CN114398240A

CN114398240A - Electromagnetic environment monitoring system

Info

Publication number: CN114398240A
Application number: CN202210071706.1A
Authority: CN
Inventors: 陈飞; 盖武; 陈予诺; 程云柯; 盖昱升; 程晓军
Original assignee: Chengdu Ruinaibo Technology Co ltd
Current assignee: Chengdu Ruinaibo Technology Co ltd
Priority date: 2022-01-21
Filing date: 2022-01-21
Publication date: 2022-04-26

Abstract

The invention discloses an electromagnetic environment monitoring system, which is used for solving the problem that the environment monitoring system in the prior art cannot effectively receive data and efficiently process the data under the condition of more stations and comprises stations and a gathering center, wherein the stations are numerous, the gathering center acquires environmental electromagnetic data through the stations and adopts a C/S framework and comprises a service end and a client end, and the service end is generally divided into electromagnetic environment data acquisition service, electromagnetic environment data analysis service, electromagnetic environment data management service, electromagnetic environment report management service and basic service; the basic service is a group of service packages which are irrelevant to the service, and provides common support for the whole system, and comprises the following steps: the system comprises a message bus, a data storage access service, an operation and maintenance management service and a configuration management service; the client is responsible for calling various services and providing human-computer interaction interfaces such as frequency spectrum display, comparison analysis, report generation, operation and maintenance management, configuration management and the like for the user.

Description

Electromagnetic environment monitoring system

Technical Field

The invention belongs to the field of electromagnetic environment monitoring, and particularly relates to an electromagnetic environment monitoring system.

Background

In recent years, short-distance and low-power radio communication services are rapidly developed, various new services combined with the internet are widely popularized and used, higher requirements are provided for fine monitoring and management of radio frequency spectrum resources, the development direction of a future electromagnetic spectrum monitoring network system is that a traditional electromagnetic environment monitoring system mainly collects electromagnetic waves through data acquisition devices which are dispersedly arranged, and required parameters are obtained through data analysis, but the traditional electromagnetic environment monitoring system is limited by a network environment when in use, and when a plurality of sites send data simultaneously, a convergence center often causes network blockage and influences data collection.

Disclosure of Invention

The invention aims to provide an electromagnetic environment monitoring system which can reduce the influence of network fluctuation on data transmission and improve the accuracy of data through electromagnetic environment dynamic element analysis and electromagnetic environment calibration technology.

In order to achieve the purpose, the invention adopts the following technical scheme:

an electromagnetic environment monitoring system comprising: the system comprises a gathering center and stations, wherein the electromagnetic environment spectrum data of each station are transmitted back to the gathering center through continuously collecting the electromagnetic environment spectrum data around the stations, and are analyzed in the gathering center.

The presentation layer is a client provided with a corresponding functional module;

the service layer comprises: the service interface and the message bus encapsulate the operation of the service logic into a simple API interface and expose the simple API interface to the presentation layer, and the two parties access the API interface based on a communication protocol to realize the decoupling of the service and the calling party;

the service layer comprises: the system comprises an electromagnetic environment data processing service, an electromagnetic environment data management service and an electromagnetic environment data report management service;

the data access layer realizes data distribution by using a message bus, and the data access layer comprises the following steps: the system comprises a data storage access service, an electromagnetic environment data acquisition service and a database; the data storage access service is an abstract layer positioned between a business module and a database, decoupling between the business module and the database is realized by defining a standard access interface, and the data storage access service is divided into a database connection management module, an antenna parameter access module, a site information parameter access module, a spectrum data access module, a background noise data access module, a large signal interference data access module, an alarm data access module, a working state information recording access module and an operation log recording access module; the business module calls a corresponding data access module to realize the addition, deletion, modification and check of the data; the data management of the data layer mainly comprises the following steps: data playback, data import and export, and data return.

Further, the electromagnetic environment data processing service: the method comprises the following steps: electromagnetic environment interference signal statistical analysis, including: interference signal measurement, interference signal preprocessing and interference signal comparison analysis.

Further, the step of interference signal measurement is explained as follows:

1) setting a minimum allowable signal-to-noise ratio, ignoring signals with a signal-to-noise ratio below this value;

2) acquiring a working frequency point set by a user, and regarding signals close to the working frequency point as interference;

3) searching signals according to the signal-to-noise ratio, starting to search from a frequency spectrum data starting point, and sequentially searching a valley point, a peak point and a valley point to form a signal and recording the signal;

4) processing an incomplete signal of the spectrum ending, and removing in the searching process;

5) calculating the signal bottom noise, comparing the signal bottom noise with the adjacent bottom noise, and judging whether the bottom noise is obviously increased or not;

6) calculating whether the signal amplitude exceeds a large signal reference value;

7) analyzing whether the signal is an interference signal or not according to the working frequency point list;

8) obtaining an interference signal list, wherein interference signal parameters comprise interference frequency points, bandwidth, amplitude and measurement time, and storing and displaying measurement results;

9) and the interference signal measurement and analysis are completed.

