CN115765820B - Data acquisition method, device, equipment and storage medium - Google Patents
Data acquisition method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN115765820B CN115765820B CN202310032464.XA CN202310032464A CN115765820B CN 115765820 B CN115765820 B CN 115765820B CN 202310032464 A CN202310032464 A CN 202310032464A CN 115765820 B CN115765820 B CN 115765820B
- Authority
- CN
- China
- Prior art keywords
- signal
- acquisition
- data
- interference
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The application discloses a data acquisition method, a device, equipment and a storage medium, and relates to the technical field of microwave antennas, wherein the method comprises the following steps: determining an acquisition target, and transmitting an acquisition signal to the acquisition target based on a DBF communication channel; based on the acquisition signals, acquiring data signals of an acquisition target, and determining signal identification information of required data; converting an interference signal in the data signal into a preset form based on a preset filtering model and signal identification information so as to extract a target data signal from the data signal based on the signal identification information; demodulating the target data signal to obtain target acquisition data. In the method, the DBF communication channel is used for sending signals or data signals, the acquired signals and the data signals are converted into signals in the form of digital beams in the transmission process, so that the time for converting the acquired target into the signals is shortened, the interference signals are filtered through the filtering model, the time for identifying various interference signals is shortened, and the data acquisition rate of the radar is improved.
Description
Technical Field
The present disclosure relates to the field of microwave antennas, and in particular, to a data acquisition method, apparatus, device, and storage medium.
Background
As the application field of communication technology is becoming wider, DBF (digital beamforming) is also applied to the radar field.
The DBF is applied to the radar field, can extract useful signals from received data signals, inhibit interference signals, determine the azimuth of the received signals and improve the accuracy of radar data acquisition. However, due to the influence of the environment, errors are easy to occur in the DBF communication channel, so that signal transmission is biased, accuracy of receiving or transmitting data signals by the radar is further affected, errors are easy to occur between the data signals received by the radar and the data signals transmitted by the signal source, and further data collection rate of the radar is reduced.
Disclosure of Invention
The main purpose of the application is to provide a data acquisition method, a device, equipment and a storage medium, which aim at solving the technical problems that in the prior art, radar acquisition data can be interfered by interference signals, errors are easy to occur in a DBF communication channel, and the rate of radar acquisition data is reduced.
In order to achieve the above object, the present application provides a data acquisition method, including:
determining an acquisition target and transmitting an acquisition signal to the acquisition target based on a DBF communication channel;
based on the acquisition signals, acquiring data signals of the acquisition targets, and determining signal identification information of required data;
converting an 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;
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 the 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 camouflage interference signal and/or a direct interference signal from the historical signal;
and based on the camouflage interference signal and/or the direct interference signal and a preset gradient, iteratively training a preset model to be trained to obtain a filtering model.
Optionally, the step of 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 includes:
analyzing the camouflage success rate of each camouflage interference signal and the interference success rate of each direct interference signal;
based on the camouflage success rate and a preset gradient, performing gradient iterative training on a camouflage model in a preset model to be trained;
based on the interference success rate and the preset gradient, iteratively training an interference model in the model to be trained according to the 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 the acquisition signals 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;
the DBF communication channels are corrected in parallel based on the amplitude and phase errors.
Optionally, the step of analyzing the amplitude-phase error between the DBF communication channel and the preset standard channel based on the preset optimization algorithm includes:
analyzing a directional diagram of the DBF communication channel for transmitting the acquisition signals based on a preset optimization algorithm, and determining azimuth angles of the DBF communication channel for transmitting the acquisition signals;
and comparing the azimuth angle with a standard angle of a preset standard channel to obtain an amplitude-phase error.
Optionally, the step of determining a DBF communication channel for transmitting the acquisition signal from the acquisition log includes:
extracting a historical data signal from the acquisition log;
setting the history data signal as 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 to extract the target data signal from the data signal based on the signal identification information includes:
screening 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 application also provides a data acquisition device, the data acquisition device includes:
the sending module is used for determining an acquisition target and sending an acquisition signal to the acquisition target based on the DBF communication channel;
the acquisition module is used for acquiring the data signals of the acquisition targets based on the acquisition signals 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.
