CN115267331B - Signal orientation positioning method and system based on multi-spectral analysis - Google Patents
Signal orientation positioning method and system based on multi-spectral analysis Download PDFInfo
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Abstract
The invention discloses a signal orientation positioning method and a signal orientation positioning system based on multi-spectral analysis, which relate to the field of data processing, wherein the method comprises the following steps: acquiring a signal to be positioned through frequency band scanning; obtaining a first group of analysis signals and a second group of analysis signals based on a signal to be positioned; transmitting the first group of analysis signals and the second group of analysis signals to a spectrum analysis system, and acquiring first signal spectrum characteristics and second signal spectrum characteristics according to a plurality of spectrum analyzers; comparing the first signal spectrum characteristic with the second signal spectrum characteristic to obtain a signal characteristic comparison result; and outputting a signal positioning result based on the signal characteristic comparison result. The technical problem of not high to the location accuracy nature of signal among the prior art, and then cause the location effect of signal not good is solved. The technical effects of improving the positioning accuracy of the signals, further improving the positioning quality of the signals and the like are achieved.
Description
Technical Field
The invention relates to the field of data processing, in particular to a signal orientation positioning method and system based on multi-spectral analysis.
Background
With the continuous development of science and technology, the demand of signal positioning is not limited to the traditional fields of navigation, aviation, aerospace, surveying and mapping, and the signal positioning is integrated with the life of people. Many network services that people use rely on signal localization. Spectral analysis is an important means for performing feature analysis on signals, and the signal features obtained through spectral analysis are important reference data for signal positioning. In the prior art, most signal characteristics are obtained through one-time spectrum analysis, the accuracy of the obtained signal characteristics is low, reliable reference data cannot be provided for signal positioning, and the quality of the signal positioning is greatly reduced. How to accurately and efficiently locate signals is widely concerned by people.
In the prior art, the technical problem that the positioning accuracy of signals is not high, and then the positioning effect of the signals is not good exists.
Disclosure of Invention
The application provides a signal orientation positioning method and system based on multi-spectral analysis. The technical problem of not high to the location accuracy nature of signal among the prior art, and then cause the location effect of signal not good is solved.
In view of the foregoing problems, the present application provides a method and a system for signal orientation positioning based on multi-spectral analysis.
In a first aspect, the present application provides a multi-spectral analysis-based signal position location method, where the method is applied to a multi-spectral analysis-based signal position location system, and the method includes: acquiring a signal to be positioned through frequency band scanning, wherein the signal to be positioned comprises real-time signals acquired at the same relative time and real-time signal sets acquired at different relative times; taking the real-time signals collected at the same relative time as a first group of analysis signals, and taking the real-time signals collected at different relative times as a second group of analysis signals; transmitting the first and second sets of analysis signals from the signal transmission device to the spectrum analysis system, wherein the spectrum analysis system is connected to a plurality of spectrum analyzers; acquiring a first signal spectrum characteristic and a second signal spectrum characteristic according to the plurality of spectrum analyzers; comparing the first signal spectrum characteristic with the second signal spectrum characteristic to obtain a signal characteristic comparison result; and outputting a signal positioning result based on the signal characteristic comparison result.
In a second aspect, the present application further provides a multi-spectral analysis based signal position location system, wherein the system comprises: the positioning device comprises a signal acquisition module, a signal processing module and a positioning module, wherein the signal acquisition module is used for acquiring a signal to be positioned through frequency band scanning, and the signal to be positioned comprises real-time signals acquired at the same relative time and real-time signal sets acquired at different relative times; the signal grouping module is used for taking the real-time signals collected at the same relative time as a first group of analysis signals and taking the real-time signals collected at different relative times as a second group of analysis signals; a signal transmission module for transmitting the first and second sets of analysis signals from a signal transmission device to a spectrum analysis system, wherein the spectrum analysis system is connected to a plurality of spectrum analyzers; the signal spectrum characteristic acquisition module is used for acquiring a first signal spectrum characteristic and a second signal spectrum characteristic according to the plurality of spectrum analyzers; the signal spectrum characteristic comparison module is used for comparing the first signal spectrum characteristic with the second signal spectrum characteristic to obtain a signal characteristic comparison result; and the signal positioning result output module is used for outputting a signal positioning result based on the signal characteristic comparison result.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
acquiring a signal to be positioned through frequency band scanning, wherein the signal to be positioned comprises real-time signals acquired at the same relative time and real-time signal sets acquired at different relative times; taking real-time signals acquired at the same relative time as a first group of analysis signals, and taking a real-time signal set acquired at different relative times as a second group of analysis signals; transmitting the first set of analysis signals and the second set of analysis signals by the signal transmission means to the spectral analysis system; performing spectrum analysis on the first group of analysis signals and the second group of analysis signals according to a spectrum analysis system to obtain first signal spectrum characteristics and second signal spectrum characteristics; comparing the first signal spectrum characteristic with the second signal spectrum characteristic to obtain a signal characteristic comparison result; and outputting a signal positioning result based on the signal characteristic comparison result. The positioning accuracy of the signals is improved, and the positioning quality of the signals is improved; meanwhile, the reliability and intelligence of positioning the signal are improved, the scientific progress of signal positioning is promoted, and the technical effect of providing reference data for further development of a signal positioning technology is achieved.
