A method and system for synchronous transmission of emergency broadcast

Abstract

The present application relates to the technical field of broadcast mobile intelligent terminals, and specifically to a method and system for synchronous transmission and reporting of emergency broadcast, which includes: collecting emergency broadcast signals received by a signal receiver in a campus area, collecting the electromagnetic intensity at each moment in the campus area, obtaining the electromagnetic interference consistency factor and interference correlation index of the emergency broadcast signal, determining the electromagnetic fluctuation weight of the emergency broadcast signal, obtaining the local frequency risk index and electromagnetic interference potential risk index of the emergency broadcast signal, determining the electromagnetic interference intensity of the emergency broadcast signal, and denoising the emergency broadcast signal received by the signal receiver in combination with a filtering algorithm, and synchronously transmitting and reporting the denoised emergency broadcast signal using a broadcast synchronous transmission mechanism. This improves the accuracy of synchronous transmission and reporting of emergency broadcast signals.

Description

Technical Field

[0001] The present application relates to the technical field of broadcast mobile intelligent terminals, and in particular to a method and system for synchronous transmission of emergency broadcasts. Background Art

[0002] In the modern educational environment, schools are crowded places, so the perfection of their emergency management systems is of vital importance. The application of emergency broadcasting systems in schools is one of the key measures to ensure the safety of teachers and students and maintain campus order. Through the emergency broadcasting system on campus, key information and instructions can be quickly and accurately transmitted to all teachers and students in an emergency, providing a strong guarantee for building a harmonious and safe campus environment.

[0003] During the synchronous transmission of campus emergency broadcasts, the transmission of wireless signals may be interfered by a variety of external factors. When the frequency used by the emergency broadcast system conflicts with other wireless devices on campus, such as Wi-Fi routers, mobile phone signal towers, Bluetooth devices, etc., signal interference may occur. This interference may cause the attenuation of the emergency broadcast signal, causing the emergency broadcast signal to be distorted, resulting in low accuracy of the synchronous transmission of emergency broadcasts. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide an emergency broadcast synchronous transmission and reporting method and system, and the technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides an emergency broadcast synchronous transmission and reporting method, the method comprising the following steps:

[0006] (1) Collecting the emergency broadcast signal received by the signal receiver in the target area, collecting the electromagnetic intensity at each moment at the signal receiver in the target area, and combining the electromagnetic intensity in a preset time period before the signal receiver receives the emergency broadcast signal and the electromagnetic intensity in a time interval when the signal receiver receives the emergency broadcast signal to form an electromagnetic intensity signal;

[0007] (2) The electromagnetic intensity signal is divided into different categories, and the similarities and differences of the electromagnetic intensity of different categories in the electromagnetic intensity signal are analyzed to determine the electromagnetic interference consistency factor of the emergency broadcast signal; the autocorrelation of the electromagnetic intensity signal and the time difference between the electromagnetic intensity of different categories are analyzed to obtain the interference correlation index of the emergency broadcast signal; the electromagnetic fluctuation weight of the emergency broadcast signal is obtained by combining the electromagnetic interference consistency factor and the interference correlation index;

[0008] (3) analyzing the frequency domain amplitude distribution of the electromagnetic intensity within the time interval, screening the frequencies in the frequency domain, calculating the spectrum density of the remaining frequencies screened, and determining the local frequency risk index of the emergency broadcast signal; combining the electromagnetic fluctuation weight with the spectrum density to obtain the electromagnetic interference potential risk index of the emergency broadcast signal;

[0009] (4) The electromagnetic interference intensity of the emergency broadcast signal is determined by combining the local frequency risk index and the electromagnetic interference potential risk index. The emergency broadcast signal received by the signal receiver is denoised by combining the filtering algorithm, and the denoised emergency broadcast signal is synchronously transmitted and broadcasted using the broadcast synchronous transmission mechanism.

[0010] In one embodiment, the determination of the electromagnetic interference consistency factor includes:

[0011] The electromagnetic intensity signal is divided into clusters using a clustering algorithm, the difference between the mean of all electromagnetic intensities in the time interval and the mean of all electromagnetic intensities in the last cluster is calculated, recorded as a first difference, the difference between the number of all electromagnetic intensities in the time interval and the number of all electromagnetic intensities in the last cluster is calculated, recorded as a second difference, and the electromagnetic interference consistency factor is determined by combining the first difference and the second difference;

[0012] The electromagnetic interference consistency factor is negatively correlated with the first difference and positively correlated with the second difference.

