CN115765820A - Data acquisition method, device, equipment and storage medium - Google Patents
Data acquisition method, device, equipment and storage medium Download PDFInfo
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Abstract
The application discloses a data acquisition method, a device, equipment and a storage medium, which relate to the technical field of microwave antennas, and the method comprises the following steps: determining an acquisition target, and sending an acquisition signal to the acquisition target based on a DBF communication channel; acquiring data signals of an acquisition target based on the acquisition signals, and determining signal identification information of required data; converting interference signals in the data signals into a preset form based on a preset filtering model and signal identification information so as to extract target data signals from the data signals based on the signal identification information; and demodulating the target data signal to obtain target acquisition data. In the application, the DBF communication channel is used for sending signals or data signals, the collected signals and the data signals are converted into signals in a digital beam form in the transmission process, so that the time for collecting the target converted signal form is reduced, interference signals are filtered through the filtering model, the time for identifying various interference signals is reduced, and the data collection rate of the radar is further improved.
Description
Technical Field
The present application relates to the field of microwave antenna technology, and in particular, to a data acquisition method, apparatus, device, and storage medium.
Background
With the increasingly wide application field of communication technology, DBF (Digital Beam Forming) is also applied to the radar field.
The DBF is applied to the field of radar, useful signals can be extracted from received data signals, interference signals are suppressed, the direction of the received signals can be determined, and the accuracy of radar data acquisition is improved. However, due to the influence of the environment, errors are prone to occur in the DBF communication channel, which causes deviation in signal transmission, and further affects the accuracy of receiving or sending data signals by the radar, and errors are prone to occur in the data signals received by the radar and the data signals sent by the signal source, so that the rate of data acquisition by the radar is reduced.
Disclosure of Invention
The application mainly aims to provide a data acquisition method, a data acquisition device, data acquisition equipment and a storage medium, and aims to solve the technical problems that in the prior art, the radar data acquisition process is interfered by interference signals, and errors easily occur in a DBF communication channel, so that the rate of data acquisition by the radar is reduced.
In order to achieve the above object, the present application provides a data acquisition method, including:
determining an acquisition target, and sending an acquisition signal to the acquisition target based on a DBF communication channel;
acquiring a data signal of the acquisition target based on the acquisition signal, and determining signal identification information of required data;
converting interference signals in the data signals into a preset form based on a preset filtering model and the signal identification information so as to extract target data signals from the data signals based on the signal identification information;
and demodulating the target data signal to obtain target acquisition data.
Optionally, before the step of converting the interference signal in the data signal into a preset form based on a preset filtering model to extract the target data signal from the data signal based on the signal identification information, the method further includes:
calling an acquisition log of the data signal;
determining a historical data signal from the acquisition log;
identifying a disguised interference signal and/or a direct interference signal from the historical signal;
and iteratively training a preset model to be trained based on the disguised interference signal and/or the direct interference signal and a preset gradient to obtain a filtering model.
Optionally, the step of iteratively training a preset model to be trained based on the disguised interference signal and/or the direct interference signal and a preset gradient to obtain a filtering model includes:
analyzing the disguise success rate of each kind of disguise interference signal and the interference success rate of each kind of direct interference signal;
iteratively training a preset camouflage model in a model to be trained in a gradient manner based on the camouflage success rate and a preset gradient;
iteratively training an interference model in the model to be trained in a gradient manner based on the interference success rate and the preset gradient;
and obtaining a filtering model based on the camouflage model and the interference model.
Optionally, before the step of sending the acquisition signal to the acquisition target based on the DBF communication channel, the method includes:
calling an acquisition log of the data signal;
determining a DBF communication channel for transmitting an acquisition signal from the acquisition log;
analyzing an amplitude-phase error between the DBF communication channel and a preset standard channel based on a preset optimization algorithm;
and correcting the DBF communication channel in parallel based on the amplitude and phase errors.
