal will serve as the basic data for subsequent lightning source location, propagation speed correction and error correction. By accurately collecting these characteristic data, it can provide strong data support for subsequent signal analysis and processing, and further improve the accuracy and stability of lightning source location.

[0032] Specifically, the frequency and intensity data of the signal can help the system perform noise identification and suppression, signal filtering and other operations in subsequent steps. Through these preliminary data analysis, the system can identify and eliminate environmental noise that does not belong to lightning signals, thereby ensuring the accuracy of lightning source location.

[0033] In some embodiments, for strong lightning signals, the system can further refine the signal through time window control and signal windowing methods to extract the main features and eliminate unnecessary interference signals.

[0034] S2. Use the effective light speed model to correct the influence of lightning signal propagation speed in the atmosphere, and calculate the effective propagation speed of lightning signal by considering the refraction effect of ionosphere and atmosphere;

[0035] In this embodiment, step S2 involves correcting the propagation speed of the lightning signal in the atmosphere, especially taking into account the refraction effect of the ionosphere and the atmosphere. Since the electromagnetic waves generated by lightning discharge are affected by the ionosphere and the atmosphere during propagation, the propagation speed of the signal must be corrected in order to more accurately estimate the time when the signal arrives at each meteorological station, thereby improving the accuracy of lightning source location.

[0036] During the propagation of lightning signals, the electron density in the ionosphere and the refraction effect of the atmosphere are the two main factors that affect the signal propagation speed. Changes in the electron density of the ionosphere will slow down the propagation speed of lightning signals, especially when high-frequency radio signals are propagating. The atmospheric refraction effect is the change in refractive index caused by factors such as air pressure, temperature and humidity, which causes a deviation in the signal propagation path.

[0037] This embodiment uses the effective light speed model to correct the propagation speed of the lightning signal. Through the effective light speed model, the electron density, refractive factor and influence of the atmosphere in the ionosphere can be considered to calculate the corrected propagation speed. Specifically, the propagation speed v of the lightning signal under the influence of the ionosphere can be expressed by the following formula:

[0038]

[0039] Where c is the speed of light in vacuum, N e is the electron density of the ionosphere, N0 is the standard electron density (usually 10 12 electrons / cubic meter). When the electron density of the ionosphere is N e When it increases, the propagation speed of the signal will slow down, which in turn affects the signal propagation time.

[0040] Under the influence of the atmosphere, the propagation speed of lightning signals is v effIt will be corrected by the refraction factor. The change of atmospheric refraction factor is usually related to factors such as temperature, humidity, and air pressure. The refraction factor α can be expressed as:

[0041]

[0042] Among them, P is air pressure and T is temperature, both of which can be obtained in real time through weather stations. The change of refraction factor will cause the propagation path of lightning signals to shift, so it is necessary to make corrections when calculating the propagation speed.

[0043] According to the influence of the ionosphere and atmosphere, the corrected propagation speed v eff It can be calculated by the following formula:

[0044] v eff =v·(1-α·ΔT)

[0045] Among them, ΔT is the effect of temperature change on the propagation speed measured by the weather station, and α is the atmospheric refractive index, which represents the correction factor of temperature change on the propagation speed of lightning signals. By combining the refractive index with the temperature change, the propagation speed of lightning signals can be corrected.

[0046] In order to ensure the accuracy of the effective light speed model, it is very important to obtain meteorological data in real time. The electron density of the ionosphere and meteorological data (such as temperature, humidity, and air pressure) can be obtained in real time through ground-based meteorological stations, meteorological satellites, or radars. These data will serve as key inputs for correcting the propagation speed of lightning signals.

[0047] Corrected lightning signal propagation speed v eff The time data of the signal arriving at each weather station will be processed based on the corrected speed to more accurately estimate the propagation path of the signal and further calculate the spatial location of the lightning source.

[0048] In this embodiment, step S2 corrects the propagation speed of the lightning signal in the atmosphere through the effective light speed model, taking into account the refraction effect of the ionosphere and the atmosphere. This correction process can effectively improve the accuracy of lightning source positioning, especially under complex meteorological conditions. By obtaining real-time meteorological data and correcting the propagation speed, the positioning error caused by meteorological factors can be significantly reduced, providing more reliable basic data for subsequent lightning source positioning and lightning protection warning.

[0049] S3, by measuring the arrival time difference and time difference of lightning signals received at different sites, and using the geometric positions of multiple sites, the lightning source location is estimated;

[0050] In this embodiment, the main goal of step S3 is to estimate the spatial position of the lightning source by combining the arrival time difference of the lightning signals received by multiple meteorological stations with the geometric position of each station. In this way, high-precision lightning source positioning can be achieved, thereby providing reliable support for lightning protection warning. In order to ensure the accuracy of the position estimation, this step relies on measuring the arrival time difference of the signals at multiple stations.