The application also provides a data acquisition device, the data acquisition device is entity node device, the data acquisition device includes: the data acquisition system comprises a memory, a processor and a program of the data acquisition method stored on the memory and capable of running on the processor, wherein the program of the data acquisition method can realize the steps of the data acquisition method when being executed by the processor.
The present application also provides a storage medium, where a program for implementing the above data collection method is stored, where the program for implementing the above data collection method when executed by a processor performs the steps of the above data collection method.
Compared with the prior art that the radar data acquisition process is interfered by interference signals and the DBF communication channel is easy to generate errors, the data acquisition method, device and equipment and storage medium have the advantages that in the application, an acquisition target is determined and an acquisition signal is sent to the acquisition target based on the DBF communication channel; based on the acquisition signals, acquiring data signals of the acquisition targets, and determining signal identification information of required data; converting an 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; demodulating the target data signal to obtain target acquisition data. In the application, after an acquisition target is determined, an acquisition signal is sent to the acquisition target through a DBF communication channel, the acquisition signal can be converted into a digital wave beam, so that the conversion process of the acquisition target to the acquisition signal is reduced, based on the acquisition signal, the data signal of the acquisition target is acquired, an interference signal is filtered from the data signal through a preset filtering model, the influence of the interference signal 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, namely, in the application, the acquisition signal and the data signal are sent through the DBF communication channel and are converted into signals in the form of the digital wave beam in the transmission process, the time for converting the acquisition target and the radar into the form of the signal is reduced, the interference signal is filtered through the filtering model, the time for identifying various interference signals is reduced, and the rate of radar acquisition data is further improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the 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 that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
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 acquisition method of the present application;
fig. 3 is a schematic device structure diagram of a hardware running environment according to an embodiment of the present application.
The implementation, functional features and advantages of the present application will be further described with reference to the accompanying drawings in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
An embodiment of the present application provides a data acquisition method, 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 an acquisition target, and sending an acquisition signal to the acquisition target based on a DBF communication channel;
step S20, based on the acquisition signals, acquiring data signals of the acquisition targets and determining signal identification information of required data;
step S30, converting an 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;
and step S40, demodulating the target data signal to obtain target acquisition data.
The present embodiment aims at: when the radar collects data, the influence of interference signals on the collected target data signals is reduced, and the time for transmitting the collected signals and the data signals is saved, so that the data collection 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 device belonging to a data acquisition apparatus belonging to a data acquisition system.
The collection signal may be a collection instruction, where the collection signal at least includes collected target sample information, collection frequency, collection time, collection times, and the like, and is not specifically 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 signal in the filtering model can convert the interference signal recorded in the filtering module into a preset form, so as to save the processing time of the interference signal, and further extract the target data signal from the data signal rapidly.
The method comprises the following specific steps:
step S10, determining an acquisition target, and sending an acquisition signal to the acquisition target based on a DBF communication channel;
the DBF has the capability of suppressing the interference signals, so that the probability that the acquisition signals or the target data signals are interfered by the interference signals can be reduced in the process of transmitting the acquisition signals or the data signals, namely, the interference signals in the communication channel can be reduced when the acquisition signals or the data signals are transmitted through the DBF communication channel, and the probability that the acquisition signals or the target data signals are interfered by the interference signals can be further 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 set itself to the acquisition target on the ground according to the data acquired on the ground.
In this embodiment, before determining the acquisition target and transmitting the acquisition signal to the acquisition target through the DBF communication channel, detecting the amplitude and phase of the DBF communication channel, and compensating and correcting the DBF communication channel according to the amplitude, so as to avoid the influence of the interference signal received by the communication channel on the occurrence of the transmitting address offset and/or the receiving address offset, and reduce the interference signal in the communication channel, so as to improve the accuracy of transmitting the acquisition signal to the acquisition target.