Optionally, the step of analyzing an amplitude-phase error between the DBF communication channel and a preset standard channel based on a preset optimization algorithm includes:
analyzing a directional diagram of the collected signal transmitted by the DBF communication channel based on a preset optimization algorithm, and determining an azimuth angle of the collected signal transmitted by the DBF communication channel;
and comparing the azimuth angle with a preset standard angle of a standard channel to obtain an amplitude-phase error.
Optionally, the step of determining, from the acquisition log, a DBF communication channel for transmitting the acquisition signal includes:
extracting historical data signals from the acquisition log;
setting the historical data signal into a plurality of data sub-arrays;
and optimizing the data submatrix based on a preset genetic algorithm, and determining a DBF communication channel meeting preset requirements.
Optionally, the step of converting the interference signal in the data signal into a preset form based on a preset filtering model and the signal identification information, so as to extract the target data signal from the data signal based on the signal identification information includes:
screening out interference signals from the data signals based on a preset filtering model to obtain collected data signals;
and extracting a target data signal corresponding to the signal identification information from the acquired signal.
The present application further provides a data collection device, the data collection device includes:
the transmitting module is used for determining an acquisition target and transmitting an acquisition signal to the acquisition target based on a DBF communication channel;
the acquisition module acquires the data signal of the acquisition target based on the acquisition signal and determines the signal identification information of the required data;
the extraction module is used for converting interference signals in the data signals into a preset form based on a preset filtering model and the signal identification information so as to extract target data signals from the data signals based on the signal identification information;
and the demodulation module is used for demodulating the target data signal to obtain target acquisition data.
The present application further provides a data acquisition device, the data acquisition device is entity node device, the data acquisition device includes: a memory, a processor and a program of the data acquisition method stored on the memory and executable on the processor, which program, when executed by the processor, may implement the steps of the data acquisition method as described above.
The present application also provides a storage medium having stored thereon a program for implementing the above-described data acquisition method, the program for implementing the data acquisition method implementing the steps of the above-described data acquisition method when executed by a processor.
Compared with the prior art that the radar is interfered by interference signals in the data acquisition process, and errors easily occur in a DBF communication channel, so that the rate of data acquisition of the radar is reduced, in the data acquisition method, the data acquisition device, the data acquisition equipment and the storage medium, an acquisition target is determined, and an acquisition signal is sent to the acquisition target based on the DBF communication channel; acquiring a data signal of the acquisition target based on the acquisition signal, and determining signal identification information of required data; converting interference signals in the data signals into a preset form based on a preset filtering model and the signal identification information, so as to extract target data signals from the data signals based on the signal identification information; and demodulating the target data signal to obtain target acquisition data. In the application, after the acquisition target is determined, the acquisition signal is sent to the acquisition target through the DBF communication channel, the acquisition signal can be converted into a digital beam, so that the conversion process of the acquisition target on the acquisition signal is reduced, the data signal of the acquisition target is acquired based on the acquisition signal, interference signals are filtered from the data signal through a preset filtering model, a target data signal is obtained, so that the influence of the interference signals is reduced, the time for identifying various interference signals is reduced, and finally the target data signal is demodulated, so that target acquisition data is obtained.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic flow chart of a first embodiment of a data acquisition method of the present application;
FIG. 2 is a schematic flow chart of a second embodiment of the data collection method of the present application;
fig. 3 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present application.
The objectives, features, and advantages of the present application will be further described with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In a first embodiment of the data acquisition method of the present application, referring to fig. 1, the data acquisition method includes:
step S10, determining a collection target, and sending a collection signal to the collection target based on a DBF communication channel;
step S20, acquiring data signals of the acquisition target based on the acquisition signals, and determining signal identification information of required data;
step S30, converting interference signals in the data signals into a preset form based on a preset filtering model and the signal identification information, and extracting target data signals from the data signals based on the signal identification information;
and S40, demodulating the target data signal to obtain target acquisition data.
The present embodiment is intended to: when the radar collects data, the influence of interference signals on the collected target data signals is reduced, and the time for collecting the signals and transmitting the data signals is saved, so that the data collecting rate of the radar is improved.