[0013] In one embodiment, determining the interference correlation index includes:

[0014] Calculate the average value of all autocorrelation coefficients of the electromagnetic intensity signal at a preset order, calculate the metric distance between the last cluster and the remaining clusters, forward fuse all the metric distances, and determine the interference correlation index based on the result of the forward fusion and the average value;

[0015] The interference correlation index is positively correlated with the average value, and negatively correlated with the result of the forward fusion.

[0016] In one embodiment, the electromagnetic fluctuation weight is a forward fusion result of the electromagnetic interference consistency factor and the interference correlation index.

[0017] In one embodiment, the screening is:

[0018] The difference between the maximum peak value and the minimum valley value in the frequency domain is calculated and recorded as the third difference. The preset percentage of the third difference is used as the screening threshold. The amplitude of the frequency in the frequency domain whose amplitude is less than or equal to the screening threshold is set to 0, and the frequency whose amplitude is not 0 is used as the remaining frequency after screening.

[0019] In one embodiment, the determination of the local frequency risk index includes:

[0020] Calculate the difference between the number of the remaining frequencies and the number of all frequencies in the frequency domain, record it as the fourth difference, take the frequencies in the frequency domain whose number of continuous non-zero frequencies is greater than or equal to 2 as a non-zero frequency band, calculate the difference between the number of the remaining frequencies and the number of the non-zero frequency bands, record it as the fifth difference, and determine the local frequency risk index by combining the fourth difference and the fifth difference;

[0021] The local frequency risk index is positively correlated with the fourth difference and the fifth difference.

[0022] In one embodiment, the electromagnetic interference potential risk index is a forward fusion result of the electromagnetic fluctuation weight and the spectrum density.

[0023] In one embodiment, the electromagnetic interference intensity is a forward fusion result of the local frequency risk index and the electromagnetic interference potential risk index.

[0024] In one embodiment, the denoising of the emergency broadcast signal received by the signal receiver includes:

[0025] The received emergency broadcast signal is segmented at preset time intervals, and the emergency broadcast signal in each time period is used as the input of the filtering algorithm, and the output is the denoised emergency broadcast signal in each time period, wherein the gain coefficient of the filtering algorithm is the forward fusion result of the normalized value of the electromagnetic interference intensity of the emergency broadcast signal in each time period and the gain coefficient of the filtering algorithm in the previous time period.

[0026] In the second aspect, an embodiment of the present application also provides an emergency broadcast synchronous transmission and announcement system, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the above methods are implemented.

[0027] This application has at least the following beneficial effects:

[0028] The present application collects emergency broadcast signals received by signal receivers in the campus area, collects electromagnetic strength at each moment in the campus area, and composes an electromagnetic strength signal from the electromagnetic strength in a preset time period before the signal receiver receives the emergency broadcast signal and the electromagnetic strength in the time interval when the signal receiver receives the emergency broadcast signal. The electromagnetic strength signal is divided into different categories, and the similarities and differences of electromagnetic strengths of different categories in the electromagnetic strength signal are analyzed to determine the electromagnetic interference consistency factor of the emergency broadcast signal, which reflects the similarity between the electromagnetic strength in the time interval of the emergency broadcast signal and the electromagnetic strength in the last category. When receiving the emergency broadcast signal, the consistency of the current electromagnetic interference environment and the past electromagnetic interference environment is determined. The larger the electromagnetic interference consistency factor, the more similar the current electromagnetic environment is to the electromagnetic environment in the last cluster, thereby improving the reliability of the electromagnetic interference environment analysis. The autocorrelation of the electromagnetic strength signal and the time gap between electromagnetic strengths of different categories are analyzed to obtain the interference correlation index of the emergency broadcast signal, which reflects the periodicity and similarity between the last category and other categories. The larger the interference correlation index, the stronger the correlation between different electromagnetic interference types, indicating that the electromagnetic interference has a higher repeatability in the time series. The electromagnetic interference consistency factor and the interference correlation index are combined to obtain the electromagnetic interference consistency factor of the emergency broadcast signal. The electromagnetic fluctuation weight reflects the potential impact of the current electromagnetic interference on the reception quality of the emergency broadcast signal, and improves the accuracy of the electromagnetic interference impact degree measurement; analyzes the frequency domain amplitude distribution of the electromagnetic intensity in the time interval when the emergency broadcast signal is received, screens the frequency in the frequency domain, calculates the spectrum density of the remaining frequencies screened, and determines the local frequency risk index of the emergency broadcast signal; reflects the degree to which the local detail position of the emergency broadcast signal is affected by electromagnetic interference, and improves the accuracy of distinguishing different types of electromagnetic interference; combines the electromagnetic fluctuation weight with the spectrum density to obtain the electromagnetic interference potential risk index of the emergency broadcast signal, evaluates the potential impact of high-intensity frequency components in the frequency domain on the reception quality of the broadcast signal, and combines the local frequency risk index with the electromagnetic interference potential risk index to determine the electromagnetic interference intensity of the emergency broadcast signal, which comprehensively reflects the degree of electromagnetic interference received in the time interval of the emergency broadcast signal reception, and improves the accuracy of the electromagnetic interference measurement; combines the electromagnetic interference intensity with the filtering algorithm to denoise the emergency broadcast signal received by the signal receiver, and uses the broadcast synchronous transmission mechanism to synchronously transmit and broadcast the denoised emergency broadcast signal, which improves the accuracy of the filtering algorithm for denoising the emergency broadcast signal, improves the transmission quality of the emergency broadcast signal, and thereby improves the accuracy and stability of the emergency broadcast synchronous transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 A flowchart of a method for synchronous transmission of emergency broadcasts provided in accordance with an embodiment of the present application;