Step S20, based on the acquisition signals, acquiring data signals of the acquisition targets 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 the 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 acquisition signal when the acquisition signal is issued, and the carrying signal is added to the target data signal when the acquired target data is converted into the target data signal, so that the radar can conveniently and rapidly 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 may 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 consolidated and then converted into a target data signal, and the target data signal is sent to the acquisition radar.
Step S30, converting an 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 acquired data signals, so that the condition that the acquired data signals in the data signals cannot be directly and rapidly identified is avoided.
In this embodiment, different types of interference signals and different forms of interference signals are set in the filtering model, so that the interference signals set in the filtering model can be identified from the data signals, and the interference signals are converted into a preset form for the acquisition radar to extract the target signals from the identified data signals.
If the target data signal is not provided with a 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 a collected data signal, and the target data signal is extracted from the data signal through the identification information.
In this embodiment, the filtering model is used to filter out 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 that the target data signal carries the interference 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 the preset filtering model and the signal identification information to extract the target data signal from the data signal based on the signal identification information includes:
step S31, based on a preset filtering model, interference signals are screened out from the data signals, and acquired data signals are obtained;
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 adopted.
It should be noted that, the collected data signal at least includes a target data signal, and may further include a carried data signal, and if the target data does not carry carried data and the collected target does not add protection information on the target data, the collected data signal includes the target data signal. If the target data carries the carrying data and/or the acquisition target adds the protection information on the target data, the acquisition data signal comprises a target data signal and a carrying data signal, wherein the carrying data signal is a signal for transmitting the carrying data.
In this embodiment, the interference signal in the data signal is filtered by 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 step 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 locally preset modulation and coding strategy, so as to obtain the collected target data locally.
Step S10, determining an acquisition target, and sending an acquisition signal to the acquisition target based on a DBF communication channel;
step S20, based on the acquisition signals, acquiring data signals of the acquisition targets and determining signal identification information of required data;
step S30, converting an 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;
step S40, demodulating the target data signal to obtain target acquisition data
In this embodiment, after an acquisition target is determined, an acquisition signal containing target sample information is sent through a communication channel in a DBF form, in the process of transmitting the acquisition signal, the acquisition signal can be converted into a signal in a digital beam form, so as to increase the transmission speed, and reduce the interference probability of an interfered signal.
Compared with the prior art that the radar data acquisition process is interfered by interference signals and the DBF communication channel is easy to generate errors, the data acquisition method, device and equipment and storage medium have the advantages that in the application, an acquisition target is determined and an acquisition signal is sent to the acquisition target based on the DBF communication channel; converting an 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; converting an 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; demodulating the target data signal to obtain target acquisition data. In the application, after an acquisition target is determined, an acquisition signal is sent to the acquisition target through a DBF communication channel, the acquisition signal can be converted into a digital wave beam, so that the conversion process of the acquisition target to the acquisition signal is reduced, based on the acquisition signal, the data signal of the acquisition target is acquired, an interference signal is filtered from the data signal through a preset filtering model, the influence of the interference signal 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, namely, in the application, the acquisition signal and the data signal are sent through the DBF communication channel and are converted into signals in the form of the digital wave beam in the transmission process, the time for converting the acquisition target and the radar into the form of the signal is reduced, the interference signal is filtered through the filtering model, the time for identifying various interference signals is reduced, and the rate of radar acquisition data is further improved.
Further, based on the foregoing embodiments of the present application, another embodiment of the present application is provided, in which, referring to fig. 2, the step of converting, based on a preset filtering model, an interference signal in the data signal into a preset form to extract, based on the signal identification information, a target data signal from the data signal, and before the step of further includes:
step S01, calling an acquisition log of the data signal;
step S02, determining a historical data signal from the acquisition log;
step S03, identifying a disguised interference signal and/or a direct interference signal from the historical signal;
step S04, based on the camouflage interference signal and/or the direct interference signal and a preset gradient, iteratively training a preset model to be trained to obtain a filtering model.