In this embodiment, it should be noted that the data acquisition method may be applied to a data acquisition apparatus, where the data acquisition apparatus is subordinate to a data acquisition device, and the data acquisition device belongs to a data acquisition system.
The acquisition signal may be an acquisition instruction, and the acquisition signal at least includes acquired target sample information, acquisition frequency, acquisition time, acquisition frequency, and the like, and is not particularly limited.
The filtering model is obtained by performing iterative training on a preset model to be trained based on training data of a preset interference signal label.
It should be noted that the interference signals recorded in the filtering module can be converted into a preset form by filtering the signals in the model, so that the processing time of the interference signals is saved, and the target data signals are extracted from the data signals quickly.
The method comprises the following specific steps:
step S10, determining a collection target, and sending a collection signal to the collection target based on a DBF communication channel;
the DBF has the capability of inhibiting interference signals, and can reduce the probability of interference of the acquired signals or the target data signals by the interference signals in the process of transmitting the acquired signals or the data signals, namely, when the acquired signals or the data signals are transmitted through the DBF communication channel, the interference signals in the communication channel can be reduced, and then the probability of interference of the acquired signals or the target data signals by the interference signals is reduced.
It should be noted that the acquisition target may be set by the user, or may be set by the user according to the application scenario, so as to improve the flexibility of the radar. For example, if the satellite radar is used to receive information on the ground, the acquisition target of the satellite radar may be set by itself according to the data acquired on the ground.
In the implementation, before the acquisition target is determined and the acquisition signal is sent to the acquisition target through the DBF communication channel, the amplitude phase of the DBF communication channel is detected and compensated and corrected relative to the DBF channel according to the amplitude phase, so that the transmission address offset and/or the receiving address offset caused by the influence of the interference signal received by the communication channel are avoided, the interference signal in the communication channel is reduced, and the accuracy of the acquisition signal transmission to the acquisition target is improved.
Step S20, acquiring data signals of the acquisition target based on the acquisition signals, and determining signal identification information of required data;
it should be noted that the signal identification information may be a signal string of an address of the acquisition target, and when the acquired target data is converted into a target data signal, the signal string of the acquisition target is added to the target data signal; the signal identification information can also be a preset carrying signal, the carrying signal is added to the collected signal when the collected signal is sent down, and the carrying signal is added to the target data signal when the collected target data is converted into the target data signal, so that the radar can quickly identify the target data signal through the signal identification information.
It should be noted that, in order to ensure that the target data signal is not interfered by the interference signal or reduce the interference degree of the interference signal in the transmission process, some acquisition targets add a layer of protection number for protecting the target data signal by the user on the target data signal, and convert the target data signal into the acquisition data signal.
In this embodiment, after the acquisition target receives the acquisition signal, sample data (i.e., target data) required in the acquisition signal is sorted and converted into a target data signal, and the target data signal is sent to the acquisition radar.
Step S30, converting the interference signal in the data signal into a preset form based on a preset filtering model and the signal identification information, so as to extract a target data signal from the data signal based on the signal identification information;
the preset form can be an analog form signal, but the preset form cannot be the same as the form of the collected data signal, so that the situation that the collected data signal in the data signal cannot be directly and quickly identified is avoided.
In this embodiment, be equipped with different types, different forms's interfering signal in the filtering model, can discern the interfering signal who is equipped with in the filtering model from data signal to turn into the preset form with interfering signal, for gathering the radar and extracting the target signal from discerning data signal.
It should be noted that, if the target data signal is not provided with the protection signal, the interference signal is filtered to directly obtain the target data signal, and if the target data signal is provided with the protection signal, the interference signal is filtered to obtain the collected data signal, and the target data signal is extracted from the data signal through the identification information.
In this embodiment, first, the filtering model is used to filter the interference signal in the data signal, so as to avoid the interference signal from affecting the extraction of the target data signal, that is, avoid the interference signal being carried on the target data signal when the identification information identifies the target data signal.