Further, the statistical preprocessing of the interference signal comprises the following steps:

1) and (3) interference signal correlation and collection: and establishing an incidence relation between the interference signals with the same frequency of the frequency spectrums at different moments, combining the interference signals into a corresponding signal set, and establishing a signal event linked list.

2) And (3) interference signal base number correlation set: and comparing and analyzing the interference signal and the interference signal base number table, independently collecting the signal change events inconsistent with the base number, and recording the signal change events as an abnormal signal event linked list in a centralized manner.

3) And (3) adjusting parameters such as an interference threshold and the like, and then updating the collection: and updating the associated set data after adjusting parameters such as an interference threshold and the like.

Further, the interference signal alignment analysis: comparing and analyzing the intensity and the quantity of the interference signals in different time periods, frequency bands and places;

a) the client initiates data query according to the current user interface parameters;

b) the server receives the query parameters to perform data statistics and returns a statistical result to the client;

c) and the client displays according to the query result.

Further, the electromagnetic environment data processing service: further comprising: large signal early warning;

the large signal alarm function comprises alarm template generation, large signal measurement and alarm message management, the threshold value of the large signal is configured through the alarm template, the measurement signal is compared with the large signal threshold value, if the threshold value is exceeded, an alarm message is generated, and the alarm signal is stored and displayed through the alarm message management;

the alarm template is composed of two groups of frequency spectrum data, and respectively represents the upper limit and the lower limit of the alarm threshold, the upper limit data is used for detecting a large signal, and the lower limit data can be used for detecting the abnormal condition of the noise bottom.

Further, the main mode of large signal measurement is that energy blocks exceeding a threshold value are detected and recorded, the detected large signals are stored as alarm information in a storage mode one by one, before the alarm information is stored in the storage mode, the alarm information is compared with historical records, states of the alarm information are identified, the states are divided into newly-added alarms and existing alarms, the historical records already exist, and when the alarm marks disappear at the time, the alarm marks are disappearing alarms.

Furthermore, the data access mode of the aggregation center and the stations adopts an on-demand distribution architecture based on a center cache, a center cache is arranged between the client and the stations, the client and the stations are connected with the center cache, the acquired fragment data and the alarm data are transmitted back to the center cache in real time, the cache is performed in the center cache, and all the clients subscribe the real-time data to the center.

The invention has at least the following beneficial effects:

(1) the electromagnetic environment spectrum monitoring device has an electromagnetic environment spectrum monitoring function, can measure the background noise level, displays electromagnetic environment data after statistical analysis is carried out on the collected data, and is convenient for a user to conveniently and flexibly master data information.

(2) The data acquisition and distribution on demand architecture reduces the access load of each site, and the more sites are connected, the more obvious the optimization effect on the bandwidth is.

(3) The acquired data values are analyzed through a dynamic element analysis technology, so that the error of the data values obtained by the two systems is minimum.

(4) Through the electromagnetic environment data calibration technology, the problems that in use, the number of test points is large, the workload of manual test calibration is large, and outfield protection is difficult are solved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention.

In the drawings:

FIG. 1 schematically shows a system configuration diagram of the present invention;

FIG. 2 schematically illustrates artifact median data in various environments;

FIG. 3 schematically shows an electromagnetic environment comparison analysis flow at different time periods;

FIG. 4 schematically illustrates an interference signal measurement analysis flow diagram;

FIG. 5 schematically shows a flow chart of alignment analysis;

FIG. 6 schematically illustrates a report management flow diagram;

FIG. 7 schematically illustrates a message bus interaction diagram with modules;

FIG. 8 is a schematic diagram of an operation and maintenance management flow diagram;

FIG. 9 is a diagram schematically illustrating a client and site access pattern of the prior art;

FIG. 10 is a diagram schematically illustrating client and site access patterns in the present application;

FIG. 11 schematically illustrates a dynamic analytical model UML class diagram;

FIG. 12 schematically illustrates a signal source alignment calibration schematic;

Detailed Description

It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure; 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.

It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application; as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.

Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Spatially relative terms, such as "above … …," "above … …," "above … …, above," "overlying" and the like, may be used herein for ease of description to describe one device or feature's spatial relationship to another device or feature as illustrated in the figures; it will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures.

Examples

An electromagnetic environment monitoring system is used for solving the problem that an environment monitoring system in the prior art cannot effectively receive data and efficiently process the data under the condition of more sites, the application optimizes the use of bandwidth through a framework distributed according to the needs of data acquisition, the data returned by the sites can be effectively received, and the data is effectively acquired and analyzed through a dynamic element analysis technology and an electromagnetic environment data calibration technology and then displayed through a presentation layer; the system comprises a plurality of stations and a gathering center, wherein the stations collect environmental electromagnetic data, the gathering center adopts a C/S (client/server) framework and comprises a service end and a client, and the service end is generally composed of an electromagnetic environment data collection service, an electromagnetic environment data analysis service, an electromagnetic environment data management service, an electromagnetic environment report management service and a basic service; the basic service is a group of service packages which are irrelevant to the service, and provides common support for the whole system, and comprises the following steps: the system comprises a message bus, a data storage access service, an operation and maintenance management service and a configuration management service; the client is responsible for calling various services and providing human-computer interaction interfaces such as frequency spectrum display, comparison analysis, report generation, operation and maintenance management, configuration management and the like for the user.

