CN115801030A - Carrier automatic searching system and searching method thereof - Google Patents
Carrier automatic searching system and searching method thereof Download PDFInfo
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Abstract
The invention discloses a carrier automatic search system and a search method thereof, which mainly solve the problems that the dynamic range of signal level is large, and the probability of false detection and missed detection of signal search is relatively high when the energy of a noise substrate is uneven. The system comprises a hardware control module, a receiver, an intermediate frequency preprocessing module, a digital acquisition system, a signal search module, an output control module, a back-end processing database and a network data sharing module. The system utilizes the receiver, the intermediate frequency preprocessing module and the digital acquisition system to complete the functions of signal receiving, down conversion, filtering, gain control, intermediate frequency preprocessing, digital acquisition and the like, and obtains intermediate frequency sampling data. The system sets and controls hardware according to search requirements, processes and detects the intermediate digital signals, combines detection results with a rear-end database for analysis and mining, completes signal screening, finds signal change rules, counts signal occupancy rate, and finally realizes electromagnetic situation analysis of the observed object.
Description
Technical Field
The invention belongs to the technical field of mobile communication, and particularly relates to an automatic carrier search system and a search method thereof.
Background
Signal searching refers to searching for signals in a multidimensional space and multiple sampling values, judging the existence of the signals according to a certain criterion, and intercepting the detected signal samples to a proper length to estimate basic parameters of the signals, such as center frequency, bandwidth and the like. Research has shown that a signal can be completely determined by the time domain, the frequency domain, the polarization domain and the incoming wave direction domain. Considering different existing domains aiming at the same signal can obtain different results, and because the communication signal occupies different frequency channels, which is the biggest and most outstanding characteristic of the communication signal, in most cases, signal search is completed in a frequency domain, namely, in a wider observation frequency band, signal blind detection is performed under the condition that parameters such as the number of signals, carrier frequency, bandwidth, signal-to-noise ratio and the like are unknown. The signal search is the premise of implementing effective monitoring, high-efficiency interference and information acquisition, and has important significance in the field of electromagnetic spectrum monitoring. At present, two methods, namely manual signal searching and automatic signal searching, are mainly adopted for signal searching.
The manual signal search refers to the search and detection of signals in a specified frequency band by means of instruments such as a frequency spectrograph, an oscilloscope, a vector analyzer and a receiver and by means of observing frequency spectrum distribution and monitoring sound by experienced professionals and manually tuning the frequency of the receiver. The method has the advantages of low false detection probability, low missed detection probability in a smaller search frequency band range and the like, and is still generally adopted in actual work. However, the method has low working efficiency, complex operation procedures and high requirements on the quality of workers, and is difficult to meet the increasingly complex electromagnetic signal monitoring requirements. Therefore, the automatic signal search method has become an important research point in signal search.
An automatic signal search method, also called an electrical scanning signal search method, is generally based on a software radio concept, and utilizes developed signal analysis processing software to analyze and compare time domain, frequency domain or time-frequency domain characteristics of captured broadband data on a general hardware platform to realize automatic signal search and discovery. The method has the advantages of high speed and high efficiency, and the false detection and missing detection probability of automatic signal search is lower under the conditions that the background level of a channel is relatively flat and the signal change is relatively small. For example, the signal search in the normal satellite channel has better practical application effect. However, for a specific area satellite signal, due to the large dynamic range of signal level and uneven noise floor energy, the probability of false detection and missed detection of signal search is relatively high.
Disclosure of Invention
The invention aims to provide an automatic carrier search system and a search method thereof, which mainly solve the problems that the dynamic range of signal level is large, and the probability of false detection and missed detection of signal search is relatively high when the energy of a noise substrate is uneven.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a carrier automatic search system comprising:
the hardware control module receives a control instruction of system software to realize control on system hardware;
a receiver that receives a sampled signal;
the intermediate frequency preprocessing module is used for performing intermediate frequency preprocessing on the sampling signal;
the digital acquisition system is used for carrying out digital acquisition to obtain an intermediate frequency sampling signal;
the signal searching module sends a signal searching instruction to the hardware control module, and the intermediate frequency sampling signal is processed and detected;
the output control module controls the input and output data transmission of the signal search module;
and the back end processes the database, combines the detection result with the back end database for analysis and mining, completes signal screening, finds the signal change rule, counts the signal occupancy rate, and realizes the electromagnetic situation analysis of the observed object.