Specifically, the step of converting the interference signal in the data signal into a preset form based on a preset filtering model and the signal identification information to extract a target data signal from the data signal based on the signal identification information includes:
s31, screening out interference signals from the data signals based on a preset filtering model to obtain collected data signals;
and step S32, extracting a target data signal corresponding to the signal identification information from the acquired signal.
The collected data signal may also be carried data carried by the target data when the target data is collected.
It should be noted that the acquired data signal at least includes a target data signal and may also include a carried data signal, and if the target data does not carry the carried data and the acquired target does not add protection information to the target data, the acquired data signal includes the target data signal. If the target data carries the carried data and/or the collected target adds the protection information on the target data, the collected data signal comprises a target data signal and a carried data signal, wherein the carried data signal is a signal for transmitting the carried data.
In this embodiment, the interference signal in the data signal is filtered out through the filtering model, and when the target data signal has a protection signal or a carried data signal, the target data signal needs to be identified from the collected data signal based on the identification information, so as to reduce the influence of the interference signal or the carried data signal on the target data signal.
And S40, demodulating the target data signal to obtain target acquisition data.
In this embodiment, after the target data signal is identified, the target data is parsed from the target data signal.
In this embodiment, the demodulation target data signal may demodulate the target data signal through a local preset modulation and coding strategy, so as to locally obtain the acquired target data.
Step S10, determining a collection target, and sending a collection signal to the collection target based on a DBF communication channel;
step S20, acquiring data signals of the acquisition target based on the acquisition signals, and determining signal identification information of required data;
step S30, converting interference signals in the data signals into a preset form based on a preset filtering model and the signal identification information, and extracting target data signals from the data signals based on the signal identification information;
s40, demodulating the target data signal to obtain target acquisition data
In this embodiment, after the acquisition target is determined, the acquisition signal containing the target sample information is sent through the communication channel in the DBF form, in the process of transmitting the acquisition signal, the acquisition signal can be converted into a signal in the digital beam form to accelerate the transmission speed and reduce the probability of being interfered by the interference signal, after the acquisition target receives the acquisition signal, the target data corresponding to the target sample information is converted into a target data signal, and then the target data signal is transmitted to the local through the communication channel in the DBF form, after the data signal containing the target data signal is received locally, the interference signal is filtered from the data signal based on the filtering model, and the target data signal is identified through the identification information, so that the processing time for the interference signal is reduced, and the target data signal is prevented from being influenced and identified by the interference signal.
Compared with the prior art that the radar is interfered by interference signals in the data acquisition process, and errors easily occur in a DBF communication channel, so that the rate of data acquisition of the radar is reduced, in the data acquisition method, the data acquisition device, the data acquisition equipment and the storage medium, an acquisition target is determined, and an acquisition signal is sent to the acquisition target based on the DBF communication channel; converting interference signals in the data signals into a preset form based on a preset filtering model and the signal identification information, so as to extract target data signals from the data signals based on the signal identification information; converting interference signals in the data signals into a preset form based on a preset filtering model and the signal identification information, so as to extract target data signals from the data signals based on the signal identification information; and demodulating the target data signal to obtain target acquisition data. In the application, after the acquisition target is determined, the acquisition signal is sent to the acquisition target through the DBF communication channel, the acquisition signal can be converted into a digital beam, so that the conversion process of the acquisition target on the acquisition signal is reduced, the data signal of the acquisition target is acquired based on the acquisition signal, interference signals are filtered from the data signal through a preset filtering model, a target data signal is obtained, so that the influence of the interference signals is reduced, the time for identifying various interference signals is reduced, and finally the target data signal is demodulated, so that target acquisition data is obtained.