The principle of the system is as follows: the electromagnetic environment spectrum data of each site is transmitted back to the convergence center by continuously collecting the electromagnetic environment spectrum data around the site, and multi-site comparison analysis can be performed through the electromagnetic environment processing and analyzing service deployed in the convergence center; obtaining artificial background noise according to a standard calculation method, and counting the artificial background noise according to time periods of hours, morning, noon and evening, every day and the like; the spectrum data is analyzed in real time, the large signal interference condition can be measured, and the alarm information is generated in time for the burst interference and pushed to the user; after long-time data accumulation, the background noise can be compared and analyzed according to the span of days, months, quarters, years and the like, and the electromagnetic environment change trend is obtained.

As shown in fig. 1, the system adopts a four-layer architecture of a presentation layer, a service layer, a business layer and a data access layer from top to bottom.

The presentation layer is a client with a corresponding functional module, is implemented by a Windows form, is a mature prior art, and is not described in detail, and in this embodiment, the presentation layer includes: UI component, UI logic component, service agent, storage access agent.

The service layer comprises: the service interface and the message bus are used for packaging the operation of the service logic into a simple API (application program interface) interface (namely the service interface) by utilizing the message bus and exposing the API interface to the presentation layer, and the service interface and the message bus are accessed based on a communication protocol, so that the decoupling of the service and a calling party is realized.

Wherein the message bus is used for data subscription publishing and remote call (RPC); the data storage access service is used for storing and accessing collected data, analysis result data and other auxiliary data; the operation and maintenance management service is used for monitoring and reporting the system state; the configuration management service is used for parameter configuration management of the system.

It should be noted that: as shown in fig. 7, each module of the system realizes data flow by calling a message bus interface, which is not only beneficial to decoupling of calling modes of each module, but also convenient for collecting running states of each module through the message bus, each module periodically publishes the running states through the message bus, and the operation and maintenance module subscribes a running state theme to collect state information, thereby realizing comprehensive monitoring of the system.

The business layer mainly realizes various business functions of the system, including: the system comprises an electromagnetic environment data processing service, an electromagnetic environment data management service and an electromagnetic environment data report management service; wherein the electromagnetic environment data processing service comprises: the method comprises the following steps of electromagnetic environment change trend analysis, electromagnetic environment interference signal statistical analysis and large signal early warning.

Wherein the electromagnetic environment change trend analysis function firstly measures the background noise, and the system tests artificial noise caused by collective unintentional radiation of electrical machinery, electrical and electronic equipment, power transmission lines or ignition of an external combustion engine.

For human artificial noise, data is provided that represents a class of environments showing typical levels of electrical and electronic activity that are normally present within typical distances in the environment.

The noise figure Fa characterizing the level of the artificial noise is calculated as follows:

the noise coefficient of the receiving system is composed of a series of noise sources of a receiving terminal of the system, and an equivalent lossless receiving antenna is the only proper reference point Fa of the overall working noise coefficient of the radio receiving system. The external noise figure is calculated with the average antenna factor:

E＝U+AF dB(V/m)

wherein: e: field strength dB (μ V/m), U: antenna terminal voltage dB (μ V), AF: antenna factor (dB).

When AF is known, Fa can be calculated from the measured noise level as follows:

F_a＝U+AF-20log(f)-10log(b)+95.5dB

wherein: fa: antenna noise figure (dB) caused by external noise, P: root mean square gaussian white noise level (dBm), AF: antenna factor (dB), f: measurement frequency (MHz), b: the bandwidth (Hz) is measured.

After the artificial noise level of each typical frequency point is obtained, the level of the artificial noise is judged according to the following rule.

The intermediate value Fam of Fa for the artificial noise is related to the frequency f by:

Fam＝c–d log f

when f is expressed in MHz, c and d are given the values given in Table 1, resulting in a relationship of f to Fam, as shown in FIG. 2.

TABLE 1 values of constants c and d

Type of environment	c	d
			City (Curve A)	76.8	27.7
Residence (Curve B)	72.5	27.7
			Rural area (Curve C)	67.2	27.7
Quiet village (Curve D)	53.6	28.6
			Galaxy noise (Curve E)	52.0	23.0

As shown in fig. 2, which is data of artificial noise power in various environments, it can be seen from fig. 2 that the value of Fam applies to all environment types in the frequency range of 0.3 to 250MHz, except for the environment types of curves D and E, and from the above limit, it can be determined at what level the frequency of the noise is considered.