[0051] The arrival time difference of lightning signals is mainly due to the different time required for the signal to propagate from the lightning source to different sites. This time difference is related to the path length of the signal propagation. The time difference data received by multiple receiving sites, combined with the geometric position of the sites, can accurately calculate the spatial position of the lightning source, thereby achieving high-precision lightning source positioning.

[0052] Assume there are n weather stations A1, A2, ..., A n The lightning signal is sent from the lightning source L, and the time it takes to propagate to each station is t1, t2, …, t n . Lightning source to site A i The distance is d i , the propagation speed of lightning signal is v eff , then the signal propagates to site A i The propagation time is:

[0053]

[0054] Among them, d i is the distance from the lightning source to the i-th site, v eff is the corrected lightning signal propagation speed. According to this formula, the arrival time of each station can be obtained by measuring the arrival time difference of the signals received at different stations, and then estimating the location of the lightning source. Assume that the reception time difference between different stations is Δt ij ,Right now:

[0055] Δt ij =t i -t j

[0056] Among them, t i and t j The lightning signal arrives at site A i and A j Based on this time difference information, combined with the known geographic coordinates of the site (x i ,y i ,z i ) and (x j ,y j ,z j ), the time difference positioning equation can be established.

[0057] First, consider two sites A i and A j The arrival time difference of the signals they receive is Δt ij , then we have the following relationship:

[0058] d i -d j =Δt ij ·v eff

[0059] Among them, d i and d j Lightning source L to site A i and A j Through multiple sets of time differences and the geometric positions of the stations, a series of equations can be obtained, which further form a nonlinear system of equations to solve the three-dimensional coordinates (x L ,y L ,z L ).

[0060] Specifically, site A i and A j The location to the lightning source satisfies the following relationship:

[0061]

[0062] Thus, through the time difference Δt ij The precise coordinates of the lightning source (x L ,y L ,z L ).

[0063] In order to further improve the positioning accuracy, more receiving stations are usually used in practical applications. Assume that there are n stations with coordinates (x1, y1, z1), (x2, y2, z2), …, (x n ,y n ,z n ), the received time difference is Δt ij , we can construct the following multi-site positioning equations:

[0064] (xL-xi)2+(yL-yi)2+(zL-zi)2=di2,i=1,2,…,n

[0065] Combining the time difference and the station location, a set of equations can be obtained, and the three-dimensional spatial coordinates (x L ,y L ,z L ).

[0066] In this embodiment, the time difference of arrival of lightning signals received at different sites is measured, and the location of the lightning source is accurately estimated using a time difference positioning algorithm in combination with the geographical location of each site. This method calculates the three-dimensional spatial coordinates of the lightning source using multi-site data by establishing a relationship between the time difference and the geometric position of the site, thereby achieving high-precision lightning source positioning. Further error correction and optimization measures can ensure the high accuracy of lightning source positioning results in complex environments, providing a reliable basis for subsequent lightning protection warnings.

[0067] S4. Based on the error propagation theorem, the time synchronization error of multiple sites is corrected to accurately calculate the location of the lightning source;

[0068] In this embodiment, the purpose of step S4 is to correct the time synchronization error that may exist in multi-site positioning by applying the error propagation theorem, thereby improving the accuracy of lightning source positioning. In the actual lightning signal reception process, due to the hardware differences of multiple meteorological stations, noise interference during signal transmission, and time synchronization errors between sites, the measurement error of the lightning signal arrival time may occur, thereby affecting the estimation result of the lightning source location.

[0069] Therefore, accurate calculation of the location of the lightning source requires not only the basic principle of time difference positioning, but also the correction of possible synchronization errors through a reasonable error model. By correcting the time synchronization errors of multiple receiving stations, the positioning accuracy can be significantly improved, making the location estimation of the lightning source more accurate.

[0070] In multi-site lightning location, it is assumed that the times at which n meteorological stations receive lightning signals are t1, t2, ..., t n Due to the synchronization error between sites, the actual time of receiving the signal will deviate from the true signal propagation time. Therefore, the time synchronization error will affect the positioning results.

[0071] Specifically, suppose site A i and A j The time synchronization error between sync,ij , then site A i The actual time the signal is received is:

[0072] t′ i =t i +Δt sync,ij

[0073] At this time, the time difference Δt ij It no longer fully reflects the true situation of signal propagation, but is affected by synchronization errors. Therefore, how to correct these time synchronization errors is the key to accurate positioning.

[0074] The error propagation theorem describes how the input error affects the error of the final result during the calculation of a physical quantity. In lightning source location, the time synchronization error will affect the time difference between the signals received by each station, thus affecting the final calculated lightning source location. According to the error propagation theorem, it is assumed that the estimation of the lightning source location depends on the time difference Δt ij ,The error propagation theorem can be used to calculate the propagation law of the error in lightning source location estimation.