Further, based on the foregoing embodiment in the present application, another embodiment of the present application is provided, in this embodiment, referring to fig. 2, before the step of converting the interference signal in the data signal into a preset form based on a preset filtering model, so as to extract the target data signal from the data signal based on the signal identification information, the method further includes:
s01, calling an acquisition log of the data signal;
step S02, determining historical data signals from the acquisition logs;
step S03, identifying a disguised interference signal and/or a direct interference signal from the historical signal;
and S04, iteratively training a preset model to be trained based on the camouflage interference signal and/or the direct interference signal and a preset gradient to obtain a filtering model.
The disguised interference signal may be an interference signal hidden in the target data signal, or an interference signal which is not easily recognized, such as an interference signal disguised as the target data signal.
The direct interference signal may be an interference signal that can be directly identified.
It should be noted that the acquisition log is updated in real time, that is, when the target data signal is obtained, the target data signal column in the acquisition log is updated in real time, when the target data is obtained, the target data column in the acquisition log and the like are updated in real time, and the data signal and the acquisition data signal are also updated in real time in the acquisition log and are changed into historical data in real time after being updated in the next time and in the log.
The model to be trained is composed of at least two submodels to be trained, so that different filtering submodels can be conveniently trained according to different types of interference signals.
In this embodiment, a sub-log and a log of a data signal are called, a historical data signal is determined from the sub-log and the log so as to obtain a historical interference signal from the historical data signal, the historical interference signal is divided into a direct interference signal which is easy to identify and a disguised interference limit signal which is difficult to identify, different submodels to be trained are iteratively trained corresponding to different interference signals, and finally a filtering model is obtained.
It should be noted that, the interference signals used in the iterative training of the model to be trained need to be screened according to the number of times that the interference signals are recorded in the acquisition log, data with a time difference being too large from the current time is filtered, and data within a preset time period is used, so that the interference signals learned by writing the filtering model cannot be deleted by itself when the filtering model is used and used, and it is avoided that one or more abnormal interference signals suddenly appear and cannot be identified by the filtering module. That is, in this embodiment, the accuracy of identifying the interference signal is improved, and the number of interference signals carried on the final target data signal is reduced.
Specifically, the step of iteratively training a preset model to be trained based on the disguised interference signal and/or the direct interference signal and a preset gradient to obtain a filtering model includes:
step S041, analyzing the camouflage success rate of each camouflage interference signal and the interference success rate of each direct interference signal;
step S042, based on the disguise success rate and the preset gradient, performing gradient iterative training on a disguise model in a preset model to be trained;
step S043, based on the interference success rate and the preset gradient, iteratively training an interference model in the model to be trained in a gradient manner;
and step S045, obtaining a filtering model based on the camouflage model and the interference model.
The preset gradient may be a usage rate of an interference signal, or an interference rate of an interfered signal, and the like, which is not limited specifically.
In this embodiment, the camouflage model and the interference model in the model to be trained are iteratively trained in a gradient manner to divide the training weight, so as to emphasize the interference signal which is easy to use, and continue to train the interference signal which has a low use frequency effect or interference success rate, so that the interference signal learned by the filtering model is more comprehensive, and any interference signal is prevented from being missed in the use process.
In this embodiment, a disguised interference signal and a direct interference signal are selected from the historical data signals in the collection log, the disguised success rate (i.e., the interfered rate of the target data signal) of the disguised interference signal and the interference success rate of the direct interference signal are analyzed, the usage rate of each interference signal is analyzed, and the usage rate or the interference success rate is divided into a gradient of training weights to enable the filtering model to learn each interference signal.
It should be noted that the newly-appearing interference signal is preferentially learned and trained.
Further, based on the above-mentioned embodiment in the present application, another embodiment of the present application is provided, in which before the step of sending the acquisition signal to the acquisition target based on the DBF communication channel, the method includes:
step A10, calling an acquisition log of the data signal;
step A20, determining a DBF communication channel for transmitting an acquisition signal from the acquisition log;
step A30, analyzing an amplitude-phase error between the DBF communication channel and a preset standard channel based on a preset optimization algorithm;
and A40, correcting the DBF communication channel in parallel based on the amplitude and phase errors.