[0031] Figure 2 Construct a flow chart for electromagnetic interference intensity. DETAILED DESCRIPTION

[0032] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the emergency broadcast synchronous transmission and reporting method and system proposed in accordance with the present application, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0033] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0034] The following is a detailed description of a specific scheme of an emergency broadcast synchronous transmission and reporting method and system provided by the present application in conjunction with the accompanying drawings.

[0035] See also Figure 1 , which shows a flowchart of a method for synchronous transmission of emergency broadcasting provided by an embodiment of the present application, the method comprising the following steps:

[0036] Step (1) collects the emergency broadcast signal received by the signal receiver in the campus area, collects the electromagnetic strength at each time in the campus area, and combines the electromagnetic strength in a preset time period before the signal receiver receives the emergency broadcast signal and the electromagnetic strength in the time interval when the signal receiver receives the emergency broadcast signal to form an electromagnetic strength signal.

[0037] In order to eliminate the impact of electromagnetic interference in the broadcast signals received by the campus emergency broadcast system, the same low-frequency electromagnetic sensor equipped with a data acquisition instrument is used to continuously collect the electromagnetic intensity near all broadcast signal receivers in the campus. In one embodiment of the present application, the collection interval is 0.01s, and the implementer can set it according to the actual situation. This application does not impose any restrictions here.

[0038] While collecting the electromagnetic intensity, a broadcast signal receiver is used to collect the emergency broadcast signal in the campus area. The moment when the broadcast signal receiver receives the emergency broadcast signal is taken as the starting moment of the emergency broadcast signal. All electromagnetic intensities collected within the preset time period before the starting moment of the emergency broadcast signal, as well as all electromagnetic intensities collected within the time interval from the starting moment to the end moment of the emergency broadcast signal, are combined into an electromagnetic intensity signal in chronological order. Each element in the electromagnetic intensity signal is the electromagnetic intensity at each collection moment.

[0039] In one embodiment of the present application, the preset time period is 1 hour. The implementer can set the length of the preset time period according to actual conditions, and the present application does not impose any limitation thereto.

[0040] Due to the complex and changeable campus environment, electromagnetic interference sources may include electronic equipment inside the campus, electronic equipment in surrounding buildings, etc. The electromagnetic radiation intensity and frequency of these interference sources may change over time. Therefore, relying solely on the electromagnetic intensity collected during the time period when the emergency broadcast signal is received may not be able to fully reflect the distribution pattern of electromagnetic interference. Therefore, all electromagnetic intensities collected within the preset time period are analyzed comprehensively.

[0041] Step (2) divides the electromagnetic intensity signal into different categories, analyzes the similarities and differences of electromagnetic intensities of different categories in the electromagnetic intensity signal, and determines the electromagnetic interference consistency factor of the emergency broadcast signal; analyzes the autocorrelation of the electromagnetic intensity signal and the time difference between electromagnetic intensities of different categories to obtain the interference correlation index of the emergency broadcast signal; and combines the electromagnetic interference consistency factor with the interference correlation index to obtain the electromagnetic fluctuation weight of the emergency broadcast signal.