Furthermore, the invention also comprises a network data sharing module which is used for sharing the detection result of the signal searching module and the analysis result of the back-end processing database.
Based on the search system, the invention also provides an automatic carrier search method, which comprises the following steps:
s1, performing power spectrum estimation on a search channel by adopting a multi-window spectrum estimation method; according to the actual receiver bandwidth, a sliding window method of center frequency stepping is adopted to realize signal spectrum estimation, and then a complete spectrum is obtained through a channel frequency band splicing technology;
s2, performing continuous wavelet transform on the power spectrum of the obtained signal;
s3, preliminarily determining singular points according to extreme points of the large-scale wavelet transform coefficients: assuming Pi (n) is a wavelet transform coefficient of scale i, then there are:
wherein Pi' (n) is a module extreme point array of Pi (n), and M is a judgment extreme point comparison range selected according to actual conditions;
s4, removing pseudo singular points through windowing summation: selecting a proper window function, respectively summing the Pi (n) by taking the extreme point Pi ' (n) of the large-scale wavelet transform as a center to obtain Pi ' (n), wherein if the Pi ' (n) is greater than a preset threshold, the n is the position of a singular point, otherwise, the n is a pseudo singular point; namely:
s5, dividing the broadband frequency spectrum into a plurality of sub-band frequency spectrums according to the singular point positions obtained in the step S4, and calculating the average power of each sub-band frequency spectrum;
s6, calculating a detection threshold according to the average power of each sub-band, comparing the detection threshold with a set threshold L, and judging whether the detection threshold carries a signal or not so as to complete signal search; wherein, the judging process is as follows: the system adopts three relevant decision thresholds to realize the search of one signal: searching a threshold l, an amplitude threshold a and a bandwidth threshold b; firstly, determining the area of which the signal energy exceeds a search threshold l as a suspicious signal, and then roughly estimating relevant parameters of the suspicious signal: and comparing the relative amplitude, the estimated bandwidth and the central frequency with a preset amplitude threshold a and a preset bandwidth threshold b respectively, if the relative amplitude and the estimated bandwidth both exceed the corresponding thresholds, judging the signals as search signals, otherwise, judging the signals as noise.
Further, in step S6, the method for calculating the detection threshold includes:
firstly, selecting 2N +1 sub-band by taking the sub-band k to be judged as the center, carrying out sorting operation on the average power of the sub-band, then removing signals with larger power, averaging the residual data to be used as the average power of noise, and adding an empirical constant to the average power of the noise to be used as a detection threshold, namely:
wherein the scale factor is a ratio of the total number of the pixels,
meaning that the rounding is done down,
presentation pair
The order is ascending, C represents an empirical constant, and N is a constant.
Compared with the prior art, the invention has the following beneficial effects:
(1) The invention utilizes the receiver, the intermediate frequency preprocessing module and the digital acquisition system to complete the functions of signal receiving, down conversion, filtering, gain control, intermediate frequency preprocessing, digital acquisition and the like, and obtains intermediate frequency sampling data. Considering that the frequency of satellite signals is up to several GHz, in order to reduce the requirement on an acquisition module and reduce the subsequent operation data volume, the system adopts intermediate frequency band-pass sampling to digitize the signals. The actual receiving bandwidth of the receiver is often much smaller than the designated searching bandwidth of the system, so the system adopts the idea of step-by-step and segment receiving, namely, the designated bandwidth is searched segment by changing the center frequency of the receiver. The hardware control module sets and controls hardware according to the search requirement, processes and detects the intermediate digital signals, combines the detection result with a rear-end database for analysis and mining, completes signal screening, finds out the signal change rule, counts the signal occupancy rate, and finally realizes the electromagnetic situation analysis of the observation object, thereby realizing the automatic search of the signals.
(2) The minimum carrier-to-noise ratio and the minimum bandwidth of the search signal are respectively limited by using the amplitude threshold and the bandwidth threshold in the searching method, the minimum carrier-to-noise ratio and the minimum bandwidth can be set according to some prior knowledge of the current electromagnetic background, and if the minimum carrier-to-noise ratio and the minimum bandwidth are set properly, the false alarm probability can be reduced, and the reliability of the signal searching result can be improved.
Drawings
FIG. 1 is a schematic structural diagram of the present invention.
Fig. 2 is a graph of a spectrum of an actual satellite signal in an embodiment of the present invention.
FIG. 3 is a diagram illustrating the effect of the singular point detection algorithm in the embodiment of the present invention.
Detailed Description
The present invention will be further described with reference to the following description and examples, which include but are not limited to the following examples.
Examples
As shown in fig. 1, the carrier automatic search system disclosed in the present invention includes a hardware control module, a receiver, an intermediate frequency preprocessing module, a digital acquisition system, a signal search module, an output control module, a back-end processing database and a network data sharing module. The system utilizes the receiver, the intermediate frequency preprocessing module and the digital acquisition system to complete the functions of signal receiving, down conversion, filtering, gain control, intermediate frequency preprocessing, digital acquisition and the like, and obtains intermediate frequency sampling data. Considering that the frequency of satellite signals is up to several GHz, in order to reduce the requirement on an acquisition module and reduce the subsequent operation data volume, the system adopts intermediate frequency band-pass sampling to digitize the signals. The actual receiving bandwidth of the receiver is often much smaller than the designated searching bandwidth of the system, so the system adopts the idea of step-by-step and segment receiving, namely, the designated bandwidth is searched segment by changing the center frequency of the receiver. The hardware control module sets and controls hardware according to search requirements, processes and detects the intermediate digital signals, combines detection results with a back-end database for analysis and mining, completes signal screening, finds signal change rules, counts signal occupancy rate, and finally realizes electromagnetic situation analysis of the observed object, thereby realizing automatic search of signals.
And the system is also provided with a network data sharing module which is used for sharing the detection result of the signal searching module and the analysis result of the back-end processing database.
In this embodiment, the carrier automatic search method is as follows:
s1, performing power spectrum estimation on a search channel by adopting a multi-window spectrum estimation method; according to the actual receiver bandwidth, a sliding window method of central frequency stepping is adopted to realize signal spectrum estimation, and then a complete spectrum is obtained through a channel frequency band splicing technology;
s2, performing continuous wavelet transform on the power spectrum of the obtained signal;
s3, preliminarily determining singular points according to extreme points of the large-scale wavelet transform coefficients: assuming Pi (n) is a wavelet transform coefficient with a scale i, there are:
wherein Pi' (n) is a module extreme point array of Pi (n), and M is a judgment extreme point comparison range selected according to actual conditions;
s4, removing pseudo singular points through windowing summation: selecting a proper window function, respectively taking a large-scale wavelet transformation extreme point Pi ' (n) as a center to calculate partial sum of Pi (n) to obtain Pi ' (n), if Pi ' (n) is greater than a preset threshold, n is a singular point position, otherwise, n is a pseudo singular point; namely:
s5, dividing the broadband frequency spectrum into a plurality of sub-band frequency spectrums according to the singular point positions obtained in the step S4, and calculating the average power of each sub-band frequency spectrum;
s6, calculating a detection threshold according to the average power of each sub-band, comparing the detection threshold with a set threshold L, and judging whether the detection threshold carries a signal or not so as to complete signal search; wherein the judging process is as follows: the system adopts three relevant decision thresholds to realize the search of one signal: searching a threshold l, an amplitude threshold a and a bandwidth threshold b; firstly, determining the area of which the signal energy exceeds a search threshold l as a suspicious signal, and then roughly estimating relevant parameters of the suspicious signal: and comparing the relative amplitude, the estimated bandwidth and the center frequency with a preset amplitude threshold a and a preset bandwidth threshold b respectively, judging as a search signal if the relative amplitude and the estimated bandwidth both exceed the corresponding thresholds, and judging as noise if the relative amplitude and the estimated bandwidth do not exceed the corresponding thresholds.
The method for calculating the detection threshold comprises the following steps:
firstly, selecting 2N +1 sub-band by taking the sub-band k to be determined as the center, sorting the average power of the sub-band, then removing the signal with larger power, averaging the residual data to be used as the average power of noise, and taking the average power of the noise plus an empirical constant as a detection threshold, namely:
wherein the scale factor is a ratio of the total number of the pixels,
meaning that the rounding is done down,
pair of representations
The sorting was performed in ascending order, C represents an empirical constant and N is a constant.
In the embodiment, the minimum carrier-to-noise ratio and the minimum bandwidth of the search signal are respectively limited by using the amplitude threshold and the bandwidth threshold, the minimum carrier-to-noise ratio and the minimum bandwidth can be set according to some priori knowledge of the current electromagnetic background, and if the setting is proper, the false alarm probability can be reduced, and the reliability of the signal search result is improved.
And comparing the performances of the two detection algorithms under the actual satellite signal environment. The experiment adopts a C-band satellite signal intercepted by a third-party receiver from a satellite in a certain area, and a part of the signal with the center frequency of 4082MHz is intercepted. Fig. 2 shows a frequency spectrum diagram of the intercepted signal, and it can be seen that the direction signal is obviously different from the frequency spectrum diagram of the satellite signal in the normal channel environment, and the signal cannot be simply searched by adopting a single threshold.
Fig. 3 shows the detection results obtained by the signal detection algorithm using wavelet double noise suppression. The method used by the scheme has a good detection effect through the effect graph.
The above-mentioned embodiment is only one of the preferred embodiments of the present invention, and should not be used to limit the scope of the present invention, but any insubstantial modifications or changes made in the spirit and the spirit of the main design of the present invention, which still solves the technical problems consistent with the present invention, should be included in the scope of the present invention.
Claims (4)
1. A carrier automatic search system, comprising:
the hardware control module receives a control instruction of system software to realize control on system hardware;
a receiver receiving a sampled signal;
the intermediate frequency preprocessing module is used for performing intermediate frequency preprocessing on the sampling signal;
the digital acquisition system is used for carrying out digital acquisition to obtain an intermediate frequency sampling signal;
the signal searching module sends a signal searching instruction to the hardware control module, and the intermediate frequency sampling signal is processed and detected;
the output control module controls the input and output data transmission of the signal search module;
and the back end processes the database, combines the detection result with the back end database for analysis and mining, completes signal screening, finds the signal change rule, counts the signal occupancy rate, and realizes the electromagnetic situation analysis of the observed object.
2. The system according to claim 1, further comprising a network data sharing module for sharing the detection result of the signal searching module and the analysis result of the back-end processing database.
3. A carrier automatic search method, characterized in that the search system of claim 2 is adopted, comprising the steps of:
s1, performing power spectrum estimation on a search channel by adopting a multi-window spectrum estimation method; according to the actual receiver bandwidth, a sliding window method of central frequency stepping is adopted to realize signal spectrum estimation, and then a complete spectrum is obtained through a channel frequency band splicing technology;
s2, performing continuous wavelet transform on the power spectrum of the obtained signal;
s3, preliminarily determining singular points according to extreme points of the large-scale wavelet transform coefficients: assuming Pi (n) is a wavelet transform coefficient of scale i, then there are:
wherein Pi' (n) is a module extreme point array of Pi (n), and M is a judgment extreme point comparison range selected according to actual conditions;
s4, removing pseudo singular points through windowing summation: selecting a proper window function, respectively summing the Pi (n) by taking the extreme point Pi ' (n) of the large-scale wavelet transform as a center to obtain Pi ' (n), wherein if the Pi ' (n) is greater than a preset threshold, the n is the position of a singular point, otherwise, the n is a pseudo singular point; namely:
s5, dividing the broadband frequency spectrum into a plurality of sub-band frequency spectrums according to the singular point positions obtained in the step S4, and calculating the average power of each sub-band frequency spectrum;
s6, calculating a detection threshold according to the average power of each sub-band, comparing the detection threshold with a set threshold L, and judging whether the detection threshold carries a signal or not so as to complete signal search; wherein the judging process is as follows: the system uses three relevant decision thresholds to realize the search of one signal: searching a threshold l, an amplitude threshold a and a bandwidth threshold b; firstly, determining the area of which the signal energy exceeds a search threshold l as a suspicious signal, and then roughly estimating relevant parameters of the suspicious signal: and comparing the relative amplitude, the estimated bandwidth and the center frequency with a preset amplitude threshold a and a preset bandwidth threshold b respectively, judging as a search signal if the relative amplitude and the estimated bandwidth both exceed the corresponding thresholds, and judging as noise if the relative amplitude and the estimated bandwidth do not exceed the corresponding thresholds.
4. The method according to claim 3, wherein in the step S6, the detection threshold is calculated by:
firstly, selecting 2N +1 sub-band by taking the sub-band k to be determined as the center, sorting the average power of the sub-band, then removing the signal with larger power, averaging the residual data to be used as the average power of noise, and taking the average power of the noise plus an empirical constant as a detection threshold, namely:
wherein xi epsilon (0, 1) is a scaling factor,
meaning that the rounding is done down,
presentation pair
The sorting was performed in ascending order, C represents an empirical constant and N is a constant.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001230689A (en) * | 2000-02-15 | 2001-08-24 | Toshiba Corp | Ground-wave broadcasting receiver |
| CN1615004A (en) * | 2004-09-03 | 2005-05-11 | 杭州国芯科技有限公司 | Automatic channel searching method in digital Tv-set |
| JP2009005048A (en) * | 2007-06-21 | 2009-01-08 | Mitsubishi Electric Corp | Digital broadcast receiver |
| CN101914532A (en) * | 2002-11-22 | 2010-12-15 | 生物智囊团株式会社 | Method of detecting target base sequence of rna interference |
| EP2469783A1 (en) * | 2010-12-23 | 2012-06-27 | The Swatch Group Research and Development Ltd. | FSK radio signal receiver with high-sensitivity demodulator and method for operating said receiver |
| CN102892037A (en) * | 2011-07-22 | 2013-01-23 | 中兴通讯股份有限公司 | CMMB (China mobile multimedia broadcasting) terminal receiving method and device |
| WO2013093956A1 (en) * | 2011-12-19 | 2013-06-27 | 三菱電機株式会社 | Broadcasting receiver, broadcast station search method for broadcast receiver, and navigation device provided with broadcast receiver |
| JP2013131927A (en) * | 2011-12-21 | 2013-07-04 | Pioneer Electronic Corp | Broadcast reception apparatus and broadcast reception method |
| CN206096437U (en) * | 2016-10-28 | 2017-04-12 | 成都老鹰信息技术有限公司 | Civilian unmanned aerial vehicle system of catching based on three -dimensional radar |
-
2022
- 2022-10-13 CN CN202211251400.0A patent/CN115801030B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001230689A (en) * | 2000-02-15 | 2001-08-24 | Toshiba Corp | Ground-wave broadcasting receiver |
| CN101914532A (en) * | 2002-11-22 | 2010-12-15 | 生物智囊团株式会社 | Method of detecting target base sequence of rna interference |
| CN1615004A (en) * | 2004-09-03 | 2005-05-11 | 杭州国芯科技有限公司 | Automatic channel searching method in digital Tv-set |
| JP2009005048A (en) * | 2007-06-21 | 2009-01-08 | Mitsubishi Electric Corp | Digital broadcast receiver |
| EP2469783A1 (en) * | 2010-12-23 | 2012-06-27 | The Swatch Group Research and Development Ltd. | FSK radio signal receiver with high-sensitivity demodulator and method for operating said receiver |
| CN102892037A (en) * | 2011-07-22 | 2013-01-23 | 中兴通讯股份有限公司 | CMMB (China mobile multimedia broadcasting) terminal receiving method and device |
| WO2013093956A1 (en) * | 2011-12-19 | 2013-06-27 | 三菱電機株式会社 | Broadcasting receiver, broadcast station search method for broadcast receiver, and navigation device provided with broadcast receiver |
| JP2013131927A (en) * | 2011-12-21 | 2013-07-04 | Pioneer Electronic Corp | Broadcast reception apparatus and broadcast reception method |
| CN206096437U (en) * | 2016-10-28 | 2017-04-12 | 成都老鹰信息技术有限公司 | Civilian unmanned aerial vehicle system of catching based on three -dimensional radar |
Non-Patent Citations (2)
| Title |
|---|
| 江胜文;: "电磁环境自动监测和评估分析", 中国无线电, no. 01 * |
| 薛会军;: "对日常无线电频谱监测中若干技术问题的探讨", 中国无线电, no. 07 * |
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