In the embodiment, the DBF communication channel for transmitting the acquisition signal or receiving the data signal is determined in the acquisition day, the amplitude and phase of the DBF communication channel are analyzed according to the data of the historical received or sent signal and based on the preset optimization algorithm, the amplitude and phase are compared with the standard amplitude and phase, the amplitude and phase error between the DBF communication channel and the standard amplitude and phase is determined, the DBF communication channel is corrected according to the amplitude and phase error, the phenomenon that the DBF communication channel points inaccurately is avoided, the transmitted or received signal has errors, and the efficiency of receiving the data signal is improved.
Specifically, the step of analyzing the amplitude-phase error between the DBF communication channel and a preset standard channel based on a preset optimization algorithm includes:
step A31, analyzing a directional diagram of the acquired signal transmitted by the DBF communication channel based on a preset optimization algorithm, and determining an azimuth angle of the acquired signal transmitted by the DBF communication channel;
and A32, comparing the azimuth angle with a preset standard angle of a standard channel to obtain an amplitude-phase error.
In this embodiment, the directional diagram of the DBF communication channel for transmitting the acquisition signal is analyzed through an optimization algorithm, and the directional diagram of the acquisition target for receiving the acquisition signal is determined, so that the error between the DBF communication channel and the transmission address of the acquisition radar is accurately and quickly determined, and the error between the DBF communication channel and the reception address of the acquisition target is accurately and quickly determined.
Specifically, the step of determining the DBF communication channel for transmitting the collection signal from the collection log includes:
step A21, extracting historical data signals from the acquisition logs;
step A22, setting the historical data signal into a plurality of data sub-arrays;
and A23, optimizing the data submatrix based on a preset genetic algorithm, and determining a DBF communication channel meeting preset requirements.
In this embodiment, because the DBF communication channel used each time data is collected is random, the historical data signal is randomly set as a plurality of data sub-arrays, the DBF communication channel whose use frequency does not conform to the use frequency in the genetic algorithm and the DBF communication channel that cannot be used continuously in each data sub-matrix are eliminated through a preset genetic algorithm, and the DBF communication channel whose use frequency satisfies the use frequency in the genetic algorithm is determined to optimize the data sub-matrices, and then the DBF communication channel satisfying the requirements is determined, thereby avoiding waste of resources.
In this embodiment, before sending the acquisition signal, the use information of the DBF communication channel is acquired from the acquisition log, the DBF communication channel meeting the requirement is screened out from the acquired DBF communication channel through a genetic algorithm, a preset optimization algorithm is utilized to determine the amplitude-phase error of the DBF communication channel, and then the DBF communication channel is corrected, after correction, the acquisition signal is sent or the data signal is received, the data acquisition accuracy is improved, the speed of detecting the amplitude phase of the DBF communication channel and correcting the amplitude phase of the DBF communication channel is increased, the time for the DBF communication channel is shortened, and further the data acquisition speed of the radar is increased.
Referring to fig. 3, fig. 3 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present application.
As shown in fig. 3, the data acquisition apparatus may include: a processor 1001, such as a CPU, a memory 1005, and a communication bus 1002. The communication bus 1002 is used to realize connection and communication between the processor 1001 and the memory 1005. The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a memory device separate from the processor 1001 described above.
Optionally, the data acquisition device may further include a rectangular user interface, a network interface, a camera, RF (Radio Frequency) circuitry, a sensor, audio circuitry, a WiFi module, and so on. The rectangular user interface may comprise a Display screen (Display), an input sub-module such as a Keyboard (Keyboard), and the optional rectangular user interface may also comprise a standard wired interface, a wireless interface. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface).
Those skilled in the art will appreciate that the data acquisition device configuration shown in fig. 3 is not meant to be limiting as the data acquisition device may include more or less components than shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 3, a memory 1005, which is a storage medium, may include an operating system, a network communication module, and a data collection program. An operating system is a program that manages and controls the hardware and software resources of the data collection device, supporting the operation of the data collection program as well as other software and/or programs. The network communication module is used for implementing communication between the components in the memory 1005 and with other hardware and software in the data acquisition method, apparatus, device and storage medium.