The camouflage interference signal may be an interference signal hidden in the target data signal, or may be an interference signal that is not easily recognized, such as an interference signal camouflaged 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 field in the acquisition log is updated in real time, when the target data is obtained, the target data field in the acquisition log is updated in real time, and the data signal and the acquisition data signal are also updated in real time into the acquisition log, and become the historical data in real time after being updated into the acquisition log.
The model to be trained is composed of at least two sub-models to be trained, so that different filtering sub-models can be trained conveniently according to different types of interference signals.
In this embodiment, an acquisition log of the data signal is called, the historical data signal is determined from the acquisition log, so that the historical interference signal is obtained 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 number which is not easy to identify, different sub-models to be trained are trained through corresponding iteration of different interference signals, and finally a filtering model is obtained.
It should be noted that, the interference signals used for iteratively training the model to be trained need to be filtered according to the recorded times of the interference signals in the acquisition log, data with excessively large time difference from the current time is filtered, and data in a preset time period is used, so that the interference signals learned by writing the filter model are not deleted by themselves when the filter model trained by iteration is used and currently used, so that a plurality of unusual interference signals are prevented from suddenly appearing, and the filter module cannot recognize the interference signals. That is, in this embodiment, the accuracy of identifying the interference signals 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 camouflage 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 camouflage success rate and a preset gradient, performing gradient iterative training on a camouflage 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 according to the gradient;
and step S045, obtaining a filtering model based on the camouflage model and the interference model.
The preset gradient may be the usage rate of the interference signal, or may be the interference rate of the interfered signal, which is not limited in particular.
In this embodiment, the camouflage model and the interference model in the model to be trained are trained in a gradient iteration mode to divide the training weight, and the interference signals which are easy to use are emphasized and trained, and the interference signals with frequency effects or small interference success rate are continuously trained, so that the interference signals learned by the filtering model are more comprehensive, and any interference signals are avoided being omitted in the use process.
In this embodiment, the camouflage interference signal and the direct interference signal are selected from the historical data signals in the acquisition log, the camouflage interference signal is analyzed to obtain the camouflage success rate (i.e., the interfered rate of the target data signal) and the interference success rate of the direct interference signal, the use rate of each interference signal is analyzed, and the gradient of the training weight is divided according to the use rate or the interference success rate, so that the filtering model learns each interference signal.
The newly appearing interference signal is preferentially trained for learning.
Further, based on the foregoing embodiments of the present application, another embodiment of the present application is provided, in which, before the step of transmitting 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 the acquisition signals from the acquisition log;
step A30, analyzing the amplitude-phase error between the DBF communication channel and a preset standard channel based on a preset optimization algorithm;
and step A40, correcting the DBF communication channel in parallel based on the amplitude-phase error.
In this embodiment, the DBF communication channel for transmitting the acquisition signal or receiving the data signal is determined in the acquisition day, the data of the signal is received or transmitted according to the history, the amplitude phase of the DBF communication channel is analyzed based on a preset optimization algorithm, the amplitude phase and the standard amplitude phase are compared, the amplitude phase error between the DBF communication channel and the standard amplitude phase is determined, and the DBF communication channel is corrected according to the amplitude phase error, so that the inaccurate pointing of the DBF communication channel is avoided, the error exists in the transmitted or received signal, 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 the preset standard channel based on the preset optimization algorithm includes:
step A31, analyzing a pattern of the DBF communication channel transmitting the acquisition signal based on a preset optimization algorithm, and determining an azimuth angle of the DBF communication channel transmitting the acquisition signal;
and step A32, comparing the azimuth angle with a standard angle of a preset standard channel to obtain an amplitude-phase error.
In this embodiment, the pattern of the collected signal transmitted by the DBF communication channel is analyzed by the optimization algorithm, and the pattern of the collected target receiving the collected signal is determined, so that the error between the DBF communication channel and the transmitting address of the collected radar is accurately and rapidly determined, and the error between the DBF communication channel and the receiving address of the collected target is accurately and rapidly determined.