[0075] In the multi-site location model, the location of the lightning source L(x L ,y L ,z L ) is calculated by the time difference Δt ij The geometric coordinates of each site are calculated by the formula (as described in step S3). Assuming the estimated error of the lightning source location is ΔL, according to the error propagation theorem, the error propagation can be expressed as:

[0076] ΔL=J·Δt

[0077] Where J is the Jacobian matrix, which represents the sensitivity of the time difference change to the change of the lightning source location, Δt

[0078] It is the influence of time synchronization error on the estimation result of lightning source location.

[0079] In one possible implementation, J can be represented as the following matrix:

[0080]

[0081] in, It represents the influence of time difference on the position of lightning source on x-axis, and other partial derivatives represent similar relationships. By solving these partial derivatives, we can get the influence of time difference between different sites on the position of lightning source.

[0082] After correcting the time synchronization error by applying the error propagation theorem, the location of the lightning source can be further accurately calculated. In this case, the location estimation of the lightning source does not only rely on the simple calculation of the time difference, but also combines the error propagation model to provide a more accurate positioning result.

[0083] In this embodiment, the time synchronization error of multiple sites is corrected by applying the error propagation theorem, thereby improving the accuracy of lightning source location. By constructing an error propagation matrix and combining strategies such as weighted method, iterative update method or Kalman filter algorithm, the synchronization error can be dynamically corrected to ensure accurate estimation of the lightning source location.

[0084] S5. By calculating the geometric precision reduction factor, the layout of multiple sites is optimized to minimize the positioning error;

[0085] In this embodiment, the purpose of step S5 is to optimize the layout of multiple sites by calculating the geometric precision reduction factor, thereby minimizing the positioning error and further improving the accuracy of the lightning source location estimation. The accuracy of the lightning source positioning system is affected by multiple factors, among which the geometric distribution of the site plays an important role in the positioning accuracy. Meteorological sites in different locations have different effects on the lightning source positioning accuracy, so a reasonable site layout design is the key to improving the positioning accuracy.

[0086] The geometrical dilution of precision factor is usually calculated based on the distance and angle between the sites. In this embodiment, it is assumed that there are n receiving sites and the location of the lightning source is L(x L ,y L ,z L ), the coordinates of each receiving station are Ai(xAi,y Ai ,z Ai )(i=1,2,...,n). In order to optimize the site layout, it is first necessary to calculate the contribution of each site to the positioning accuracy and the influence of the relative geometric relationship between the sites.

[0087] The geometrical reduction of precision factor can be calculated using the following formula:

[0088]

[0089] Among them, d ij It is site A i and Site A j The distance between them, α is an attenuation factor, which is usually related to the accuracy of signal propagation and time measurement, and usually has a value range of 1≤α≤2. In practical applications, the value of α can be adjusted through experiments and actual conditions to reflect the propagation characteristics in different environments.

[0090] The optimization goal in this embodiment is to minimize the positioning error based on the calculated geometric precision reduction factor. According to the above formula, the farther the distance between the sites, the smaller the geometric precision reduction factor, and the higher the positioning accuracy. Therefore, the goal of the optimization process is to make the receiving sites distributed as much as possible in a wide geographical area, thereby maximizing the accuracy of the lightning source location estimation.

[0091] As an option, weighting factors can be introduced in the optimization process to take into account factors such as signal strength and equipment performance of different sites. For example, sites with better signal quality can be given higher weights so that they contribute more to the positioning results. The objective function of the optimization can be expressed as:

[0092]

[0093] Among them, w i and w jSite A i and A j By maximizing the objective function, the optimized site layout can be obtained to minimize the positioning error.

[0094] In some embodiments, intelligent optimization methods such as genetic algorithms can be used to solve the site layout problem. Genetic algorithms can find the global optimal solution in a complex search space by simulating natural selection and genetic mechanisms.

[0095] By optimizing the site layout through genetic algorithms, the optimal or nearly optimal layout scheme can be found in complex geographical environments, thereby significantly improving the accuracy of lightning source positioning.

[0096] In the collaborative layout optimization of multiple sites, the synergy between sites can also be taken into account. For example, the weights of some sites can be dynamically adjusted according to changes in their location and signal quality. In order to further improve the positioning accuracy, a dynamic optimization strategy can be adopted to adjust the site layout and weights in real time according to factors such as the actual received lightning signal quality, signal strength, and synchronization error.

[0097] Through the calculation and optimization of step S5, the accuracy of the multi-site lightning source positioning system can be effectively improved. This embodiment optimizes the site layout by calculating the geometric precision reduction factor and combining optimization methods such as genetic algorithms, and dynamically adjusts the weight of each site, thereby minimizing the positioning error. This method not only improves the positioning accuracy, but also enhances the system's adaptability to environmental changes, and has strong practical application value.