In the data acquisition apparatus shown in fig. 3, the processor 1001 is configured to execute a data acquisition program stored in the memory 1005 to implement the steps of the data acquisition method described in any one of the above.
The specific implementation of the data acquisition device of the present application is substantially the same as that of each embodiment of the data acquisition method, and is not described herein again.
The present application further provides a data collection device, the data collection device includes:
the transmitting module is used for determining an acquisition target and transmitting an acquisition signal to the acquisition target based on a DBF communication channel;
the acquisition module is used for converting interference signals in the data signals into a preset form based on a preset filtering model and the signal identification information so as to extract target data signals from the data signals based on the signal identification information;
the extraction module is used for converting the interference signals in the data signals into a preset form based on a preset filtering model and the signal identification information so as to extract target data signals from the data signals based on the signal identification information;
and the demodulation module is used for demodulating the target data signal to obtain target acquisition data.
Optionally, the data acquisition device further comprises:
the first calling module is used for calling the acquisition log of the data signal;
a second determination module for determining a historical data signal from the acquisition log;
the identification module is used for identifying a disguised interference signal and/or a direct interference signal from the historical signal;
and the training module is used for iteratively training a preset model to be trained based on the camouflage interference signal and/or the direct interference signal and a preset gradient to obtain a filtering model.
Optionally, the training module comprises:
the first analysis module is used for analyzing the disguising success rate of each kind of disguising interference signals and the interference success rate of each kind of direct interference signals;
the first training submodule is used for iteratively training a camouflage model in a preset model to be trained in a gradient manner based on the camouflage power and a preset gradient;
the second training sub-module is used for iteratively training the interference model in the model to be trained in a gradient manner based on the interference success rate and the preset gradient;
and the integration module is used for obtaining a filtering model based on the camouflage model and the interference model.
Optionally, the data acquisition device further comprises:
the second calling module is used for calling the acquisition log of the data signal;
the second determining module is used for determining a DBF communication channel for transmitting the acquisition signal from the acquisition log;
the second analysis module is used for analyzing the amplitude-phase error between the DBF communication channel and a preset standard channel based on a preset optimization algorithm;
and the correcting module is used for correcting the DBF communication channel in parallel based on the amplitude and phase errors.
Optionally, the second analysis module comprises:
the analysis sub-module is used for analyzing a directional diagram of the acquired signal transmitted by the DBF communication channel based on a preset optimization algorithm and determining an azimuth angle of the acquired signal transmitted by the DBF communication channel;
and the comparison module is used for comparing the azimuth angle with a preset standard angle of a standard channel to obtain an amplitude-phase error.
Optionally, the second determining module includes:
the first extraction submodule is used for extracting a historical data signal from the acquisition log;
the setting module is used for setting the historical data signal into a plurality of data sub-arrays;
and the optimization module is used for optimizing the data submatrix based on a preset genetic algorithm and determining the DBF communication channel meeting the preset requirement.
Optionally, the extraction module comprises:
the screening module is used for screening out interference signals from the data signals based on a preset filtering model to obtain collected data signals;
and the second extraction submodule is used for extracting a target data signal corresponding to the signal identification information from the acquired signal.
The specific implementation of the data acquisition device of the present application is substantially the same as that of each embodiment of the data acquisition method, and is not described herein again.
The embodiment of the present application provides a storage medium, and the storage medium stores one or more programs, and the one or more programs are further executable by one or more processors for implementing the steps of the data acquisition method described in any one of the above.
The specific implementation of the storage medium of the present application is substantially the same as that of the embodiments of the data acquisition method, and is not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A data acquisition method, characterized in that the data acquisition method comprises:
determining an acquisition target, and sending an acquisition signal to the acquisition target based on a DBF communication channel;
acquiring a data signal of the acquisition target based on the acquisition signal, and determining signal identification information of required data;
converting interference signals in the data signals into a preset form based on a preset filtering model and the signal identification information, so as to extract target data signals from the data signals based on the signal identification information;
and demodulating the target data signal to obtain target acquisition data.