Specifically, the step of determining a DBF communication channel for transmitting an acquisition signal from the acquisition log includes:
step A21, extracting a historical data signal from the acquisition log;
step A22, setting the historical data signal into a plurality of data subarrays;
and step 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 channels used in each data acquisition are random, the historical data signals are randomly set into a plurality of data subarrays, and the DBF communication channels with frequencies not conforming to the frequencies used in the genetic algorithm and the DBF communication channels incapable of being used continuously in each data subarray are eliminated by a preset genetic algorithm, so that the DBF communication channels with frequencies meeting the frequencies used in the genetic algorithm are determined to optimize the data subarrays, and further the DBF communication channels meeting the requirements are determined, and the waste of resources is avoided.
In this embodiment, before an acquisition signal is sent, usage information of a DBF communication channel is acquired from an acquisition log, a genetic algorithm is used to screen a DBF communication channel meeting requirements from the acquired DBF communication channels, and then a preset optimization algorithm is used to determine an amplitude-phase error of the DBF communication channel, so that 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 of the DBF communication channel is reduced, and then the rate of radar acquisition data is improved.
Referring to fig. 3, fig. 3 is a schematic device structure diagram of a hardware running environment according to an embodiment of the present application.
As shown in fig. 3, the data acquisition device may include: a processor 1001, such as a CPU, memory 1005, and a communication bus 1002. Wherein a communication bus 1002 is used to enable connected communication between the processor 1001 and a memory 1005. The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also optionally be a storage 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, an RF (Radio Frequency) circuit, a sensor, an audio circuit, a WiFi module, and the like. The rectangular user interface may include a Display screen (Display), an input sub-module such as a Keyboard (Keyboard), and the optional rectangular user interface may also include 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).
It will be appreciated by those skilled in the art that the data acquisition device structure shown in fig. 3 does not constitute a limitation of the data acquisition device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 3, an operating system, a network communication module, and a data collection program may be included in the memory 1005 as one type of storage medium. An operating system is a program that manages and controls the hardware and software resources of a data acquisition device, supporting the execution of data acquisition programs and other software and/or programs. The network communication module is used to implement communication between components within the memory 1005 and other hardware and software in the data acquisition method, apparatus, device, and storage medium.
In the data acquisition device shown in fig. 3, a processor 1001 is configured to execute a data acquisition program stored in a memory 1005, and implement the steps of the data acquisition method described in any one of the above.
The specific implementation manner of the data acquisition device is basically the same as that of each embodiment of the data acquisition method, and is not repeated here.
The application also provides a data acquisition device, the data acquisition device includes:
the sending module is used for determining an acquisition target and sending an acquisition signal to the acquisition target based on the DBF communication channel;
the acquisition module is used for converting an 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 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 includes:
the first calling module is used for calling the acquisition log of the data signal;
the second determining module is used 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 includes:
the first analysis module is used for analyzing the disguise success rate of each disguise interference signal and the interference success rate of each direct interference signal;
the first training submodule is used for iteratively training the camouflage model in the preset model to be trained according to the camouflage success rate and the preset gradient;
the second training submodule is used for iteratively training the interference model in the model to be trained according to 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 includes:
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 signals 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 correction module is used for correcting the DBF communication channel in parallel based on the amplitude-phase error.
Optionally, the second analysis module includes:
the analysis sub-module is used for analyzing the direction diagram of the DBF communication channel for transmitting the acquisition signal based on a preset optimization algorithm and determining the azimuth angle of the DBF communication channel for transmitting the acquisition signal;
and the comparison module is used for comparing the azimuth angle with a standard angle of a preset standard channel to obtain an amplitude-phase error.
Optionally, the second determining module includes:
the first extraction submodule is used for extracting historical data signals from the acquisition log;
a setting module for setting the history data signal as a plurality of data subarrays;
and the optimization module is used for optimizing the data submatrices based on a preset genetic algorithm and determining DBF communication channels meeting preset requirements.
Optionally, the extracting module includes:
the screening module is used for screening interference signals from the data signals based on a preset filtering model to obtain collected data signals;
and the second extraction sub-module is used for extracting a target data signal corresponding to the signal identification information from the acquired signal.
The specific implementation manner of the data acquisition device is basically the same as that of each embodiment of the data acquisition method, and is not repeated here.