Drawings
FIG. 1 is a schematic flow chart of a signal orientation positioning method based on multi-spectral analysis according to the present application;
fig. 2 is a schematic flow chart illustrating the preprocessing of the signal to be located in the multi-spectrum analysis-based signal direction locating method according to the present invention;
FIG. 3 is a schematic flow chart illustrating the output signal positioning result in a multi-spectral analysis-based signal orientation positioning method according to the present invention;
fig. 4 is a schematic structural diagram of a signal position location system based on multi-spectral analysis according to the present application.
Description of reference numerals: the system comprises a signal acquisition module 11, a signal grouping module 12, a signal transmission module 13, a signal spectrum characteristic acquisition module 14, a signal spectrum characteristic comparison module 15 and a signal positioning result output module 16.
Detailed Description
The application provides a signal orientation positioning method and system based on multi-spectral analysis. The technical problem of not high to the location accuracy nature of signal among the prior art, and then cause the location effect of signal not good is solved. The positioning accuracy of the signals is improved, and the positioning quality of the signals is improved; meanwhile, the reliability and intelligence of positioning the signal are improved, the scientific process of signal positioning is promoted, and the technical effect of providing reference data for the further development of the signal positioning technology is achieved.
Example one
Referring to fig. 1, the present application provides a signal orientation positioning method based on multi-spectrum analysis, wherein the method is applied to a spectrum analysis system, the system is in communication connection with a signal transmission device, and the method specifically includes the following steps:
step S100: acquiring a signal to be positioned through frequency band scanning, wherein the signal to be positioned comprises real-time signals acquired at the same relative time and real-time signal sets acquired at different relative times;
further, as shown in fig. 2, step S100 of the present application further includes:
step S110: determining the influence of phase noise and the influence of frequency drift by analyzing the influence of the signal to be positioned;
step S120: generating a first influence coefficient according to the influence of the phase noise;
step S130: generating a second influence coefficient according to the frequency drift influence;
step S140: determining a signal preprocessing parameter by taking the first influence coefficient and the second influence coefficient as variables;
step S150: and preprocessing the signal to be positioned based on the signal preprocessing parameter.
Specifically, a signal to be positioned is obtained by performing frequency band scanning on the real-time signal. Further, the influence of the signal to be positioned is analyzed, and the influence of phase noise and the influence of frequency drift are obtained. The phase noise influenzability is set to a first influence coefficient and the frequency drift influenzability is set to a second influence coefficient. And taking the first influence coefficient and the second influence coefficient as variables to obtain signal preprocessing parameters, and preprocessing the signal to be positioned according to the signal preprocessing parameters. The signals to be positioned comprise real-time signals acquired at the same relative time and real-time signal sets acquired at different relative times. The real-time signals collected at the same relative time comprise a real-time signal obtained by frequency band scanning at the same relative time. The real-time signal sets collected at different relative times comprise a plurality of real-time signals obtained by frequency band scanning at different relative times. Illustratively, when a signal to be positioned is acquired, a real-time signal sent by a signal source is received through frequency band scanning, and the received real-time signal of the signal source is used as a real-time signal acquired at the same relative time. And then, continuously receiving a plurality of real-time signals sent by the signal source through frequency band scanning, taking the plurality of received real-time signals of the signal source as a real-time signal set acquired at different relative times, wherein the number of the plurality of real-time signals can be determined according to the accuracy requirement self-adaptive setting of the positioning of the signals to be positioned. The phase noise impact is parametric information that characterizes the phase change of the noise to the signal to be positioned. The frequency drift influential is parameter information used to characterize the change in frequency of the signal to be located over time. The first influence coefficient is phase noise influenceability. The second influence coefficient is frequency drift influential. The signal preprocessing parameters comprise a plurality of parameters for correcting and modulating the signal to be positioned according to the first influence coefficient and the second influence coefficient. For example, the signal pre-processing parameters include signal de-noising parameters. The technical effects that the signal to be positioned is obtained through frequency band scanning, the signal to be positioned is preprocessed through the signal preprocessing parameters, the interference of phase noise and frequency drift to the signal to be positioned is reduced, the reliability of the signal to be positioned is improved, and the accuracy of positioning the signal to be positioned is improved are achieved.
Step S200: taking the real-time signals collected at the same relative time as a first group of analysis signals, and taking the real-time signals collected at different relative times as a second group of analysis signals;
step S300: transmitting the first and second sets of analysis signals from the signal transmission device to the spectrum analysis system, wherein the spectrum analysis system is connected to a plurality of spectrum analyzers;
specifically, the obtained signals to be positioned are grouped, real-time signals collected at the same relative time are set as a first group of analysis signals, real-time signal sets collected at different relative times are set as a second group of analysis signals, and the first group of analysis signals and the second group of analysis signals are transmitted to a spectrum analysis system through a signal transmission device. Wherein the first set of analysis signals comprises real-time signals acquired at the same relative time. The second set of analytical signals comprises a set of real-time signals acquired at different relative times. The spectrum analysis system is in communication connection with the signal transmission device and the plurality of spectrum analyzers and has the functions of performing spectrum analysis on the input signal to be positioned and the like. The signal transmission device can be a signal transmission device, a signal transmission instrument and other signal transmission equipment in the prior art. The multiple spectrum analyzers are instruments for researching signal spectrum structures and signal spectrum characteristics in the prior art. The technical effects that the signals to be positioned are grouped, and the grouped first group of analysis signals and the second group of analysis signals are transmitted to the spectrum analysis system, and a foundation is laid for the subsequent spectrum analysis of the first group of analysis signals and the second group of analysis signals are achieved.
Step S400: acquiring a first signal spectrum characteristic and a second signal spectrum characteristic according to the plurality of spectrum analyzers;
further, step S400 of the present application further includes:
step S410: transmitting the first set of analysis signals to the signal transmission device;
step S420: segmenting the first group of analysis signals according to the signal transmission device, and outputting N segments of positioning signals, wherein the size of N is equal to the number of the plurality of spectrum analyzers;
step S430: respectively sending the N sections of positioning signals to the plurality of spectrum analyzers, and outputting a plurality of groups of signal spectrum characteristics according to the plurality of spectrum analyzers;
step S440: and outputting the plurality of groups of signal spectrum characteristics as the first signal spectrum characteristics.
Specifically, a first group of analysis signals is transmitted to a signal transmission device, the first group of analysis signals is segmented by the signal transmission device, and N segments of positioning signals are output. And then, sequentially inputting the N sections of positioning signals into a plurality of spectrum analyzers to obtain a plurality of groups of signal spectrum characteristics, and outputting the plurality of groups of signal spectrum characteristics as first signal spectrum characteristics. The N-segment positioning signals comprise a plurality of segments of positioning signals obtained after the signal transmission device segments the first group of analysis signals. N is equal to the number of the plurality of spectrum analyzers. The multi-group signal spectrum characteristics comprise signal parameter information such as signal distortion degree, signal modulation degree, signal spectrum purity, signal frequency stability and the like obtained by performing spectrum analysis on N sections of positioning signals through a plurality of spectrum analyzers. The multiple groups of signal spectrum characteristics and the N sections of positioning signals have corresponding relations. The first signal spectral characteristics include a plurality of sets of signal spectral characteristics. The technical effects that N sections of positioning signals are obtained by segmenting the first group of analysis signals, and accurate first signal frequency spectrum characteristics are obtained by performing frequency spectrum analysis on the N sections of positioning signals according to the plurality of frequency spectrum analyzers, so that the reliability of subsequently obtained signal positioning results is improved are achieved.
Further, after step S440, the method further includes:
step S450: transmitting the first set of analysis signals to the signal transmission device;
step S460: segmenting the first group of analysis signals according to the signal transmission device, and outputting M segments of positioning signals, wherein the size of M is equal to half of the number of the plurality of spectrum analyzers;
specifically, the signal transmission device segments the first group of analysis signals to obtain M segments of positioning signals. Wherein M has an equal relationship with half of the number of the plurality of spectrum analyzers.
Step S470: setting a spectrum analyzer comparison group according to the plurality of spectrum analyzers;
further, step S470 of the present application further includes:
step S471: performing equipment attribute analysis on the plurality of spectrum analyzers to obtain equipment attribute information;
step S472: and performing comparison group configuration on the plurality of spectrum analyzers based on the equipment attribute information to generate a spectrum analyzer comparison group for inputting the same segmented positioning signal into two spectrum analyzers, wherein M is equal to the number of the spectrum analyzer comparison groups.
Step S480: respectively sending the M sections of positioning signals to the frequency spectrograph comparison group, and outputting comparison signal frequency spectrum characteristics according to the frequency spectrograph comparison group;
step S490: and outputting the comparison signal spectrum characteristic as the first signal spectrum characteristic.
Specifically, device attribute information is obtained by analyzing device attributes of a plurality of spectrum analyzers, and a plurality of spectrum analyzers are grouped according to the device attribute information to obtain a spectrum analyzer comparison group. And further, sequentially inputting the M sections of positioning signals into a spectrometer comparison group to obtain comparison signal spectrum characteristics, and adding the comparison signal spectrum characteristics to the first signal spectrum characteristics for output. The equipment attribute information comprises equipment attribute parameter information such as model specifications, frequency ranges, frequency sweeping speeds, sensitivities and the like of the multiple spectrum analyzers. The number of the spectrometer comparison groups is M, namely the number of the spectrometer comparison groups is half of the number of the plurality of spectrum analyzers. Each spectrometer control group comprises two spectrometers with the same equipment attribute information. And when the M sections of positioning signals are sequentially input into the spectrometer comparison group, respectively inputting each section of positioning signal in the M sections of positioning signals into the two spectrum analyzers in each spectrometer comparison group for spectrum analysis. The two spectrum analyzers in each spectrum analyzer comparison group can perform spectrum analysis on each section of positioning signal, and two groups of spectrum analysis data information corresponding to each section of obtained positioning signal are compared, so that data errors caused by the spectrum analyzers are reduced, and the accuracy of the spectrum characteristics of the obtained comparison signal is improved. The comparison signal spectrum characteristics comprise signal parameter information such as signal distortion degree, signal spectrum purity, signal frequency stability and the like obtained by performing spectrum analysis on the M sections of positioning signals by a spectrometer comparison group.
In addition, when the second signal spectrum feature is obtained, the second group of analysis signals are transmitted to the spectrum analysis system, each real-time signal in the second group of analysis signals is respectively sent to the multiple spectrum analyzers, and the multiple spectrum analyzers perform spectrum analysis on the second group of analysis signals to obtain the second signal spectrum feature. The second signal spectrum characteristics comprise signal parameter information such as signal distortion degree, signal spectrum purity, signal frequency stability and the like of each real-time signal in the second group of analysis signals. The technical effects that the first group of analysis signals and the second group of analysis signals are comprehensively and accurately subjected to spectrum analysis through a plurality of spectrum analyzers, reliable first signal spectrum characteristics and second signal spectrum characteristics are obtained, and the basis is tamped for subsequently obtaining signal characteristic comparison results are achieved.
Step S500: comparing the first signal spectrum characteristic with the second signal spectrum characteristic to obtain a signal characteristic comparison result;
specifically, the first signal spectrum characteristic and the second signal spectrum characteristic are compared, and a signal characteristic comparison result is determined. The signal characteristic comparison result comprises a signal parameter information comparison condition such as signal distortion degree of the first signal spectrum characteristic and the second signal spectrum characteristic, and a signal parameter information difference condition such as signal distortion degree of the first signal spectrum characteristic and the second signal spectrum characteristic. The technical effects of obtaining the signal characteristic comparison result and providing data support for the subsequent output signal positioning result are achieved.
Step S600: and outputting a signal positioning result based on the signal characteristic comparison result.
Further, as shown in fig. 3, step S600 of the present application further includes:
step S610: acquiring a test sample signal set, wherein the test sample signal set is a signal set with a known azimuth;
step S620: carrying out sample test by using the test sample signal set, and outputting a test result, wherein the test result is a test direction;
step S630: comparing the test result with a known azimuth in the test sample signal set, and outputting a difference coefficient, wherein the difference coefficient is used for identifying the error magnitude of the azimuth test;
step S640: generating a direction adjustment feedback network layer according to the difference coefficient;
step S650: and adjusting the signal characteristic comparison result through the direction adjustment feedback network layer, and outputting a signal positioning result.
In particular, a test sample signal set may be obtained by acquiring signals at a plurality of known orientations in the historical data. The number of signals of known orientation in the test sample signal set may be set according to the accuracy requirements of the orientation adjustment feedback network layer. And further, carrying out azimuth test on the test sample signal set through the signal positioning model to obtain a test result. Then, the test result is compared with the known position in the test sample signal set to obtain a difference coefficient, a position adjustment feedback network layer is constructed based on the difference coefficient, and the position adjustment feedback network layer is embedded into the signal positioning model. The azimuth adjustment feedback network layer comprises a function, wherein the function is f (x) = gQ (x), x is a received real-time signal to be positioned, g is a difference coefficient, Q (x) is a preliminary signal positioning result based on the real-time signal x, and f (x) is an adjusted signal positioning result. And further, the signal characteristic comparison result is used as input information, a signal positioning model is input to obtain a preliminary signal positioning result, and the preliminary signal positioning result is adjusted and corrected through an azimuth adjustment feedback network layer to obtain a signal positioning result. Wherein the set of test sample signals comprises a plurality of signals of known orientation. And the test result is the azimuth information corresponding to each signal in the test sample signal set, which is obtained by carrying out azimuth test on each signal in the test sample signal set through the signal positioning model. The difference coefficients include the difference in orientation, the error in orientation, between the test result and the known orientation of each signal in the set of test sample signals. The difference coefficient is used to identify the error magnitude for performing the orientation test. That is, the difference coefficient can be used to characterize the error magnitude of the signal localization model. The signal positioning result comprises position parameter information, such as a position and a direction corresponding to the signal to be positioned. The signal positioning model is obtained through training of a large amount of data information related to a signal set of the test sample and a signal characteristic comparison result, and has functions of intelligent signal positioning and the like. The technical effects of obtaining accurate and reliable signal positioning results through the direction adjustment feedback network layer and improving the quality of positioning signals to be positioned are achieved.
Further, step S630 of the present application further includes:
step S631: judging whether the difference coefficient is larger than a preset difference coefficient or not;
step S632: if the difference coefficient is larger than the preset difference coefficient, acquiring real-time environment information for testing;
step S633: analyzing the environmental impact of the real-time environmental information and outputting an environmental impact index;
step S634: and if the environmental impact index is larger than a preset environmental impact index, acquiring reminding information.
Specifically, the obtained difference coefficient is compared with a preset difference coefficient, and whether the difference coefficient is larger than the preset difference coefficient is determined. And if the difference coefficient is larger than the preset difference coefficient, acquiring real-time environment parameters for sample testing of the test sample signal set to obtain real-time environment information. Further, an environmental impact index is obtained by analyzing the environmental impact of the real-time environmental information. And comparing the environmental influence index with a preset environmental influence index, judging whether the environmental influence index is greater than the preset environmental influence index, and if so, acquiring reminding information. The preset difference coefficient and the preset environmental influence index can be set and determined in a user-defined mode. The real-time environment information comprises real-time environment parameters such as real-time environment noise, real-time environment temperature and the like for carrying out sample testing on the test sample signal set. The environmental impact index is parameter information for characterizing environmental interference of the real-time environmental information on the sample test of the test sample signal set. The stronger the environmental interference of the real-time environmental information to the sample test of the test sample signal set, the higher the corresponding environmental impact index. The reminding information is used for representing that the environmental influence index is larger than the preset environmental influence index, the environmental interference of the sample test on the test sample signal set is high, the accuracy of the obtained test result is poor, and the sample test needs to be carried out on the test sample signal set again. The technical effects that the reminding information is acquired adaptively by analyzing the difference coefficient, and the accuracy of the acquired direction regulation feedback network layer is improved are achieved.
In summary, the signal orientation positioning method based on multi-spectrum analysis provided by the present application has the following technical effects:
1. acquiring a signal to be positioned through frequency band scanning, wherein the signal to be positioned comprises real-time signals acquired at the same relative time and real-time signal sets acquired at different relative times; taking real-time signals collected at the same relative time as a first group of analysis signals, and taking a real-time signal set collected at different relative times as a second group of analysis signals; transmitting the first and second sets of analysis signals from the signal transmission device to the spectral analysis system; performing spectrum analysis on the first group of analysis signals and the second group of analysis signals according to a spectrum analysis system to obtain first signal spectrum characteristics and second signal spectrum characteristics; comparing the first signal spectrum characteristic with the second signal spectrum characteristic to obtain a signal characteristic comparison result; and outputting a signal positioning result based on the signal characteristic comparison result. The positioning accuracy of the signals is improved, and the positioning quality of the signals is improved; meanwhile, the reliability and intelligence of positioning the signal are improved, the scientific process of signal positioning is promoted, and the technical effect of providing reference data for the further development of the signal positioning technology is achieved.
2. The signal to be positioned is obtained through frequency band scanning, the signal to be positioned is preprocessed through the signal preprocessing parameters, interference of phase noise and frequency drift on the signal to be positioned is reduced, reliability of the signal to be positioned is improved, and accuracy of positioning the signal to be positioned is improved.
3. The first group of analysis signals are segmented to obtain N segments of positioning signals, and the N segments of positioning signals are subjected to spectrum analysis according to the plurality of spectrum analyzers to obtain accurate first signal spectrum characteristics, so that the reliability of positioning the signals to be positioned is improved.
Example two
Based on the same inventive concept as the signal direction positioning method based on multi-spectrum analysis in the foregoing embodiment, the present invention further provides a signal direction positioning system based on multi-spectrum analysis, the system is communicatively connected to a signal transmission device, please refer to fig. 4, the system includes:
the positioning system comprises a signal acquisition module 11, a signal acquisition module 11 and a positioning module, wherein the signal acquisition module 11 is used for acquiring a signal to be positioned through frequency band scanning, and the signal to be positioned comprises real-time signals acquired at the same relative time and real-time signal sets acquired at different relative times;
a signal grouping module 12, wherein the signal grouping module 12 is configured to use the real-time signals collected at the same relative time as a first group of analysis signals, and use the real-time signals collected at different relative times as a second group of analysis signals;
a signal transmission module 13, wherein the signal transmission module 13 is configured to transmit the first group of analysis signals and the second group of analysis signals to a spectrum analysis system by a signal transmission device, and the spectrum analysis system is connected with a plurality of spectrum analyzers;
a signal spectrum characteristic obtaining module 14, where the signal spectrum characteristic obtaining module 14 is configured to obtain a first signal spectrum characteristic and a second signal spectrum characteristic according to the multiple spectrum analyzers;
the signal spectrum characteristic comparison module 15 is configured to compare the first signal spectrum characteristic with the second signal spectrum characteristic to obtain a signal characteristic comparison result;
a signal positioning result output module 16, where the signal positioning result output module 16 is configured to output a signal positioning result based on the signal characteristic comparison result.
Further, the system further comprises:
a first signal transmission module for transmitting the first set of analysis signals to the signal transmission device;
the first positioning signal output module is used for segmenting the first group of analysis signals according to the signal transmission device and outputting N segments of positioning signals, wherein the size of N is equal to the number of the plurality of spectrum analyzers;
the multi-group signal spectrum characteristic determining module is used for respectively sending the N sections of positioning signals to the multiple spectrum analyzers and outputting multiple groups of signal spectrum characteristics according to the multiple spectrum analyzers;
a first signal spectral feature output module, configured to output the plurality of sets of signal spectral features as the first signal spectral feature.
Further, the system further comprises:
a first execution module for transmitting the first set of analysis signals to the signal transmission device;
a second positioning signal output module, configured to segment the first group of analysis signals according to the signal transmission device, and output M segments of positioning signals, where M is equal to half of the number of the plurality of spectrum analyzers;
the spectrometer comparison group setting module is used for setting a spectrometer comparison group according to the plurality of spectrometers;
the comparison signal spectrum characteristic output module is used for respectively sending the M sections of positioning signals to the spectrometer comparison group and outputting the spectrum characteristics of the comparison signals according to the spectrometer comparison group;
a second execution module to output the comparison signal spectral feature as the first signal spectral feature.
Further, the system further comprises:
the device attribute information acquisition module is used for carrying out device attribute analysis on the plurality of spectrum analyzers to acquire device attribute information;
and the spectrometer comparison group generation module is used for performing comparison group configuration on the plurality of spectrum analyzers based on the equipment attribute information to generate a spectrometer comparison group used for inputting the same segmented positioning signal into two spectrum analyzers, wherein M is equal to the number of the spectrometer comparison groups.
Further, the system further comprises:
the influence analysis module is used for determining the influence of phase noise and the influence of frequency drift by carrying out influence analysis on the signal to be positioned;
a first influence coefficient generation module, configured to generate a first influence coefficient according to the influence of the phase noise;
a second influence coefficient generation module, configured to generate a second influence coefficient according to the frequency drift influence;
a signal preprocessing parameter determination module, configured to determine a signal preprocessing parameter by using the first influence coefficient and the second influence coefficient as variables;
a signal preprocessing module for preprocessing the signal to be positioned based on the signal preprocessing parameters.
Further, the system further comprises:
the device comprises a test sample acquisition module, a signal processing module and a signal processing module, wherein the test sample acquisition module is used for acquiring a test sample signal set, and the test sample signal set is a signal set with a known azimuth;
the test result output module is used for carrying out sample test on the test sample signal set and outputting a test result, wherein the test result is a test direction;
the difference coefficient output module is used for comparing the test result with the known azimuth in the test sample signal set and outputting a difference coefficient, wherein the difference coefficient is used for identifying the error size of the azimuth test;
the feedback network layer generating module is used for generating a direction adjusting feedback network layer according to the difference coefficient;
and the signal positioning result output module is used for adjusting the signal characteristic comparison result through the direction adjustment feedback network layer and outputting a signal positioning result.
Further, the system further comprises:
the judging module is used for judging whether the difference coefficient is larger than a preset difference coefficient or not;
the environment information acquisition module is used for acquiring real-time environment information for testing if the difference coefficient is greater than the preset difference coefficient;
the environment influence index output module is used for analyzing the environment influence of the real-time environment information and outputting an environment influence index;
and the reminding information acquisition module is used for acquiring reminding information if the environmental influence index is larger than a preset environmental influence index.
The application provides a signal orientation positioning method based on multi-spectral analysis, wherein the method is applied to a signal orientation positioning system based on multi-spectral analysis, and the method comprises the following steps: acquiring a signal to be positioned through frequency band scanning, wherein the signal to be positioned comprises real-time signals acquired at the same relative time and real-time signal sets acquired at different relative times; taking real-time signals collected at the same relative time as a first group of analysis signals, and taking a real-time signal set collected at different relative times as a second group of analysis signals; transmitting the first set of analysis signals and the second set of analysis signals by the signal transmission means to the spectral analysis system; performing spectrum analysis on the first group of analysis signals and the second group of analysis signals according to a spectrum analysis system to obtain first signal spectrum characteristics and second signal spectrum characteristics; comparing the first signal spectrum characteristic with the second signal spectrum characteristic to obtain a signal characteristic comparison result; and outputting a signal positioning result based on the signal characteristic comparison result. The technical problem of not high to the location accuracy nature of signal among the prior art, and then cause the location effect of signal not good is solved. The positioning accuracy of the signals is improved, and the positioning quality of the signals is improved; meanwhile, the reliability and intelligence of positioning the signal are improved, the scientific process of signal positioning is promoted, and the technical effect of providing reference data for the further development of the signal positioning technology is achieved.
All possible combinations of the technical features in the above embodiments may not be described for the sake of brevity, but should be considered as being within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
The specification and drawings are merely illustrative of the present application, and it is intended that the present invention cover modifications and variations of this invention provided they come within the scope of the invention and their equivalents.
Claims (8)
1. A signal orientation positioning method based on multi-spectral analysis, wherein the method is applied to a spectral analysis system, the system is connected with a signal transmission device in a communication way, and the method comprises the following steps:
acquiring a signal to be positioned through frequency band scanning, wherein the signal to be positioned comprises real-time signals acquired at the same relative time and real-time signal sets acquired at different relative times;
taking the real-time signals acquired at the same relative time as a first group of analysis signals, and taking the real-time signals acquired at different relative times as a second group of analysis signals;
transmitting the first and second sets of analysis signals from the signal transmission device to the spectrum analysis system, wherein the spectrum analysis system is connected to a plurality of spectrum analyzers;
acquiring a first signal spectrum characteristic and a second signal spectrum characteristic according to the plurality of spectrum analyzers;
comparing the first signal spectrum characteristic with the second signal spectrum characteristic to obtain a signal characteristic comparison result;
and outputting a signal positioning result based on the signal characteristic comparison result.
2. The method of claim 1, wherein the method further comprises:
transmitting the first set of analysis signals to the signal transmission device;
segmenting the first group of analysis signals according to the signal transmission device, and outputting N segments of positioning signals, wherein the size of N is equal to the number of the plurality of spectrum analyzers;
respectively sending the N sections of positioning signals to the plurality of spectrum analyzers, and outputting a plurality of groups of signal spectrum characteristics according to the plurality of spectrum analyzers;
and outputting the plurality of groups of signal spectrum characteristics as the first signal spectrum characteristics.
3. The method of claim 1, wherein the method further comprises:
transmitting the first set of analysis signals to the signal transmission device;
segmenting the first group of analysis signals according to the signal transmission device, and outputting M segments of positioning signals, wherein the size of M is equal to half of the number of the plurality of spectrum analyzers;
setting a spectrometer control group according to the plurality of spectrum analyzers;
respectively sending the M sections of positioning signals to the frequency spectrograph comparison group, and outputting comparison signal frequency spectrum characteristics according to the frequency spectrograph comparison group;
and outputting the comparison signal spectrum characteristic as the first signal spectrum characteristic.
4. The method of claim 3, wherein the method further comprises:
analyzing the equipment attribute of the plurality of spectrum analyzers to obtain equipment attribute information;
and performing contrast group configuration on the plurality of spectrum analyzers based on the equipment attribute information to generate a spectrum analyzer contrast group for inputting the same segmented positioning signal into two spectrum analyzers, wherein M is equal to the number of the spectrum analyzer contrast groups.
5. The method of claim 1, wherein the method further comprises:
determining the influence of phase noise and the influence of frequency drift by analyzing the influence of the signal to be positioned;
generating a first influence coefficient according to the influence of the phase noise;
generating a second influence coefficient according to the frequency drift influence;
determining a signal preprocessing parameter by taking the first influence coefficient and the second influence coefficient as variables;
and preprocessing the signal to be positioned based on the signal preprocessing parameter.
6. The method of claim 1, wherein the method further comprises:
acquiring a test sample signal set, wherein the test sample signal set is a signal set with a known azimuth;
carrying out sample test on the test sample signal set, and outputting a test result, wherein the test result is a test direction;
comparing the test result with a known azimuth in the test sample signal set, and outputting a difference coefficient, wherein the difference coefficient is used for identifying the error magnitude of the azimuth test;
generating a direction regulation feedback network layer according to the difference coefficient;
and adjusting the signal characteristic comparison result through the direction adjustment feedback network layer, and outputting a signal positioning result.
7. The method of claim 6, wherein the method further comprises:
judging whether the difference coefficient is larger than a preset difference coefficient or not;
if the difference coefficient is larger than the preset difference coefficient, acquiring real-time environment information for testing;
analyzing the environmental impact of the real-time environmental information and outputting an environmental impact index;
and if the environmental impact index is larger than a preset environmental impact index, acquiring reminding information.
8. A multi-spectral analysis based signal position location system, the system comprising:
the positioning device comprises a signal acquisition module, a signal processing module and a positioning module, wherein the signal acquisition module is used for acquiring a signal to be positioned through frequency band scanning, and the signal to be positioned comprises real-time signals acquired at the same relative time and real-time signal sets acquired at different relative times;
the signal grouping module is used for taking the real-time signals acquired at the same relative time as a first group of analysis signals and taking the real-time signals acquired at different relative times as a second group of analysis signals;
a signal transmission module for transmitting the first and second sets of analysis signals from a signal transmission device to a spectrum analysis system, wherein the spectrum analysis system is connected to a plurality of spectrum analyzers;
the signal spectrum characteristic acquisition module is used for acquiring a first signal spectrum characteristic and a second signal spectrum characteristic according to the plurality of spectrum analyzers;
the signal spectrum characteristic comparison module is used for comparing the first signal spectrum characteristic with the second signal spectrum characteristic to obtain a signal characteristic comparison result;
and the signal positioning result output module is used for outputting a signal positioning result based on the signal characteristic comparison result.
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Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1200811A (en) * | 1995-09-20 | 1998-12-02 | 英国国防部 | Locating source of unknown signal |
| CN102109553A (en) * | 2009-12-25 | 2011-06-29 | 北京普源精电科技有限公司 | Digital spectrum analyzer and method for fast positioning of measuring signals |
| CN104809358A (en) * | 2015-05-21 | 2015-07-29 | 哈尔滨工业大学 | Radar radiation source identification method based on phase noise unintentional modulation characteristic |
| CN105021887A (en) * | 2015-06-30 | 2015-11-04 | 北京航空航天大学 | System for automatically collecting data of electromagnetic environment for testing of data chain of unmanned plane |
| CN107733535A (en) * | 2017-09-28 | 2018-02-23 | 北京小米移动软件有限公司 | Terminal debugging method, apparatus and system |
| CN108397692A (en) * | 2018-01-29 | 2018-08-14 | 清华大学合肥公共安全研究院 | Pipe leakage recognition methods based on noise signal Time Domain Piecewise spectrum analysis |
| CN112327095A (en) * | 2020-09-29 | 2021-02-05 | 深圳供电局有限公司 | Cable fault detection method and device, computer equipment and storage medium |
| CN112910581A (en) * | 2019-11-19 | 2021-06-04 | 大唐移动通信设备有限公司 | Interference positioning method, interference positioning device and distributed base station system |
| CN113466616A (en) * | 2021-06-22 | 2021-10-01 | 海南电网有限责任公司乐东供电局 | Method and device for quickly positioning cable fault point |
| CN114089033A (en) * | 2022-01-24 | 2022-02-25 | 天津安力信通讯科技有限公司 | Abnormal signal detection method and system based on spectrum analysis |
| CN114401055A (en) * | 2021-12-17 | 2022-04-26 | 郑州中科集成电路与***应用研究院 | Intelligent frequency spectrum detection system |
| CN114979928A (en) * | 2022-05-23 | 2022-08-30 | 深圳由我智声科技有限公司 | Testing method, device and system of bone conduction earphone and storage medium |
| CN115031875A (en) * | 2022-08-11 | 2022-09-09 | 长江水利委员会长江科学院 | Vibrating wire sensor self-adaptive frequency sweep excitation method and system based on frequency spectrum feedback |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102008043394A1 (en) * | 2008-11-03 | 2010-05-06 | Robert Bosch Gmbh | Method for detecting peak overlays in a discrete spectrum of a locating signal |
| CN103546960B (en) * | 2012-07-10 | 2017-12-12 | 中国电信股份有限公司 | Localization method and system |
| CN109451529A (en) * | 2019-01-02 | 2019-03-08 | 成都华日通讯技术有限公司 | A kind of miniature spectral sensor net system and its synergistic data processing method |
-
2022
- 2022-09-29 CN CN202211200802.8A patent/CN115267331B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1200811A (en) * | 1995-09-20 | 1998-12-02 | 英国国防部 | Locating source of unknown signal |
| CN102109553A (en) * | 2009-12-25 | 2011-06-29 | 北京普源精电科技有限公司 | Digital spectrum analyzer and method for fast positioning of measuring signals |
| CN104809358A (en) * | 2015-05-21 | 2015-07-29 | 哈尔滨工业大学 | Radar radiation source identification method based on phase noise unintentional modulation characteristic |
| CN105021887A (en) * | 2015-06-30 | 2015-11-04 | 北京航空航天大学 | System for automatically collecting data of electromagnetic environment for testing of data chain of unmanned plane |
| CN107733535A (en) * | 2017-09-28 | 2018-02-23 | 北京小米移动软件有限公司 | Terminal debugging method, apparatus and system |
| CN108397692A (en) * | 2018-01-29 | 2018-08-14 | 清华大学合肥公共安全研究院 | Pipe leakage recognition methods based on noise signal Time Domain Piecewise spectrum analysis |
| CN112910581A (en) * | 2019-11-19 | 2021-06-04 | 大唐移动通信设备有限公司 | Interference positioning method, interference positioning device and distributed base station system |
| CN112327095A (en) * | 2020-09-29 | 2021-02-05 | 深圳供电局有限公司 | Cable fault detection method and device, computer equipment and storage medium |
| CN113466616A (en) * | 2021-06-22 | 2021-10-01 | 海南电网有限责任公司乐东供电局 | Method and device for quickly positioning cable fault point |
| CN114401055A (en) * | 2021-12-17 | 2022-04-26 | 郑州中科集成电路与***应用研究院 | Intelligent frequency spectrum detection system |
| CN114089033A (en) * | 2022-01-24 | 2022-02-25 | 天津安力信通讯科技有限公司 | Abnormal signal detection method and system based on spectrum analysis |
| CN114979928A (en) * | 2022-05-23 | 2022-08-30 | 深圳由我智声科技有限公司 | Testing method, device and system of bone conduction earphone and storage medium |
| CN115031875A (en) * | 2022-08-11 | 2022-09-09 | 长江水利委员会长江科学院 | Vibrating wire sensor self-adaptive frequency sweep excitation method and system based on frequency spectrum feedback |
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| Publication number | Publication date |
|---|---|
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