It should be noted that: in the method for testing the artificial noise level, a 20% cut-off method is adopted, and after the noise level of a certain typical frequency is obtained by adopting the 20% cut-off method, the same Fa calculation method is used for processing.

Further, since the "20% cut-off method" also eliminates some noisy samples in practical use, which would result in too low noise level if not corrected, the present application can determine the required correction by connecting a white noise source to the receiver, extracting some measured samples and determining the mean rms level from all 100% samples; the upper 80% is then removed and the mean rms level is calculated from the lower 20% samples, using the correction as the difference between the two mean rms levels (100% and 20%).

The electromagnetic environment change trend analysis function can continuously collect data, preprocesses the data periodically, calculates the preprocessed data every hour and stores the preprocessed data, and generates background noise data every day and every month correspondingly so as to rapidly process the change trend.

As a possible example: when the full-band spectrum of 1MHz to 30MHz is collected, the receiver collects 1 group of data about every 1.5 minutes, and collects 40 groups of data each hour. Performing data fitting once per hour to generate preprocessed data, wherein the data fitting mode adopts an RMS (root mean square) mode, and abnormal data are removed by adopting the same processing mode as that in background noise calculation when the data fitting is performed; of course, this example is merely an illustrative example, and the case of actual use is not limited thereto.

The implementation method of the background noise comparison analysis function comprises the following steps: the client side initiates the data query and statistics according to the comparison parameters, and then sends the statistical results to the client side for display, the working flow is as shown in fig. 3, a user selects an analysis mode at the client side, the client side sends an analysis request to the data processing service, the data processing service distributes the analysis request to group fitting data, the data is returned to the client side, and the data is visually presented to a comparison analysis interface through the data of the client side.

It should be noted that: the dynamic element analysis technology is used in the application, the trend analysis is carried out by taking the time parameter as an influence factor, and the change trend analysis of the same day, the morning, the evening, the same time every day and the time span of month and year is supported.

The principle of the dynamic element Analysis technology is to further abstract the description of the parameters, the number of the parameters and the relationship between the parameters, the Analysis process needs to face unknown parameters, the Analysis process is abstracted into Analysis behavior (Analysis Action) classes, and on the basis, a Direct comparison behavior model (Direct Compare Action), a classification Fitting Analysis behavior model (Classified Fitting Action) and a correlation Analysis behavior model (coherent Action) are realized according to the mature Analysis mode at present.

The direct comparison behavior model is mainly used for directly inquiring original data or background noise data for comparison. Including but not limited to manually analyzing the change trend of the electromagnetic environment and directly analyzing the change trend of the level of a certain frequency point along with the time by looking at a time-frequency graph in a period of time.

And (3) the classification fitting analysis behavior model performs comparison analysis after matching the original data into a plurality of groups of data according to the specified conditions. Including but not limited to, analyzing the background noise level in the morning of each day by alignment.

The correlation analysis behavior model aims at the condition that one parameter needs to be analyzed to be consistent, and the result change caused by the change of the other parameter is analyzed, so that whether the parameter has correlation analysis behavior on the result change or not is obtained. Including but not limited to analyzing the effects of temperature changes on the electromagnetic environment.

Parameters are abstracted into Analysis conditions (Analysis Condition), Time Analysis conditions (Time Condition), climate Analysis conditions (Weather Condition) and the like are realized according to the currently mastered Analysis conditions, and the Analysis conditions can be further expanded according to future applications.

Through abstract design, the analysis process and the analysis conditions (parameters) can be iterated and expanded relatively independently, and the aim of dynamic analysis is fulfilled. The dynamic analysis model is shown in fig. 11.

The electromagnetic environment interference signal statistical analysis function mainly aims at the utilization of interference signal measurement data, and comprises the following steps: measurement, pretreatment and comparison analysis.

The interference signal measurement uses interference energy detection, that is, a signal having interference on a normal signal and having an influence on a background noise is searched from all the measured signals, and the steps of measuring the interference signal are described with reference to fig. 4:

9) and the interference signal measurement and analysis are completed.

The interference signal statistical preprocessing function mainly realizes preliminary analysis and processing of interference signal measurement results, establishes certain associated information for respective independent interference frequency point information, and specifically includes the following aspects:

1) and (3) interference signal correlation and collection: and establishing an incidence relation between the interference signals of the same frequency of the frequency spectrums at different time instants, and combining the interference signals into a corresponding signal set. And counting the time information of the change such as appearance, disappearance, amplitude change (exceeding the amplitude change range parameter) and the like of the signal event, and establishing a signal event linked list.

The database maintains a base number table of the interference signals, the interference signals obtained by measurement are compared with the base number table according to an allowable error range, if the base number table does not exist, the table is marked to be newly added, if the original base number table exists but does not exist at the time, the table is marked to be disappeared, and the interference signals which disappear once are found and marked to appear at the time.