[0042] In order to deeply analyze the interference characteristics and time evolution patterns in the electromagnetic intensity signal, in one embodiment of the present application, the electromagnetic intensity signal is used as the input of the DBSCAN clustering algorithm, and the output is clustering clusters of different time ranges, that is, all electromagnetic intensities in the electromagnetic intensity signal on the time series are intercepted as data clusters, and the necessary parameters in the DBSCAN clustering algorithm are set to 5 for the minimum number of points and 0.3 for the neighborhood radius. The implementer can set them according to the actual situation, and the present application does not limit this. The DBSCAN clustering algorithm is an existing well-known technology, and the present application will not be described in detail here.

[0043] It should be noted that, on the premise that all electromagnetic intensities in the electromagnetic intensity signal can be divided into different categories, that is, the present embodiment divides the electromagnetic intensity signal into clusters using the DBSCAN clustering algorithm, the implementer can choose other existing possible algorithms according to actual conditions, for example, K-means clustering algorithm, region growing algorithm, etc., and this application does not impose any restrictions here.

[0044] Each cluster obtained in this application may represent a type of electromagnetic interference. Since the time interval of the emergency broadcast signal is in the latter part of the electromagnetic intensity signal, the last cluster in the electromagnetic intensity signal, that is, the cluster at the end of the time interval close to the emergency broadcast signal, corresponds to a time period. The difference between the mean of all electromagnetic intensities in the time interval of the emergency broadcast signal and the mean of all electromagnetic intensities in the last cluster is calculated as the first difference. The difference between the number of all electromagnetic intensities in the time interval of the emergency broadcast signal and the number of all electromagnetic intensities in the last cluster is calculated as the second difference. The electromagnetic interference consistency factor of the emergency broadcast signal is determined by combining the first difference and the second difference.

[0045] Among them, the electromagnetic interference consistency factor of the emergency broadcast signal is negatively correlated with the first difference and positively correlated with the second difference.

[0046] It should be understood that the difference indicates the degree of difference between two variables, which can be specifically a difference, an absolute value of a difference, a ratio, etc. A positive correlation indicates that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases, such as a multiplication relationship, an addition relationship, and the power of an exponential function. A negative correlation indicates that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases, such as a subtraction relationship, a division relationship, etc.

[0047] In one embodiment of the present application, the absolute value of the difference between the mean of all electromagnetic intensities within the time interval of the emergency broadcast signal and the mean of all electromagnetic intensities in the last cluster is calculated, which is recorded as the first difference. The ratio of the number of all electromagnetic intensities within the time interval of the emergency broadcast signal to the number of all electromagnetic intensities in the last cluster is calculated, which is recorded as the second difference. The ratio of the second difference to the first difference is used as the electromagnetic interference consistency factor of the emergency broadcast signal.

[0048] The larger the value of the first difference is, the greater the difference between the electromagnetic intensity in the time interval of the emergency broadcast signal and the electromagnetic intensity in the last cluster, and the smaller the consistency of the corresponding electromagnetic interference is. Therefore, the smaller the electromagnetic interference consistency factor is. The larger the value of the second difference is, the greater the proportion of the number of electromagnetic intensities in the time interval of the emergency broadcast signal in the last cluster, the more likely it is that they belong to the same type of electromagnetic interference, and the stronger the consistency of the electromagnetic interference is. Therefore, the larger the electromagnetic interference consistency factor is.

[0049] Calculate the average value of all autocorrelation coefficients of the electromagnetic intensity signal at a preset order, calculate the metric distance between the last cluster and the remaining clusters, forward fuse all the metric distances, and determine the interference correlation index of the emergency broadcast signal based on the forward fusion result and the average value;

[0050] The interference correlation index of the emergency broadcast signal is positively correlated with the average value, and negatively correlated with the forward fusion result.

[0051] In one embodiment of the present application, the preset order is from 2 to half of the number of electromagnetic intensities in the electromagnetic intensity signal. The cluster center of the cluster represents the middle position in a cluster. If the number of data in the cluster is an even number, the data of the first position of the two middle positions of the cluster is used as the cluster center of the cluster.

[0052] It should be noted that the metric distance represents the gap or interval between two variables, which can be calculated using Euclidean distance, Manhattan distance, DTW distance, etc. Forward fusion means combining multiple variables with an overall amplification effect, which can be specifically addition, multiplication, etc.