2. The data collection method of claim 1, wherein prior to the step of converting the interference signal in the data signal into a predetermined form based on a predetermined filtering model to extract the target data signal from the data signal based on the signal identification information, the method further comprises:
calling an acquisition log of the data signal;
determining historical data signals from the acquisition log;
identifying a disguised interference signal and/or a direct interference signal from the historical signal;
and iteratively training a preset model to be trained based on the disguised interference signal and/or the direct interference signal and a preset gradient to obtain a filtering model.
3. The data acquisition method as claimed in claim 2, wherein the step of iteratively training a preset model to be trained based on the disguised interference signal and/or the direct interference signal and a preset gradient to obtain a filtering model comprises:
analyzing the disguise success rate of each kind of disguise interference signal and the interference success rate of each kind of direct interference signal;
iteratively training a preset camouflage model in a model to be trained in a gradient manner based on the camouflage success rate and a preset gradient;
iteratively training an interference model in the model to be trained in a gradient manner based on the interference success rate and the preset gradient;
and obtaining a filtering model based on the camouflage model and the interference model.
4. The data acquisition method as claimed in claim 1, wherein before the step of transmitting an acquisition signal to the acquisition target based on the DBF communication channel, the method comprises:
calling an acquisition log of the data signal;
determining a DBF communication channel for transmitting an acquisition signal from the acquisition log;
analyzing an amplitude-phase error between the DBF communication channel and a preset standard channel based on a preset optimization algorithm;
and correcting the DBF communication channel in parallel based on the amplitude and phase errors.
5. The data acquisition method as claimed in claim 4, wherein the step of analyzing the amplitude-phase error between the DBF communication channel and a preset standard channel based on a preset optimization algorithm comprises:
analyzing a directional diagram of the collected signal transmitted by the DBF communication channel based on a preset optimization algorithm, and determining an azimuth angle of the collected signal transmitted by the DBF communication channel;
and comparing the azimuth angle with a preset standard angle of a standard channel to obtain an amplitude-phase error.
6. The data collection method of claim 4, wherein the step of determining a DBF communication channel for transmitting the collection signal from the collection log comprises:
extracting historical data signals from the acquisition logs;
setting the historical data signal into a plurality of data sub-arrays;
and optimizing the data submatrix based on a preset genetic algorithm, and determining a DBF communication channel meeting preset requirements.
7. The data acquisition method as claimed in claim 1, wherein the step of converting the interference signal in the data signal into a predetermined form based on the predetermined filtering model and the signal identification information to extract the target data signal from the data signal based on the signal identification information comprises:
screening out interference signals from the data signals based on a preset filtering model to obtain collected data signals;
and extracting a target data signal corresponding to the signal identification information from the acquired signal.
8. A data acquisition device, characterized in that the data acquisition device comprises:
the transmitting module is used for determining an acquisition target and transmitting an acquisition signal to the acquisition target based on a DBF communication channel;
the acquisition module is used for acquiring the data signal of the acquisition target based on the acquisition signal and determining the signal identification information of the required data;
the extraction module is used for converting the interference signals in the data signals into a preset form based on a preset filtering model and the signal identification information so as to extract target data signals from the data signals based on the signal identification information;
and the demodulation module is used for demodulating the target data signal to obtain target acquisition data.
9. A data acquisition device, characterized in that the data acquisition device comprises: a memory, a processor, and a program stored on the memory for implementing the data acquisition method,
the memory is used for storing a program for realizing the data acquisition method;
the processor is configured to execute a program implementing the data acquisition method to implement the steps of the data acquisition method according to any one of claims 1 to 7.
10. A storage medium having stored thereon a program for implementing a data acquisition method, the program for implementing the data acquisition method being executed by a processor for implementing the steps of the data acquisition method according to any one of claims 1 to 7.
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