The matched base number meter maintenance interface can be provided through the client side, a user is allowed to operate the base number meter in a semi-automatic mode, interference signals which disappear for a long time are cleared, and manual addition of the base number meter is supported. The bottom table field includes frequency points, signal bandwidth, signal amplitude, and last time of occurrence.

The interference signal comparison and analysis function is used for researching and discovering the occurrence rule of the interference signals by comparing and analyzing the intensity and the quantity of the interference signals in different time periods, frequency bands and places on the basis of the statistics of the interference signals.

The interference signal comparison analysis is realized by adopting a C/S mode, and the flow is explained by referring to FIG. 5 as follows:

c) and the client displays according to the query result.

The interference data comparison, analysis and display function is that the client side utilizes the interference statistical data obtained by the server side to perform interference data comparison and display.

The large signal alarm function comprises sub-functions of alarm template generation, large signal measurement, alarm message management and the like. And configuring a threshold value of the large signal through an alarm template, comparing the measured signal with the threshold value of the large signal, generating an alarm message if the measured signal exceeds the threshold value, performing persistence processing and pushing the alarm message to an interface for display, providing an alarm information reporting interface, and supporting the pushing to an upper-level operation and maintenance system.

And the generated alarm templates support import and editing and real-time loading, and support storage of multiple groups of alarm templates so as to deal with different working scenes. Each group of alarm templates consists of two groups of frequency spectrum data, which respectively represent the upper limit and the lower limit of the threshold value of the alarm, the upper limit data is used for detecting large signals, and the lower limit data can be used for abnormal detection of noise floor, such as the condition of no signal input; the large signal measurement algorithm is designed according to the standard interface of the algorithm plug-in, and the expansibility of the algorithm is realized.

The main way of large signal measurement is by detecting and recording energy blocks exceeding a threshold, and the detection effect is as follows:

and (4) recording the detected large signals as alarm information in a storage mode one by one, wherein fields comprise alarm ID, alarm starting frequency, alarm cut-off frequency, amplitude value, alarm state and alarm time. Before the alarm information is put in storage, the alarm information is compared with the historical records, the states of the alarm information are identified, the states are divided into newly-added alarms and existing alarms, the historical records already exist, and the alarm identifier which disappears at the time is a disappearing alarm. As with the interference signal, due to factors in measurement accuracy, an error range of about 10% is allowed when determining whether the same alarm signal is present. For the original alarm signal, the alarm ID is unchanged when the alarm signal is put in storage, and the new signal uses the new ID.

As shown in fig. 6, the electromagnetic environment report management function in the service layer is implemented by: the report management service generates corresponding reports by extracting various data of an electromagnetic environment database, predefines several types of report templates including a background noise report template, a large signal interference report template, a comparison analysis report template and the like, and extracts corresponding fields from the database according to retrieval conditions of time, sites, frequency bands and the like and fills the fields into the templates to generate the reports.

The user firstly checks the module needing to generate the report, the module is selected completely under the default condition, the user interface can present the parameter setting of the selected module after the user interface confirms, such as time and frequency band parameters, and the default frequency band parameter value is 1 MHz-30 MHz; the report management service acquires corresponding data from the storage service according to the parameters, processes the data, generates a report and returns the report to the interface end; and the user selects a report output mode according to actual needs.

As shown in fig. 1, the data access layer is used for implementing acquisition, distribution and persistence of raw data of an electromagnetic environment, and the layer still implements data distribution by using a message bus, and includes: data storage access service, electromagnetic environment data acquisition service and database.

The database adopts an SQL Server 2008 database, and the access interface can carry out normal read-write operation on the original SQL Server 2005 database through testing, and has the capability of downward compatibility.

The data storage access service is used for storing and accessing collected data, analysis result data and other auxiliary data. The collected data comprises real-time frequency spectrum data and data after preprocessing of the real-time frequency spectrum; the analysis data comprises background noise data, large signal interference data, alarm data and the like; the auxiliary data includes working state information records, operation log records, and the like.

The data storage access service is an abstraction layer between the business module and the database, and the decoupling between the business module and the database is realized by defining a standard access interface, so that the stability of the business module is ensured. Meanwhile, complexity is reduced through objectification access, SQL sentences are prevented from being directly used in a business layer, and system reliability is improved.

The data storage access service is divided into a database connection management module, an antenna parameter access module, a site information parameter access module, a spectrum data access module, a background noise data access module, a large signal interference data access module, an alarm data access module, a working state information recording access module and an operation log recording access module. The business module calls the corresponding data access module to realize the increasing, deleting, modifying and checking of the data.

When the electromagnetic environment data acquisition service acquires the frequency spectrum data, an acquisition task is issued through the task management service, and the acquisition task calls a receiver through acquisition algorithm logic to drive to acquire the frequency spectrum data and stores the frequency spectrum data in a warehouse according to an agreed data format.