[0053] In one embodiment of the present application, the time interval between the cluster center of the last cluster and the cluster centers of the remaining clusters is calculated, the DTW distance between the last cluster and the remaining clusters is calculated, and the weighted sum and average value of all the DTW distances of the last cluster are calculated using the time interval as a weight. The ratio of the average value of all autocorrelation coefficients of the electromagnetic intensity signal at a preset order to the weighted sum and average value is used as the interference correlation index of the emergency broadcast signal.

[0054] The larger the average value of all autocorrelation coefficients of the electromagnetic intensity signal at the preset order, the stronger the autocorrelation of the last cluster under different time delays, reflecting the inherent periodicity and stability of the electromagnetic intensity signal, as well as the changing trend of the electromagnetic intensity signal. Correspondingly, the larger the interference correlation index of the emergency broadcast signal is. The larger the average value of the weighted sum is, the less similar the last cluster is to other clusters in time series, and the possibility of correlation between clusters is weaker. Therefore, the smaller the interference correlation index of the emergency broadcast signal is.

[0055] According to the electromagnetic interference consistency factor and interference correlation index of the emergency broadcast signal, the electromagnetic fluctuation weight of the emergency broadcast signal is determined. Specifically, the forward fusion result of the electromagnetic interference consistency factor and the interference correlation index of the emergency broadcast signal is used as the electromagnetic fluctuation weight of the emergency broadcast signal.

[0056] As an embodiment of the present application, the product of the electromagnetic interference consistency factor of the emergency broadcast signal and the interference correlation index is used as the electromagnetic fluctuation weight of the emergency broadcast signal.

[0057] The electromagnetic interference consistency factor reflects the similarity between the electromagnetic intensity within the time interval of the emergency broadcast signal and the electromagnetic intensity in the last cluster. When receiving the emergency broadcast signal, the current electromagnetic interference environment is consistent with the past electromagnetic interference environment. The larger the electromagnetic interference consistency factor, the more similar the current electromagnetic environment is to the electromagnetic environment in the last cluster. The interference correlation index reflects the periodicity and similarity between the last cluster and other clusters. The larger the interference correlation index, the stronger the correlation between different electromagnetic interference types, indicating that the electromagnetic interference has a higher repeatability in the time series.

[0058] The electromagnetic fluctuation weight combines the consistency between electromagnetic interference and the correlation between different types of electromagnetic interference, reflecting the potential impact of current electromagnetic interference on the reception quality of emergency broadcast signals.

[0059] Step (3) analyzes the frequency domain amplitude distribution of the electromagnetic intensity within the time interval of the emergency broadcast signal, screens the frequencies in the frequency domain, calculates the spectrum density of the remaining frequencies after screening, and determines the local frequency risk index of the emergency broadcast signal; and combines the electromagnetic fluctuation weight with the spectrum density to obtain the electromagnetic interference potential risk index of the emergency broadcast signal.

[0060] In order to further analyze the impact of electromagnetic interference within the time interval of receiving the emergency broadcast signal, all electromagnetic intensities within the time interval of receiving the emergency broadcast signal are converted to the frequency domain using the fast Fourier transform algorithm, and the difference between the maximum peak and the minimum valley in the frequency domain is calculated, recorded as the third difference, and the value of the preset percentage of the third difference is used as the screening threshold, and the amplitude of the frequency in the frequency domain whose amplitude is less than or equal to the screening threshold is set to 0, and the frequency whose amplitude is not 0 is used as the remaining frequency after screening. The fast Fourier transform algorithm is an existing well-known technology, and this application will not be described in detail here.

[0061] It should be noted that the fast Fourier transform algorithm is only used as a frequency domain analysis algorithm. On the premise that the purpose of frequency domain conversion can be achieved, the implementer can choose other existing feasible frequency domain analysis algorithms, such as the Fourier transform algorithm, according to actual conditions. This application does not impose any restrictions on this.

[0062] In one embodiment of the present application, the difference between the maximum peak and the minimum valley in the frequency domain of all electromagnetic intensities within the time interval of receiving the emergency broadcast signal is calculated and recorded as the third difference. 50% of the difference between the maximum peak and the minimum valley is used as the screening threshold to determine the remaining frequency after screening.

[0063] Calculate the difference between the number of the remaining frequencies and the number of all frequencies in the frequency domain, record it as the fourth difference, take the frequencies in the frequency domain whose number of continuous non-zero frequencies is greater than or equal to 2 as a non-zero frequency band, calculate the difference between the number of the remaining frequencies and the number of the non-zero frequency bands, record it as the fifth difference, and determine the local frequency risk index of the emergency broadcast signal by combining the fourth difference and the fifth difference;

[0064] The local frequency risk index of the emergency broadcast signal is positively correlated with the fourth difference and the fifth difference.

[0065] In one embodiment of the present application, the ratio of the number of remaining frequencies to the number of all frequencies in the frequency domain is calculated and recorded as the fourth difference, and the ratio of the number of remaining frequencies to the number of non-zero frequency bands is calculated and recorded as the fifth difference. The product of the fourth difference and the fifth difference is used as the local frequency risk index of the emergency broadcast signal.

[0066] The fourth difference reflects the probability of occurrence of high-intensity frequency components in the frequency domain, indicating the concentration of energy distribution in the frequency domain signal. The larger the fourth difference is, the higher the probability of occurrence of high-intensity frequency components is, and the frequency domain signal may be subject to more local interference. Therefore, the local frequency risk index is larger. Furthermore, the number of non-zero frequency components reflects the complexity of the frequency domain signal. The larger the fifth difference is, the more discrete high-intensity frequency components there are, and the greater the risk of electromagnetic interference. Therefore, the local frequency risk index is larger.

[0067] The spectrum density of the frequency domain signals of all electromagnetic intensities within the time interval of receiving the emergency broadcast signal is calculated, and the electromagnetic interference potential risk index of the emergency broadcast signal is determined by combining the electromagnetic fluctuation weight of the emergency broadcast signal with the spectrum density.

[0068] In one embodiment of the present application, the electromagnetic interference potential risk index of the emergency broadcast signal is the product of the electromagnetic fluctuation weight of the emergency broadcast signal and the spectrum density.

[0069] Among them, the greater the weight of electromagnetic fluctuations, the stronger the potential impact of the current electromagnetic interference on the quality of broadcast signal reception; the greater the spectrum density, the stronger the electromagnetic interference in the frequency domain; the greater the potential risk, the greater the electromagnetic interference potential risk index.

[0070] Step (4) combines the local frequency risk index and the electromagnetic interference potential risk index to determine the electromagnetic interference intensity of the emergency broadcast signal, combines the filtering algorithm to denoise the emergency broadcast signal received by the signal receiver, and uses the broadcast synchronous transmission mechanism to synchronously transmit and broadcast the denoised emergency broadcast signal.

[0071] In one embodiment of the present application, the product of the local frequency risk index of the emergency broadcast signal and the electromagnetic interference potential risk index is used as the electromagnetic interference intensity of the emergency broadcast signal. Figure 2 shown.

[0072] The electromagnetic interference potential risk index reflects the potential risk of electromagnetic interference to emergency broadcast signals, and the local frequency risk index reflects the local risk of electromagnetic interference to emergency broadcast signals. The product of the two reflects the degree of impact of electromagnetic interference on emergency broadcast signals during reception.

[0073] As an embodiment of the present application, the emergency broadcast signal received by the broadcast signal receiver is processed in segments at preset time intervals. In the first time period of the emergency broadcast signal, the emergency broadcast signal in the first time period is denoised using the original Kalman filter algorithm. For the emergency broadcast signal in each subsequent time period, the gain coefficient in the Kalman filter algorithm is adjusted and optimized in combination with the electromagnetic interference intensity of the emergency broadcast signal. Specifically, taking the emergency broadcast signal in the nth time period as an example, the normalized value of the electromagnetic interference intensity of the emergency broadcast signal in the nth time period is calculated, and the product of the normalized value and the gain coefficient in the filtering algorithm in the nth time period is used as the gain coefficient in the filtering algorithm in the n+1th time period. After obtaining the gain coefficient in the filtering algorithm in each time period, the emergency broadcast signal in each time period is denoised using the Kalman filter algorithm to obtain the denoised emergency broadcast signal. The Kalman filter algorithm is an existing well-known technology, and this application will not be described in detail here. When calculating the normalized value of the electromagnetic interference intensity, this embodiment uses the sigmoid function for calculation. The implementer can select other existing feasible normalization algorithms according to actual conditions, and this application does not limit this.

[0074] The adjusted and optimized gain coefficient can adapt to different electromagnetic interference environments, remove noise while improving the transmission quality of emergency broadcast signals, and ensure the stability and accuracy of emergency broadcast signal transmission.

[0075] Among them, the preset time interval in this embodiment is 0.5s, and the implementer can set it according to the actual situation, and this application does not limit it here.