[0098] S6, using adaptive filtering algorithm to suppress noise on received signals and improve signal quality;

[0099] In this embodiment, the core goal of step S6 is to use an adaptive filtering algorithm to suppress noise on the received lightning signal, improve signal quality, and thus enhance the accuracy of the positioning system. Lightning signals are subject to a variety of noise interference during propagation, such as environmental noise, equipment noise, and multipath effects, which can affect the quality of the signal and thus affect the precise positioning of the lightning source. Therefore, noise suppression plays a vital role in lightning signal processing.

[0100] In order to effectively suppress noise, the present invention adopts adaptive filtering technology. Different from traditional filtering methods, the adaptive filtering algorithm can dynamically adjust the filter parameters according to the changes of signals and noise, and automatically optimize the filtering effect. This makes the method highly adaptable in complex environments and can effectively cope with the time-varying characteristics of signal changes and noise.

[0101] An adaptive filter is a filter that can dynamically adjust coefficients based on the statistical characteristics of the input signal. In the process of lightning signal processing, the goal is to remove the noise component in the signal and retain the effective information of the lightning signal. The core of the adaptive filter is to iteratively update the coefficients of the filter based on a certain optimization criterion so that the output signal is as consistent as possible with the expected signal.

[0102] Specifically, assume that the received signal is d(t), which is composed of the lightning signal s(t) and the noise n(t, that is:

[0103] d(t)=s(t)+n(t)

[0104] Where s(t) is the signal from the lightning source and n(t) is the noise signal. In adaptive filtering, the goal is to output an estimated signal through the filter. Minimize the error between it and the actual lightning signal s(t), that is:

[0105]

[0106] Where w(t) is the weight vector of the adaptive filter, x(t) is the input signal vector, and w T (t)x(t) is the output of the filter. The output of the filter It should be as close as possible to the real lightning signal s(t) while removing the noise part.

[0107] In this embodiment, the adaptive filtering algorithm used is the least mean square error (LMS) algorithm, which is widely used in the field of signal processing due to its simple calculation and fast convergence speed.

[0108] Specifically, the LMS algorithm adjusts the filter coefficients by minimizing the error function. Let the error signal be e(t), which is defined as the difference between the actual received signal and the filter output:

[0109]

[0110] The goal of the LMS algorithm is to minimize the error signal by continuously updating the weights of the filter. The weight update formula is:

[0111] w(t+1)=w(t)+μe(t)x(t)

[0112] Among them, μ is the step size factor, which controls the convergence speed and stability of the algorithm. A larger μ value can speed up the convergence, but may cause instability; a smaller μ value will make the algorithm stable, but the convergence speed will be slower.

[0113] After the above adaptive filtering process, the noise part of the received lightning signal is effectively suppressed. The filter's adaptive adjustment capability enables it to dynamically adjust its parameters according to different noise types and signal changes, thereby ensuring the best noise suppression effect in various environments.

[0114] In some embodiments, other signal processing techniques, such as frequency domain filtering or wavelet transform, can be combined to perform more sophisticated signal processing. Frequency domain filtering can further improve the quality of the signal by selectively filtering different frequency components. Wavelet transform is suitable for processing non-stationary signals and can effectively suppress noise at multiple scales.

[0115] In order to further improve the performance of noise suppression, in some embodiments, a multi-channel adaptive filtering technology can be used, that is, using the signals of multiple receiving sites simultaneously for noise suppression. Through multi-site collaborative processing, the system can better separate noise and signals, thereby further improving positioning accuracy.

[0116] Specifically, assuming there are n receiving stations, the received signal can be expressed as:

[0117] d i (t) = s(t) + n i (t),i=1,2,…,n

[0118] For the signal of each receiving station, an adaptive filter is applied to process it and the output of each station is obtained. By fusing the filtered outputs of multiple sites (for example, by weighted averaging), a more accurate lightning signal estimate can be obtained, thereby improving positioning accuracy.

[0119] By using the adaptive filtering algorithm in step S6 to suppress noise on the received lightning signal, the signal quality can be significantly improved, thereby improving the accuracy of lightning source location. The adaptive filter can dynamically adjust parameters according to the changes in the actual signal and noise, and has strong adaptability. In addition, combined with multi-site collaborative processing and signal enhancement technology, the noise suppression effect can be further improved to ensure the reliability and accuracy of the system in various complex environments.

[0120] S7. Dynamically adjust signal processing strategy and site coordination strategy through reinforcement learning algorithm

[0121] In this embodiment, the goal of step S7 is to dynamically adjust the signal processing strategy and the site coordination strategy through the reinforcement learning algorithm, thereby further improving the performance of the lightning source location system. Reinforcement learning is a machine learning method that can automatically optimize the decision-making process by learning the optimal strategy through interaction with the environment. In the present invention, the application of the reinforcement learning algorithm can effectively adjust the signal processing and site coordination strategies according to the real-time lightning signal characteristics and environmental changes, thereby continuously improving the accuracy of signal processing and the overall performance of the system.

[0122] Reinforcement learning algorithms are based on the interaction between the agent and the environment, and aim to learn the optimal decision-making strategy through the process of exploration and utilization. In the lightning signal processing system, the "agent" in the system can be regarded as a decision maker, while the "environment" of the system is factors such as the received lightning signal and external noise. Through interaction with the environment, the agent continuously adjusts its behavior through trial and error to optimize positioning accuracy.

[0123] In this embodiment, the reinforcement learning algorithm can use methods such as Q-learning and deep Q network (DQN) to optimize the signal processing strategy by continuously evaluating the system behavior. Specifically, the system will update the current strategy based on the processing results of each lightning event and adjust future behavior based on past experience.

[0124] For example, suppose the current state of the system is s t , indicating the characteristics of the received lightning signal and the effect of the current signal processing. The system t Select an action t , the action may be to adjust the parameters of the filter, change the site coordination strategy or switch to a different signal processing method. Depending on the action performed, the system receives a reward signal r t , reflecting the impact of the action on the improvement of positioning accuracy or other performance indicators.

[0125] According to the update formula of reinforcement learning, the agent updates the Q value (i.e., the state-action value function) to optimize the strategy:

[0126] Q(s t ,a t )←Q(s t ,a t )+α[r t +γmax a′ Q(s t+1 ,a′)-Q(s t ,a t

[0127] Among them, α is the learning rate, which controls the degree to which new experience updates old knowledge; γ is the discount factor, which indicates the importance of future rewards; rt is the current reward; max a′ Q(s t+1 ,a′) is the maximum expected reward of all possible actions in the next state.

[0128] Through continuous iteration and learning, the intelligent body will gradually optimize its decision-making strategy to minimize positioning errors, improve signal quality, and ultimately achieve the optimal signal processing effect.

[0129] In this embodiment, the system can dynamically adjust the signal processing strategy through reinforcement learning. For example, when the quality of the lightning signal is poor, the system may choose to enhance the signal processing effect by increasing the gain of the filter; when the signal quality is good, the system may choose a more conservative signal processing strategy to avoid over-processing the signal.

[0130] Specifically, signal processing strategies may include the following:

[0131] Signal enhancement strategy: According to the signal quality and noise characteristics, select the appropriate signal enhancement method, such as adaptive filtering, frequency domain processing or wavelet transform.

[0132] Multi-site coordination strategy: By dynamically adjusting the coordination strategy between multiple receiving sites, the synthesis and positioning accuracy of lightning signals are optimized. The system can adjust the coordination strategy in different time periods or different lightning events to improve the overall accuracy and stability of the system.

[0133] Through these dynamic adjustments, the system can adaptively optimize the signal processing process to ensure that high positioning accuracy can always be achieved in different environments.

[0134] In a multi-site lightning signal receiving system, the collaborative work of different sites is crucial to positioning accuracy. Reinforcement learning algorithms can dynamically adjust the collaborative strategies between sites to maximize positioning accuracy and minimize error propagation.

[0135] Through reinforcement learning, the system can automatically learn and adjust these collaborative strategies to always maintain the best positioning performance under different lightning events and environmental conditions.

[0136] This embodiment introduces a reinforcement learning algorithm to dynamically adjust the signal processing strategy and site coordination strategy, greatly improving the accuracy of lightning source positioning and the adaptability of the system. Through real-time interaction with the environment, the reinforcement learning algorithm can automatically optimize system decisions to ensure that high-quality lightning signal processing results are always provided in various complex and dynamic environments. This method not only improves positioning accuracy, but also enhances the intelligence level of the system, enabling it to adapt to different lightning events and environmental changes in practical applications.

[0137] The effective light speed model is used to correct the influence of the lightning signal propagation speed in the atmosphere. The steps of calculating the effective propagation speed of the lightning signal by considering the refraction effect of the ionosphere and the atmosphere include:

[0138] Obtain real-time meteorological data, including ionospheric potential energy distribution, atmospheric refraction parameters and meteorological conditions;

[0139] Calculate the ionospheric refraction factor in the target area and use the refraction factor to determine the medium change characteristics in the signal propagation path;

[0140] Combined with the ionospheric potential energy of the target area, the effective propagation speed model of the signal is constructed;

[0141] By correcting the path and time of signal propagation in the atmosphere, the effective propagation speed of lightning signals is calculated for subsequent lightning source location calculations;

[0142] The modified propagation velocity model is applied to the lightning signal time data received at all stations to generate the standard propagation time of the signal, which serves as the input parameter for subsequent calculations.

[0143] By measuring the arrival time difference and time difference of lightning signals received at different sites, and using the geometric positions of multiple sites, the steps of estimating the lightning source location include:

[0144] Obtain the time information of lightning signals received by multiple sites and synchronize the time data of each site;

[0145] Determine the geometric distance model between each site and the lightning source, and establish the lightning signal propagation time difference relationship based on the site's geographic coordinates and the arrival time of the measured signal;

[0146] Use the time difference of arrival algorithm or the time arrival algorithm, combined with the geometric location of the site, to preliminarily calculate the spatial location of the lightning source;

[0147] Iteratively correct the initially calculated lightning source location and use the error minimization method to optimize the three-dimensional spatial coordinates of the lightning source;

[0148] The final accurate lightning source location is output for lightning protection warning and subsequent data analysis.

[0149] Based on the error propagation theorem, the time synchronization error of multiple sites is corrected and the steps to accurately calculate the location of the lightning source include:

[0150] Establish an error propagation model between lightning signal propagation time and site time synchronization error, and calculate the impact of time error on lightning source location results;

[0151] Based on the signal time data received from multiple sites, the time deviation between sites is analyzed and the time synchronization error component is extracted;

[0152] The error propagation theorem is used to quantify the time synchronization error and construct the error correction objective function;

[0153] The generalized least square method is used to correct the time synchronization error and adjust the time data received by the station;

[0154] The corrected time data is input into the lightning source location model to recalculate the spatial position of the lightning source.

[0155] The step of optimizing the layout of multiple sites and minimizing the positioning error by calculating the geometric attenuation of precision factor comprises:

[0156] Determine the geometric scope of the monitoring area, analyze the possible distribution characteristics of lightning activities in the area, and generate a preliminary site layout plan;

[0157] Establish a geometric dilution of precision factor model for site layout and calculate the geometric dilution of precision factor of each site combination to quantify the impact of site layout on lightning source location accuracy;

[0158] Adopt optimization algorithms to adjust the site layout, including adjusting the geographic coordinates of the sites and the distances between the sites, to minimize the geometric loss of precision factor;

[0159] According to the optimized site layout plan, the positioning error under different lightning source locations and signal propagation conditions is simulated to verify the effectiveness of the layout plan;

[0160] Determine the final optimized site layout plan and deploy the sites to ensure high-precision lightning source positioning within the monitoring area.

[0161] Adopting adaptive filtering algorithm to suppress noise of received signal and improve signal quality include:

[0162] Perform spectrum analysis on the received lightning signal, extract the main frequency components and noise frequency band distribution of the signal, and identify the effective frequency range of the signal;

[0163] Design an adaptive filter to automatically adjust the filter parameters according to the spectral characteristics of the signal to initially filter out background noise;

[0164] Construct a recursive model based on Kalman filtering, take the time series of the signal as input, dynamically predict and update the true value of the signal, and reduce the interference of random noise on the signal;

[0165] Perform quality assessment on the filtering results, including signal-to-noise ratio improvement, waveform recovery, and signal integrity, to ensure that the filtered signal meets the requirements of subsequent positioning calculations;

[0166] The processed high-quality signal is transmitted to the lightning source positioning module to improve the positioning accuracy.

[0167] The steps of dynamically adjusting the signal processing strategy and site coordination strategy through the reinforcement learning algorithm include:

[0168] Define the dynamic optimization objective function, minimize the lightning source location error and maximize the system response speed, and establish the optimization relationship between signal processing and site coordination strategy;

[0169] Construct a reinforcement learning model, use the intensity of lightning signals, site status, weather changes and other input parameters as the state space, and dynamically adjust the signal processing strategy and site weights;

[0170] The optimal strategy is determined using a reinforcement learning algorithm, and the action space is defined as adjusting site collaboration weights, dynamically updating filter parameters, and optimizing signal processing procedures;

[0171] Define reward and penalty functions, use key performance indicators such as positioning error, processing delay, and signal integrity as reward or penalty conditions to guide the algorithm optimization direction;

[0172] Adjust system configuration in real time based on optimization results, including reallocating site computing tasks, updating key parameters of signal processing algorithms, and evaluating the improvements in positioning accuracy and response speed after adjustments;

[0173] The dynamic optimization model is continuously trained and updated online to adapt to different lightning activity patterns and environmental changes.

[0174] The location estimation of the lightning source includes the following steps:

[0175] Initialize the geographic coordinates and time synchronization parameters of the site, and collect the lightning signal time data received at each site;

[0176] Construct a positioning model based on the geometric relationship between sites, and use the spatial distribution of sites and the time difference of received signals to calculate the initial lightning source location;

[0177] According to the error propagation characteristics of the positioning model, the time difference and geometric position error between stations are quantified and an error correction function is established.

[0178] Adopting iterative calculation method and combining dynamic correction of signal propagation model, the initial position is updated and optimized multiple times, gradually approaching the precise three-dimensional spatial coordinates of the lightning source;

[0179] The consistency of the final position estimation result is verified by comparing the signal propagation time received by the site with the propagation path calculation result of the estimated position to ensure that the positioning result conforms to the physical propagation law;

[0180] The optimized lightning source location is output in the form of three-dimensional spatial coordinates, and the data is used for lightning protection warning and lightning activity analysis.

[0181] The steps of receiving electromagnetic wave signals generated by lightning discharge in real time through radio receiving equipment of multiple weather stations and obtaining characteristic data of time, frequency and intensity of the signals include:

[0182] Deploy three weather stations and equip them with radio signal receiving equipment to ensure that the distribution of weather stations can cover the target monitoring area;

[0183] Each weather station is equipped with a high-sensitivity broadband antenna and receiving device to capture the electromagnetic wave signals generated by lightning discharges and ensure that the receiving equipment has a low signal-to-noise ratio;

[0184] Collect lightning signal data in real time at each weather station, including signal arrival time, frequency distribution, and waveform characteristics of signal strength;

[0185] The signal data received by each weather station is uploaded to the central data processing module through a high-speed data transmission network, and the timestamp is recorded to ensure the time synchronization of the data;

[0186] Perform preliminary screening on the received signal data to filter out non-target signals and obvious environmental noise interference, providing reliable input data for subsequent signal propagation model establishment and positioning calculation;

[0187] According to the signals received in real time, the subsequent signal propagation correction and lightning source location steps are triggered to ensure the high timeliness and stability of signal acquisition.

[0188] The precise location of the lightning source is output as three-dimensional coordinates for subsequent processing and analysis by the lightning protection warning system.

[0189] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for lightning protection detection based on radio signals in a weather station, characterized in that: The following steps are involved: Through the radio receiving equipment of multiple weather stations, the electromagnetic wave signals generated by lightning discharge are received in real time, and the characteristic data of the time, frequency and intensity of the signals are obtained; The effective light speed model is used to correct the influence of lightning signal propagation speed in the atmosphere, and the effective propagation speed of lightning signal is calculated by considering the refraction effect of ionosphere and atmosphere; By measuring the arrival time difference and time difference of lightning signals received at different sites, the location of lightning sources can be estimated using the geometric positions of multiple sites; Based on the error propagation theorem, the time synchronization error of multiple sites is corrected and the location of the lightning source is accurately calculated; By calculating the geometric dilution of precision factor, the layout of multiple sites is optimized to minimize the positioning error; Adopt adaptive filtering algorithm to suppress noise of received signals and improve signal quality; Dynamically adjust signal processing strategies and site coordination strategies through reinforcement learning algorithms.

2. The method for lightning protection detection based on radio signals of a weather station according to claim 1, characterized in that: The steps of using the effective light speed model to correct the influence of the lightning signal propagation speed in the atmosphere and calculating the effective propagation speed of the lightning signal by considering the refraction effect of the ionosphere and the atmosphere include: Obtain real-time meteorological data, including ionospheric potential energy distribution, atmospheric refraction parameters and meteorological conditions; Calculate the ionospheric refraction factor in the target area and use the refraction factor to determine the medium change characteristics in the signal propagation path; Combined with the ionospheric potential energy of the target area, the effective propagation speed model of the signal is constructed; By correcting the path and time of signal propagation in the atmosphere, the effective propagation speed of lightning signals is calculated for subsequent lightning source location calculations; The modified propagation velocity model is applied to the lightning signal time data received at all stations to generate the standard propagation time of the signal, which serves as the input parameter for subsequent calculations.

3. The method for lightning protection detection based on radio signals of a weather station according to claim 1, characterized in that: The step of estimating the lightning source location by measuring the arrival time difference and time difference of lightning signals received at different sites and using the geometric positions of multiple sites includes: Obtain the time information of lightning signals received by multiple sites and synchronize the time data of each site; Determine the geometric distance model between each site and the lightning source, and establish the lightning signal propagation time difference relationship based on the site's geographic coordinates and the arrival time of the measured signal; Use the time difference of arrival algorithm or the time arrival algorithm, combined with the geometric location of the site, to preliminarily calculate the spatial location of the lightning source; Iteratively correct the initially calculated lightning source location and use the error minimization method to optimize the three-dimensional spatial coordinates of the lightning source; The final accurate lightning source location is output for lightning protection warning and subsequent data analysis.

4. The method for lightning protection detection based on radio signals of a weather station according to claim 1, characterized in that: The steps of correcting the time synchronization error of multiple sites based on the error propagation theorem and accurately calculating the location of the lightning source include: Establish an error propagation model between lightning signal propagation time and site time synchronization error, and calculate the impact of time error on lightning source location results; Based on the signal time data received from multiple sites, the time deviation between sites is analyzed and the time synchronization error component is extracted; The error propagation theorem is used to quantify the time synchronization error and construct the error correction objective function; The generalized least square method is used to correct the time synchronization error and adjust the time data received by the station; The corrected time data is input into the lightning source location model to recalculate the spatial position of the lightning source.

5. The method for lightning protection detection based on radio signals of a weather station according to claim 1, characterized in that: The step of optimizing the layout of multiple sites and minimizing the positioning error by calculating the geometric attenuation of precision factor comprises: Determine the geometric scope of the monitoring area, analyze the possible distribution characteristics of lightning activities in the area, and generate a preliminary site layout plan; Establish a geometric dilution of precision factor model for site layout and calculate the geometric dilution of precision factor of each site combination to quantify the impact of site layout on lightning source location accuracy; Adopt optimization algorithms to adjust the site layout, including adjusting the geographic coordinates of the sites and the distances between the sites, to minimize the geometric loss of precision factor; According to the optimized site layout plan, the positioning error under different lightning source locations and signal propagation conditions is simulated to verify the effectiveness of the layout plan; Determine the final optimized site layout plan and deploy the sites to ensure high-precision lightning source positioning within the monitoring area.

6. The method for lightning protection detection based on radio signals of a weather station according to claim 1, characterized in that: The step of adopting an adaptive filtering algorithm to suppress noise on the received signal and improve the signal quality includes: Perform spectrum analysis on the received lightning signal, extract the main frequency components and noise frequency band distribution of the signal, and identify the effective frequency range of the signal; Design an adaptive filter to automatically adjust the filter parameters according to the spectral characteristics of the signal to initially filter out background noise; Construct a recursive model based on Kalman filtering, take the time series of the signal as input, dynamically predict and update the true value of the signal, and reduce the interference of random noise on the signal; Perform quality assessment on the filtering results, including signal-to-noise ratio improvement, waveform recovery, and signal integrity, to ensure that the filtered signal meets the requirements of subsequent positioning calculations; The processed high-quality signal is transmitted to the lightning source positioning module to improve the positioning accuracy.

7. The method for lightning protection detection based on radio signals of a weather station according to claim 1, characterized in that: The step of dynamically adjusting the signal processing strategy and the site coordination strategy by using the reinforcement learning algorithm comprises: Define the dynamic optimization objective function, with the goal of minimizing the lightning source location error and maximizing the system response speed, and establish the optimization relationship between signal processing and site coordination strategy; Construct a reinforcement learning model, use the intensity of lightning signals, site status, weather changes and other input parameters as the state space, and dynamically adjust the signal processing strategy and site weights; The optimal strategy is determined using a reinforcement learning algorithm, and the action space is defined as adjusting site collaboration weights, dynamically updating filter parameters, and optimizing signal processing procedures; Define reward and penalty functions, use key performance indicators such as positioning error, processing delay, and signal integrity as reward or penalty conditions to guide the algorithm optimization direction; Adjust system configuration in real time based on optimization results, including reallocating site computing tasks, updating key parameters of signal processing algorithms, and evaluating the improvements in positioning accuracy and response speed after adjustments; The dynamic optimization model is continuously trained and updated online to adapt to different lightning activity patterns and environmental changes.

8. The method for lightning protection detection based on radio signals of a weather station according to claim 1, characterized in that: The position estimation of the lightning source comprises the following steps: Initialize the geographic coordinates and time synchronization parameters of the site, and collect the lightning signal time data received at each site; Construct a positioning model based on the geometric relationship between sites, and use the spatial distribution of sites and the time difference of received signals to calculate the initial lightning source location; According to the error propagation characteristics of the positioning model, the time difference and geometric position error between stations are quantified and an error correction function is established. Adopting iterative calculation method and combining dynamic correction of signal propagation model, the initial position is updated and optimized multiple times, gradually approaching the precise three-dimensional spatial coordinates of the lightning source; The consistency of the final position estimation result is verified by comparing the signal propagation time received by the site with the propagation path calculation result of the estimated position to ensure that the positioning result conforms to the physical propagation law; The optimized lightning source location is output in the form of three-dimensional spatial coordinates, and the data is used for lightning protection warning and lightning activity analysis.

9. The method for lightning protection detection based on radio signals of a weather station according to claim 1, characterized in that: The step of receiving electromagnetic wave signals generated by lightning discharge in real time through radio receiving equipment of multiple weather stations and obtaining characteristic data of time, frequency and intensity of the signals comprises: Deploy three weather stations and equip them with radio signal receiving equipment to ensure that the distribution of weather stations can cover the target monitoring area; Each weather station is equipped with a high-sensitivity broadband antenna and receiving device to capture the electromagnetic wave signals generated by lightning discharges and ensure that the receiving equipment has a low signal-to-noise ratio; Collect lightning signal data in real time at each weather station, including the signal’s arrival time, frequency distribution, and waveform characteristics of signal strength; The signal data received by each weather station is uploaded to the central data processing module through a high-speed data transmission network, and the timestamp is recorded to ensure the time synchronization of the data; Perform preliminary screening on the received signal data to filter out non-target signals and obvious environmental noise interference, providing reliable input data for subsequent signal propagation model establishment and positioning calculation; According to the signals received in real time, the subsequent signal propagation correction and lightning source location steps are triggered to ensure the high timeliness and stability of signal acquisition.

10. The method for lightning protection detection based on radio signals of a weather station according to claim 1, characterized in that: The precise location of the lightning source is output as three-dimensional coordinates for subsequent processing and analysis by the lightning protection warning system.

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