Embodiments of the present application provide a storage medium, where one or more programs are stored, where the one or more programs are further executable by one or more processors to implement the steps of the data acquisition method described in any one of the above.
The specific implementation manner of the storage medium is basically the same as that of each embodiment of the data acquisition method, and is not repeated here.
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 one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (8)
1. A data acquisition method, the data acquisition method comprising:
invoking an acquisition log of the data signal;
determining a historical data signal from the acquisition log;
identifying a camouflage interference signal and/or a direct interference signal from the historical data signal;
analyzing the camouflage success rate of each camouflage interference signal and the interference success rate of each direct interference signal;
based on the camouflage success rate and a preset gradient, performing gradient iterative training on a camouflage model in a preset model to be trained;
based on the interference success rate and the preset gradient, iteratively training an interference model in the model to be trained according to the gradient;
obtaining a filtering model based on the camouflage model and the interference model;
determining an acquisition target and transmitting an acquisition signal to the acquisition target based on a DBF communication channel;
based on the acquisition signals, acquiring data signals of the acquisition targets, and determining signal identification information of required data, wherein the signal identification information is a signal string of an address of the acquisition targets or a preset carrying signal;
converting an interference signal in the data signal into a preset form based on the 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;
demodulating the target data signal to obtain target acquisition data.
2. The data acquisition method of claim 1, wherein prior to the step of transmitting acquisition signals to the acquisition target based on a DBF communication channel, the method comprises:
calling an acquisition log of the data signal;
determining a DBF communication channel for transmitting the acquisition signals 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;
the DBF communication channels are corrected in parallel based on the amplitude and phase errors.
3. The data acquisition method of claim 2, wherein the step of analyzing the amplitude and 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 DBF communication channel for transmitting the acquisition signals based on a preset optimization algorithm, and determining azimuth angles of the DBF communication channel for transmitting the acquisition signals;
and comparing the azimuth angle with a standard angle of a preset standard channel to obtain an amplitude-phase error.
4. The data acquisition method of claim 2 wherein the step of determining a DBF communication channel from the acquisition log that transmits an acquisition signal comprises:
extracting a historical data signal from the acquisition log;
setting the history data signal as 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.
5. The data acquisition method of claim 1, wherein the step of converting the interference signal in the data signal into a preset form based on the filtering model and the signal identification information to extract the target data signal from the data signal based on the signal identification information comprises:
based on the filtering model, screening interference signals from the data signals to obtain collected data signals;
and extracting a target data signal corresponding to the signal identification information from the acquired signal.
6. A data acquisition device, the data acquisition device comprising:
the first calling module is used for calling the acquisition log of the data signal;
the second determining module is used 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 data signal;
the first analysis module is used for analyzing the disguise success rate of each disguise interference signal and the interference success rate of each direct interference signal;
the first training submodule is used for iteratively training the camouflage model in the preset model to be trained according to the camouflage success rate and the preset gradient;
the second training submodule is used for iteratively training the interference model in the model to be trained according to the interference success rate and the preset gradient;
the integration module is used for obtaining a filtering model based on the camouflage model and the interference model;
the sending module is used for determining an acquisition target and sending an acquisition signal to the acquisition target based on the 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, wherein the signal identification information is a signal string of the address of the acquisition target or a preset carrying signal;
the extraction module is used for converting an interference signal in the data signal into a preset form based on the 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;
and the demodulation module is used for demodulating the target data signal to obtain target acquisition data.
7. A data acquisition device, the data acquisition device comprising: 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 a 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 5.