[0076] It should be noted that the Kalman filter algorithm is only one embodiment provided in this application. Under the conditions that the emergency broadcast signal can be denoised and has a gain coefficient, the implementer can choose other existing feasible filtering algorithms according to actual conditions, and this application does not impose any restrictions here.

[0077] The denoised emergency broadcast signal is synchronously transmitted and broadcasted using the Periodic Advertising Sync Transfer (PAST) mechanism, wherein the PAST mechanism is a known technology and will not be described in detail in this application.

[0078] In summary, the present application collects emergency broadcast signals received by signal receivers in the campus area, collects electromagnetic strength at each moment in the campus area, and combines the electromagnetic strength within a preset time period before the signal receiver receives the emergency broadcast signal, and the electromagnetic strength within the time interval when the signal receiver receives the emergency broadcast signal, to form an electromagnetic strength signal, divides the electromagnetic strength signal into different categories, analyzes the similarities and differences of electromagnetic strengths of different categories in the electromagnetic strength signal, determines the electromagnetic interference consistency factor of the emergency broadcast signal, reflects the similarity between the electromagnetic strength within the time interval of the emergency broadcast signal and the electromagnetic strength in the last category, and when receiving the emergency broadcast signal, the consistency of the current electromagnetic interference environment and the past electromagnetic interference environment. The larger the electromagnetic interference consistency factor, the more similar the current electromagnetic environment is to the electromagnetic environment in the last cluster, thereby improving the reliability of the electromagnetic interference environment analysis; analyzes the autocorrelation of the electromagnetic strength signal and the time gap between electromagnetic strengths of different categories, and obtains the interference correlation index of the emergency broadcast signal, which reflects the periodicity and similarity between the last category and other categories. The larger the interference correlation index, the stronger the correlation between different electromagnetic interference types, indicating that electromagnetic interference has a higher repeatability in the time series; combines the electromagnetic interference consistency factor and the interference correlation index to obtain the emergency broadcast signal. The electromagnetic fluctuation weight of the signal reflects the potential impact of the current electromagnetic interference on the reception quality of the emergency broadcast signal, and improves the accuracy of measuring the impact of electromagnetic interference; analyzes the frequency domain amplitude distribution of the electromagnetic intensity within the time interval when the emergency broadcast signal is received, screens the frequencies in the frequency domain, calculates the spectrum density of the remaining frequencies, and determines the local frequency risk index of the emergency broadcast signal; reflects the degree to which the local detail positions of the emergency broadcast signal are affected by electromagnetic interference, and improves the accuracy of distinguishing different types of electromagnetic interference; combines the electromagnetic fluctuation weight with the spectrum density to obtain the electromagnetic interference potential risk index of the emergency broadcast signal, and evaluates the high-intensity frequency components in the frequency domain. The potential impact on the reception quality of broadcast signals is determined by combining the local frequency risk index and the electromagnetic interference potential risk index to determine the electromagnetic interference intensity of the emergency broadcast signal, which comprehensively reflects the degree of electromagnetic interference during the time period of emergency broadcast signal reception and improves the accuracy of electromagnetic interference measurement. The electromagnetic interference intensity is combined with the filtering algorithm to denoise the emergency broadcast signal received by the signal receiver, and the denoised emergency broadcast signal is synchronously transmitted and broadcasted using the broadcast synchronous transmission mechanism, which improves the accuracy of the filtering algorithm for denoising the emergency broadcast signal, improves the transmission quality of the emergency broadcast signal, and thereby improves the accuracy and stability of the emergency broadcast synchronous transmission and broadcasting.

[0079] Based on the same inventive concept as the above method, an embodiment of the present application also provides an emergency broadcast synchronous transmission and announcement system, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, it implements the steps of any one of the above-mentioned emergency broadcast synchronous transmission and announcement methods.

[0080] It should be noted that the above sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above is a description of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0081] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0082] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for synchronous transmission of emergency broadcast, characterized in that: The method comprises the following steps: (1) Collecting the emergency broadcast signal received by the signal receiver in the target area, collecting the electromagnetic intensity at each moment at the signal receiver in the target area, and combining the electromagnetic intensity in a preset time period before the signal receiver receives the emergency broadcast signal and the electromagnetic intensity in a time interval when the signal receiver receives the emergency broadcast signal to form an electromagnetic intensity signal; (2) The electromagnetic intensity signal is divided into different categories, and the similarities and differences of the electromagnetic intensity of different categories in the electromagnetic intensity signal are analyzed to determine the electromagnetic interference consistency factor of the emergency broadcast signal; the autocorrelation of the electromagnetic intensity signal and the time difference between the electromagnetic intensity of different categories are analyzed to obtain the interference correlation index of the emergency broadcast signal; the electromagnetic fluctuation weight of the emergency broadcast signal is obtained by combining the electromagnetic interference consistency factor and the interference correlation index; (3) analyzing the frequency domain amplitude distribution of the electromagnetic intensity within the time interval, screening the frequencies in the frequency domain, calculating the spectrum density of the remaining frequencies screened, and determining the local frequency risk index of the emergency broadcast signal; combining the electromagnetic fluctuation weight with the spectrum density to obtain the electromagnetic interference potential risk index of the emergency broadcast signal; (4) Determine the electromagnetic interference intensity of the emergency broadcast signal by combining the local frequency risk index and the electromagnetic interference potential risk index, denoise the emergency broadcast signal received by the signal receiver by combining the filtering algorithm, and synchronously transmit and broadcast the denoised emergency broadcast signal using the broadcast synchronous transmission mechanism; The determination of the electromagnetic interference consistency factor includes: The electromagnetic intensity signal is divided into clusters using a clustering algorithm, the difference between the mean of all electromagnetic intensities in the time interval and the mean of all electromagnetic intensities in the last cluster is calculated, recorded as a first difference, the difference between the number of all electromagnetic intensities in the time interval and the number of all electromagnetic intensities in the last cluster is calculated, recorded as a second difference, and the electromagnetic interference consistency factor is determined by combining the first difference and the second difference; The electromagnetic interference consistency factor is negatively correlated with the first difference and positively correlated with the second difference; The determination of the interference correlation index includes: Calculate the average value of all autocorrelation coefficients of the electromagnetic intensity signal at a preset order, calculate the metric distance between the last cluster and the remaining clusters, forward fuse all the metric distances, and determine the interference correlation index based on the result of the forward fusion and the average value; The interference correlation index is positively correlated with the average value, and negatively correlated with the result of the forward fusion.

2. The method for synchronous transmission of emergency broadcast according to claim 1, characterized in that: The electromagnetic fluctuation weight is a forward fusion result of the electromagnetic interference consistency factor and the interference correlation index.

3. The method for synchronous transmission of emergency broadcast according to claim 1, characterized in that: The screening is: The difference between the maximum peak value and the minimum valley value in the frequency domain is calculated and recorded as the third difference. The preset percentage of the third difference is used as the screening threshold. The amplitude of the frequency in the frequency domain whose amplitude is less than or equal to the screening threshold is set to 0, and the frequency whose amplitude is not 0 is used as the remaining frequency after screening.

4. The method for synchronous transmission of emergency broadcast as claimed in claim 3, characterized in that: The determination of the local frequency risk index includes: Calculate the difference between the number of the remaining frequencies and the number of all frequencies in the frequency domain, record it as the fourth difference, take the frequencies in the frequency domain whose number of continuous non-zero frequencies is greater than or equal to 2 as a non-zero frequency band, calculate the difference between the number of the remaining frequencies and the number of the non-zero frequency bands, record it as the fifth difference, and determine the local frequency risk index by combining the fourth difference and the fifth difference; The local frequency risk index is positively correlated with the fourth difference and the fifth difference.

5. The method for synchronous transmission of emergency broadcast according to claim 1, characterized in that: The electromagnetic interference potential risk index is a forward fusion result of the electromagnetic fluctuation weight and the spectrum density.

6. The method for synchronous transmission of emergency broadcast according to claim 1, characterized in that: The electromagnetic interference intensity is a forward fusion result of the local frequency risk index and the electromagnetic interference potential risk index.

7. The method for synchronous transmission of emergency broadcast according to claim 1, characterized in that: The denoising of the emergency broadcast signal received by the signal receiver comprises: The received emergency broadcast signal is segmented at preset time intervals, and the emergency broadcast signal in each time period is used as the input of the filtering algorithm, and the output is the denoised emergency broadcast signal in each time period, wherein the gain coefficient of the filtering algorithm is the forward fusion result of the normalized value of the electromagnetic interference intensity of the emergency broadcast signal in each time period and the gain coefficient of the filtering algorithm in the previous time period.

8. An emergency broadcast synchronous transmission and announcement system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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