The input parameters of the acquisition task comprise an acquisition frequency band, scanning stepping, a receiver resolution bandwidth, a detection mode, an acquisition strategy and the like; the acquisition frequency band can realize full-frequency-band scanning and customized frequency-band scanning, while the conventional spectrum data acquisition adopts an equal step scanning mode, and the scanning is allowed according to the customized frequency point under special conditions, so that the technical personnel in the field can flexibly select the frequency band according to the actual use working condition; the acquisition strategy comprises single scanning, multiple scanning and cyclic scanning, wherein the cyclic scanning is only used for acquiring full-band spectrum data, and the system automatically enters a cyclic scanning mode after being idle for a period of time, so that monitoring interruption caused by man-made or abnormal conditions is avoided; fixed band (non-full band) acquisition allows only a limited number of scans to be run.

It should be noted that: and after each scanning is finished, storing the acquired complete frequency spectrum data into a warehouse. In the scanning process, for the continuity of the spectrum display of the client, the acquired intermediate data is pushed to the client after a fixed time interval, and the time interval is flexibly adjusted by a person skilled in the art according to the actual working condition.

The query of the spectrum data is realized by adopting a C/S mode, and the specific process is as follows:

c) and the client displays according to the query result.

The data management in the data access layer mainly comprises the following steps: data playback, data import and export, and data return.

Data playback service: original spectrum data of a user designated time period are read from a database, cached in a memory and then pushed to a client, and if data of the same time period exist when a plurality of clients access simultaneously, the data are directly read from the cache, so that the service response efficiency is improved; the main function of the data playback service is to analyze playback instructions, including time range setting, frequency range setting, playback rate setting, start, pause, stop instructions, and respond to the instructions, push data according to the settings, and perform validity management on the buffer.

And after receiving the data, the client displays a time-frequency diagram, and the operation interface provides a time range setting input control, a frequency range input control, a fast-forward slow-play button, a start instruction button, a pause instruction button and a stop instruction button and displays the playback progress. In addition, the ue needs to provide auxiliary operations for the time-frequency diagram, including frequency band and time setting functions of the interference block, time-frequency diagram storage function, and conventional spectrum operation.

Data import and export: on any spectrum interface, the derivation of current spectrum data is supported, and relevant parameters of the spectrum, such as time, position, frequency range, receiver parameters and the like, are extracted together when the derivation is carried out. The derived data format is CSV; on a specific spectrum display interface, the spectrum data can be imported for viewing or comparing and measuring. The data import source can be data files and data of other frequency spectrum interfaces, and the multi-source data can be rapidly compared in the mode.

Data returning: the function transmits the electromagnetic environment data of each station back to the electromagnetic environment monitoring center server of the sink node; the data includes real-time spectrum data, pre-processing data, background noise data, large signal interference data, alarm data, etc. The method adopts a non-real-time mode, and moves the related content of each site database to a central server by using idle network bandwidth as much as possible; in the process of data return, a return receiving module deployed on a central server records the position of data return of each site in real time, and can continue to transmit the data at a breakpoint after the system exits abnormally or the network is interrupted.

The data returning module uses the message bus module as the remote communication middleware, each station packs the data of the database and then releases the data according to the theme, the center subscribes the theme to receive the data, and the data is unpacked and then stored in the database by using the data storage module. The back transmission module of the central server configures a transmission strategy according to the condition of network bandwidth, and each site back transmission module distributes data according to the transmission strategy and reports the transmission progress.

It should be noted that: the SQL Server 2008 provided by the prior art has a data synchronization function, and can also realize data return by using the characteristic, but is difficult to control transmission flow, and needs to perform complex configuration operation when a database is installed, and has high requirements on operation and maintenance personnel, so that the data return is realized more conveniently by using an encoding mode.

As shown in fig. 1, the system architecture further includes: the system operation and maintenance and schedule management module is characterized in that an operation and maintenance management interface is designed in a layering mode, a home page is system overview information, and a user can visually check the states of infrastructure such as the state of collection equipment, the state of network communication, the state of a database and the like, the basic states of various services and the execution state of a current electromagnetic environment monitoring task.

As shown in fig. 8, the user can view various kinds of detailed information as needed, and click on the related link, so as to switch to the corresponding view.

The work flow of log management is similar to operation and maintenance management, and can also be classified into operation and maintenance management from the aspect of business, and the log management is divided into functional modules because the functions are relatively independent. The log management service side focuses on collecting process information such as service management processes, business processes and the like, logs are put into a warehouse regularly after being collected, a user can audit the system operation condition in a log retrieval mode, and log retrieval can be carried out screening according to conditions such as log grades, time periods, log types and the like.

The log content is divided into five levels according to importance:

critical error (critical/total): very serious errors result in the system not being able to continue to run, such as insufficient memory, insufficient disk space, and other information.

Error (error): and error log, wherein the system cannot normally perform some functions, but still can run, such as database exception, collection equipment exception and other information.

Warning (warning) indicates that some accident has occurred and the system is not operating according to the expected flow.

General information (info) is general process information such as system start, service start stop, task start stop, etc.

Debug information (debug): all the detailed information is used for debugging, helping development and operation and maintenance personnel to carry out fault diagnosis on the system, and is closed when the system is in normal operation after the system is on line, so that log storms are avoided.

The log types are divided according to the functional modules, and include basic service logs, electromagnetic environment data acquisition service logs, electromagnetic environment data analysis service logs, electromagnetic environment data management service logs, electromagnetic environment report management service logs and other log types, and the log types which cannot be accurately classified are classified into other log types.

The external equipment uses a short wave receiver and an antenna in the prior art, collects electromagnetic signals in the environment and transmits the electromagnetic signals through the antenna.

In addition, an on-demand distribution architecture based on a central cache is adopted in a data access manner between a convergence center and sites, as shown in fig. 9, in the prior art, a client directly checks information of the sites, but because the number of the clients and the average number of the sites are large, the clients and the sites are directly connected, the connection relationship is complex, network bandwidth limitation exists between the sites, when the service of one site simultaneously pushes electromagnetic environment data to other multiple sites, network blocking is easily caused, and part of the sites cannot be accessed due to unstable network, so that comparison analysis cannot be performed, if part of the clients are not used, the data volume to be distributed is larger and larger, so that normal user use is affected, in addition, each site needs to maintain access addresses of other sites, and once the addresses are changed, configuration and the workload is huge.

Therefore, the application adopts a central cache type demand distribution architecture, as shown in fig. 10, when spectrum data is acquired, for the real-time performance of the client interface display, the acquired fragment data and the alarm data need to be transmitted back to the center in real time, caching is performed in the center, and all clients subscribe real-time data to the center. The data storm of each site is reduced through the method, the data access requirements of each site are met through the processing capacity and the network bandwidth capacity of the center, the access load of each site is reduced through the access method of the data center cache, the bandwidth optimization effect is more obvious under the condition that the number of client connections is more, and the method has important significance particularly for the area with narrower network bandwidth.

On the other hand, in order to ensure the accuracy of the acquired data, the data needs to be calibrated, in this embodiment, the standard electromagnetic environment test system is used to calibrate each receiving system, so as to unify different receiving amplitude performances to the standard electromagnetic environment test system; after the electromagnetic environment data received in different ways are calibrated by the standard electromagnetic environment test system, the data can be equivalently collected by a plurality of sets of standard electromagnetic environment test systems at a plurality of places simultaneously, and then the electromagnetic environment data in different regions can be used for carrying out region correlation statistical analysis, so that the wide-area analysis of the electromagnetic environment change is realized.

The principle of data calibration is: and comparing and testing the quasi-calibration points one by using a standard electromagnetic environment testing system, and carrying out amplitude calibration on the quasi-calibration points by importing the synchronous testing result data of the standard electromagnetic environment testing system so that the electromagnetic environment testing result data of the system station is equivalent to the result data of the standard electromagnetic environment testing system.

Assuming that a linear relationship is satisfied between the two receiving systems, and a measurement result value of the standard electromagnetic environment test system is used as a true value of an actual electromagnetic environment, the following relationship necessarily exists between a measurement value of any frequency point of a current system and a measurement value of the standard electromagnetic environment test system:

E_r＝aE_t+b

wherein E_t: current system measurement value, E_r: a measurement of a standard electromagnetic environment test system; and a, b: is a linear parameter.

The values of a and b are estimated by calibration test, so that the measurement value of the equivalent standard electromagnetic environment test system can be calculated from the current system test value, and vice versa.

And respectively obtaining a group of measurement values of the standard electromagnetic environment test system and a current system test value, and calculating to obtain optimal linear correction parameters a and b by using a least square method, namely obtaining a calibration model. The specific derivation is as follows:

the least squares principle requires that the sum of the squares of the errors of the estimated value of the equivalent standard measurement system and the measured value of the standard measurement system using the current system measured values is minimal, i.e.

Make it

The minimum a, b value is the solution.

f_(a,b)Respectively solving the partial derivatives of a and b, and solving the partial derivatives to be 0 to obtain the calculation formulas of a and b:

and then, the values a and b can be directly estimated from the current system measurement result to obtain an equivalent measurement value with least square relation with the measurement value of the standard electromagnetic environment testing system.

The principle of least square method-based electromagnetic environment amplitude measurement data calibration substantially minimizes the error of data values obtained by two sets of systems, and the optimal parameter value of a calibration model can be calculated as long as enough samples are collected.

The principle of the signal source comparison calibration method in the present application is shown in figure 12,

a) deploying an antenna of a standard electromagnetic environment test system to be close to an antenna of a system to be calibrated;

b) deploying the amplitude-controllable signal source to a position which accords with far-field conditions for all antennas and frequency bands;

c) setting the amplitude of the signal source as a larger amplitude value (determining a set amplitude range by using two sets of system effective receiving amplitude ranges);

d) using two sets of systems to respectively receive corresponding frequency signals, and using a uniform reading mode to acquire and record amplitude values;

e) setting the amplitude of the signal source as a smaller amplitude value (determining a set amplitude range by using two sets of system effective receiving amplitude ranges);

f) using two sets of systems to respectively receive corresponding frequency signals, and using a uniform reading mode to acquire and record amplitude values;

g) measuring for multiple times to obtain multiple groups of data, and calculating calibration parameters of the system to be calibrated relative to a standard electromagnetic environment test system;

h) setting new testing frequency points and circularly executing the steps c) to g) until all the frequency point calibration is completed.

Furthermore, a large number of short-wave communication signals exist in the actual signal environment, and certain communication frequency points with stable amplitudes also exist in the actual signal environment. Because the distance between the signals and the test position is far larger than the requirement of a common far-field condition, the signals can be regarded as the input of the same excitation large signals for a standard electromagnetic environment test system with a close deployment position and a system to be calibrated, meanwhile, the noise level of the electromagnetic environment in the short-wave frequency band is obviously larger than the sensitivity of a receiving system, and the noise level of the electromagnetic environment received by the standard electromagnetic environment test system and the system to be calibrated at the same moment can be regarded as the input of the excitation small signals. Under the condition that the slow change of a frequency response curve of a receiving system is established, the noise bottom near the excitation large signal frequency point and the noise bottom of the test large signal frequency point can be considered to be equal, two test data with larger amplitude difference are obtained for the point where the excitation large signal is located, and the linear calibration condition of at least two-point amplitude calibration can be met.

Therefore, the alignment calibration method for the field signal environment is as follows:

a) firstly, scanning a field electromagnetic environment to obtain complete field electromagnetic environment frequency spectrum information;

b) observing and analyzing field electromagnetic environment data, and selecting and determining a relatively stable large signal test frequency point (covering a full frequency band as much as possible, and selecting more points for a part with large electromagnetic environment fluctuation);

c) starting two sets of systems according to a preset test point, simultaneously executing an electromagnetic environment test and collecting electromagnetic environment test frequency spectrum data;

d) scanning for multiple times and collecting enough sample data;

e) counting the amplitude data of each frequency point by a least square method, and calculating to obtain a calibration parameter (using a noise-bottom signal of a frequency point near a stable large signal as a small signal test result of the large signal frequency point);

f) and obtaining full-band calibration parameters through interpolation.

As a preferred embodiment, the receiver is a receiver of model PR 100.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.

Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims above, any of the claimed embodiments may be used in any combination. The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms part of the prior art that is known to a person skilled in the art.

Claims

1. An electromagnetic environment monitoring system comprising: gather center, website, through the electromagnetic environment spectrum data who continuously gathers around the website, transmit the electromagnetic environment spectrum data of each website back to and gather the center, carry out analysis, its characterized in that in gathering the center: the system adopts a four-layer structure of a presentation layer, a service layer and a data access layer from top to bottom.

2. An electromagnetic environment monitoring system as claimed in claim 1, wherein: the electromagnetic environment data processing service: the method comprises the following steps: electromagnetic environment interference signal statistical analysis, including: interference signal measurement, interference signal preprocessing and interference signal comparison analysis.

3. An electromagnetic environment monitoring system as claimed in claim 2, wherein: the steps of the interference signal measurement are explained as follows:

9) and the interference signal measurement and analysis are completed.

4. An electromagnetic environment monitoring system as claimed in claim 2, wherein: the interference signal statistical preprocessing comprises the following steps:

5. An electromagnetic environment monitoring system as claimed in claim 2, wherein: and (3) comparing and analyzing the interference signals: comparing and analyzing the intensity and the quantity of the interference signals in different time periods, frequency bands and places;

c) and the client displays according to the query result.

6. An electromagnetic environment monitoring system as claimed in claim 5, wherein: the electromagnetic environment data processing service: further comprising: large signal early warning;

7. An electromagnetic environment monitoring system as claimed in claim 6, wherein: the main mode of the large signal measurement is that energy blocks exceeding a threshold value are detected and recorded, the detected large signals are used as alarm information to be recorded and stored in a warehouse one by one, before the alarm information is stored in the warehouse, the alarm information is compared with a historical record, the state of the alarm information is identified, the state is divided into newly-added alarms and existing alarms, the historical record already exists, and when the alarm identifier disappears, the alarm identifier disappears.

8. An electromagnetic environment monitoring system as claimed in claim 1, wherein: the data access mode of the aggregation center and the stations adopts a demand distribution architecture based on a center cache, the center cache is arranged between the client and the stations, the client and the stations are connected with the center cache, the acquired fragment data and the alarm data are transmitted back to the center cache in real time, the cache is carried out in the center cache, and all the clients subscribe the real-time data to the center.