8. 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 to implement the steps of the data acquisition method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310032464.XA CN115765820B (en) | 2023-01-10 | 2023-01-10 | Data acquisition method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310032464.XA CN115765820B (en) | 2023-01-10 | 2023-01-10 | Data acquisition method, device, equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115765820A CN115765820A (en) | 2023-03-07 |
| CN115765820B true CN115765820B (en) | 2023-04-28 |
Family
ID=85348907
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310032464.XA Active CN115765820B (en) | 2023-01-10 | 2023-01-10 | Data acquisition method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115765820B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3082273A1 (en) * | 2015-04-18 | 2016-10-19 | Airbus DS Electronics and Border Security GmbH | Method and device for reduction of correlated interference in multichannel receiver systems correlated with digital beam forming |
| CN110187332A (en) * | 2019-05-15 | 2019-08-30 | 中科宇达（北京）科技有限公司 | Low-level defence radar system and method based on digital beam forming technology |
| CN113050045A (en) * | 2021-02-09 | 2021-06-29 | 中国人民解放军空军研究院战略预警研究所 | Intelligent comprehensive main and side lobe interference resisting system and method |
| WO2022021562A1 (en) * | 2020-07-29 | 2022-02-03 | 中国电子科技集团公司第十四研究所 | General collection device and method for radar state data |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FI20215606A1 (en) * | 2021-05-21 | 2022-05-24 | Nokia Solutions & Networks Oy | Scheduler information -based data acquisition and interference detection |
-
2023
- 2023-01-10 CN CN202310032464.XA patent/CN115765820B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3082273A1 (en) * | 2015-04-18 | 2016-10-19 | Airbus DS Electronics and Border Security GmbH | Method and device for reduction of correlated interference in multichannel receiver systems correlated with digital beam forming |
| CN110187332A (en) * | 2019-05-15 | 2019-08-30 | 中科宇达（北京）科技有限公司 | Low-level defence radar system and method based on digital beam forming technology |
| WO2022021562A1 (en) * | 2020-07-29 | 2022-02-03 | 中国电子科技集团公司第十四研究所 | General collection device and method for radar state data |
| CN113050045A (en) * | 2021-02-09 | 2021-06-29 | 中国人民解放军空军研究院战略预警研究所 | Intelligent comprehensive main and side lobe interference resisting system and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115765820A (en) | 2023-03-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20220113363A1 (en) | Direction of arrival estimation | |
| CN108493611B (en) | Device, method and system for rapidly aligning communication-in-motion antenna and communication satellite | |
| CN1898976A (en) | Adaptive diversity antenna system | |
| US20110150053A1 (en) | Method of detecting a radar signal, radar detection module, and wireless transceiver including the same | |
| CN111668606B (en) | Antenna configuration information processing method and device and electronic equipment | |
| CN112731486B (en) | Signal angle and signal frequency estimation method, device, equipment and storage medium | |
| CN104076368A (en) | GPS anti-interference antenna technology | |
| CN109239740B (en) | Data sending method and device and data receiving method and device | |
| CN115765820B (en) | Data acquisition method, device, equipment and storage medium | |
| CN111082844B (en) | Side lobe suppression method of microwave direction finding equipment, direction finding method and microwave direction finding equipment | |
| KR20210057302A (en) | Server, method and computer program for calculating path loss | |
| US20230170982A1 (en) | Carrier acquisition in satellite communications | |
| CN112202483B (en) | Beam forming method and device, electronic equipment and storage medium | |
| CN111934728B (en) | Digital multi-beam antenna processing method, device and equipment | |
| CN108717196B (en) | Interference removing method and system for array antenna receiving signal | |
| CN111970042A (en) | Phased array ephemeris-free first satellite alignment method, system and device and storage medium | |
| CN105629212A (en) | Method of realizing ADS-B IN by multiple beams | |
| CN111241470A (en) | Beam forming method and device based on adaptive null broadening algorithm | |
| Yann et al. | Reduction methods for accelerating optimization of radar search patterns | |
| US11963149B2 (en) | Carrier acquisition in satellite communications | |
| CN112285691B (en) | Single-beam area detection method and device and mobile equipment | |
| CN117092600B (en) | Array channel multiplexing interference cancellation method | |
| CN115396003B (en) | Method, system, equipment and medium for estimating frequency directivity characteristic of satellite system | |
| US20230397049A1 (en) | Method and apparatus for determining interference between heterogeneous services | |
| CN110784820B (en) | Wireless network equipment positioning method and device, storage medium and wireless network equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |