CN204928888U - Communication signal standard identification system - Google Patents
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- CN204928888U CN204928888U CN201520216237.3U CN201520216237U CN204928888U CN 204928888 U CN204928888 U CN 204928888U CN 201520216237 U CN201520216237 U CN 201520216237U CN 204928888 U CN204928888 U CN 204928888U
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Abstract
The utility model provides a communication signal standard identification system, including the signal reception antenna for receive communication signal, signal processing module is with signal reception antenna connection for carry out filtering, enlarge and the frequency conversion processing signal reception antenna received communication signal, wherein, communication signal becomes intermediate frequency signal after signal processing module handles, analog -to -digital conversion module is connected with signal processing module to intermediate frequency signal to after handling through signal processing module carries out filtering and digitalized treatment, and exports corresponding digital quantity, FPGA standard identification module is connected with analog -to -digital conversion module for carry out wavelet transform with the digital quantity and handle, and the variance characteristic of acquireing after handling wavelet transform with predetermine the threshold values and carry out the comparison, according to the comparative result to communication signal classification. Utilize the utility model discloses, can lower and do not have under the condition of any priori in the SNR, discern communication signal commonly used expeditiously, the discernment kind is many, the reliability is high.
Description
Technical field
The utility model relates to non-cooperative communication signaling mode recognition technology field, more specifically, relates to a kind of signal of communication standard recognition system.
Background technology
The object of communication is by channel effective, safety and precise ground transmission information fast.In order to make full use of channel capacity, extend the transmission range of signal, reduce the interference of various noise and meet the different demands of user, transmitting is all carry out on a different channel transmitting with different modulation classifications.Along with the fast development of electronic technology, and user's improving constantly transmission request message, the modulation classification of signal of communication experienced by by analog to digital, evolution from simple to complex.
In the communication of satellite non-cooperating, receiver need priori lack of knowledge or without the condition of priori under the standard of identification satellite signal of communication, obtain associated modulation parameter, and then realize the advanced communications facility of more modulation standard demodulation.In this senior satellite communication system, the standard identification of signal has very important using value, and when space channel condition changes, ground base station can select different modulation systems to carry out the change of adaptive channel.Under these conditions, there is the senior satellite communication system that signal of communication standard identifies automatically and just can identify signal in real time, obtain associated modulation parameter, realize the demodulation to signal, and then realize reliable communication.
Detect in receipts at traditional signal of communication, what Modulation Identification adopted usually is the mode that well-trained operating personnel and special equipment combine, the demodulator of multiple different modulating standard is allowed to carry out demodulation to same observation signal, manual analysis is carried out to all demodulation result, if the output of some demodulators is with significantly understanding information, then think that the modulation classification of the modulation classification that this demodulator adopts and observation signal is consistent, and it is for further analysis to record demodulation Output rusults.
Aforesaid way huge structure, complexity are high, and operating efficiency and intellectuality are all very low.When possible modulation classification only has seldom several and fairly simple, this mode just has certain feasibility.But along with wireless communication technology, the particularly develop rapidly of digital communication technology, the modulation classification of signal becomes and becomes increasingly complex, kind is also more old more, and generally all signal is carried out to the process of Source Encryption and chnnel coding before modulation, for these process, aforesaid way just no longer has feasibility.The technological approaches solved the problem, developing exactly can the modulation classification of identification communication signal and the system of modulation parameter or method automatically.
At present, the automatic identification of modulation signal does not also have Unified frame, and the method for employing is also varied.Existing primary modulation recognition methods roughly can be divided into two large classes: the statistical pattern recognition method that maximum likelihood hypothesis testing method and feature based based on decision theory extract.The former can realize good recognition effect, but it needs more priori, has huge operand, not easily meets the requirement of signal real-time process.The latter extracts characteristic parameter selected in advance from Received signal strength, carries out pattern recognition classifier according to certain decision rule.The statistical pattern recognition method that the domestic feature based to modulation signal extracts now is mainly divided into: based on the recognition methods of instantaneous amplitude, frequency and phase property, based on the recognition methods of Wavelet Transform Feature, based on the recognition methods of planisphere feature, based on the recognition methods of spectrum signature, the recognition methods etc. of Corpus--based Method measure feature.Above-mentioned most of algorithm is when signal to noise ratio is lower, low to the discrimination of signal.
Therefore, need badly a kind of when signal to noise ratio is lower high the and scheme that can identify conventional signal of communication under without any the condition of priori of discrimination.
Utility model content
In view of the above problems, the purpose of this utility model is to provide a kind of signal of communication standard recognition system, low to solve the discrimination of existing Signal analysis scheme to signal, and operand is large, needs the problems such as more priori.
The signal of communication standard recognition system that the utility model provides, comprises signal receiving antenna, for receiving communication signal; Signal processing module, is connected with signal receiving antenna, carries out filtering, amplification and frequency-conversion processing for the signal of communication received signal receiving antenna; Wherein, signal of communication becomes intermediate-freuqncy signal after signal processing module process; Analog-to-digital conversion module, is connected with signal processing module, to carry out filtering and digitized processing to the intermediate-freuqncy signal after signal processing module process, and exports corresponding digital quantity; FPGA standard identification module, is connected with analog-to-digital conversion module, for digital quantity is carried out wavelet transform process, and the Variance feature obtained after wavelet transform process and pre-set threshold value is compared, according to comparative result to signal of communication Classification and Identification.
In addition, preferred structure is that signal processing module comprises: receiving filter, carries out filtering process for the signal of communication received signal receiving antenna; LNA amplifier, is connected with receiving filter, for carrying out low noise amplification process to through the filtered signal of communication of receiving filter; Frequency mixer, is connected with LNA amplifier, for carrying out frequency-conversion processing to the signal of communication after the amplification of LNA amplifier.
In addition, preferred structure is that frequency mixer comprises: radio-frequency filter, for the high-frequency interferencing signal in the signal of communication of decaying after the process of LNA amplifier; Second low noise amplifier, is connected with radio-frequency filter, for carrying out low noise amplification process to by the signal of communication after radio-frequency filter process; Intermediate-frequency filter, is connected with the second low noise amplifier with radio-frequency filter respectively, to obtain intermediate-freuqncy signal from the signal of communication after radio-frequency filter and the second low noise amplifier process.
In addition, preferred structure is that analog-to-digital conversion module comprises: frequency overlapped-resistable filter, carries out low-pass filtering treatment for the intermediate-freuqncy signal exported signal processing module; A/D chip, is connected with frequency overlapped-resistable filter, so that the intermediate-freuqncy signal after frequency overlapped-resistable filter low-pass filtering treatment is converted to digital signal, and exports corresponding digital quantity.
In addition, preferred structure is, the A/D chip of analog-to-digital conversion module be sampled as lack sampling, lack sampling frequency is not more than 40MHz.
In addition, preferred structure is, FPGA standard identification module comprises: magnitude extraction unit, for storing the digital quantity that analog-to-digital conversion module exports, and is extracted the discrete wavelet transform coefficients amplitude of signal of communication by wavelet transform; Filter, for carrying out medium filtering process to the discrete wavelet transform coefficients amplitude extracted; Feature acquiring unit, for carrying out the Variance feature of the discrete wavelet transform coefficients amplitude obtaining communication signal after medium filtering process according to filter; Comparing unit, compares for the Variance feature that obtained by feature acquiring unit and pre-set threshold value, and obtains comparative result; Classification and Identification unit, for the comparative result that obtains according to comparing unit to signal of communication Classification and Identification.
In addition, preferred structure is, the sampling that analog-to-digital conversion module exports is stored to by data in the ROM of magnitude extraction unit; Further, the digital quantity in ROM is compared by the first comparison circuit and the first threshold values, and obtains the first comparative result, meanwhile, is compared, and obtain the second comparative result by the second comparison circuit and the second threshold values; Classification and Identification unit, according to the first comparative result and the second comparative result, carries out Classification and Identification to signal of communication.
In addition, preferred structure is, first comparison circuit carries out discrete wavelet transform coefficients magnitude extraction, medium filtering, Variance feature acquisition process successively to digital quantity, and the Variance feature of acquisition and the first threshold values is compared, the first comparative result input Classification and Identification unit of acquisition; Second comparison circuit carries out amplitude normalization, discrete wavelet transform coefficients magnitude extraction, medium filtering, Variance feature acquisition process successively to digital quantity, and the Variance feature of acquisition and the second threshold values are compared, the second comparative result input Classification and Identification unit of acquisition.
In addition, preferred structure is, discrete wavelet transformer is changed to discrete haar wavelet transform.
From technical scheme above, signal of communication standard recognition system of the present utility model, standard identification can be carried out to conventional signal of communication under without any the condition of priori, while, reliability many in identification kind is high, the real-time process to signal of communication can be realized, and then realize reliable communication.
Accompanying drawing explanation
By reference to the content below in conjunction with the description of the drawings and claims, and understand more comprehensively along with to of the present utility model, other object of the present utility model and result will be understood and easy to understand more.In the accompanying drawings:
Fig. 1 is the signal of communication standard recognition system structural representation according to the utility model embodiment;
Fig. 2 is the structural representation of the analog-to-digital conversion module according to the utility model embodiment; And
Fig. 3 is the FPGA standard identification module structural representation according to the utility model embodiment.
Reference numeral wherein comprises: signal receiving antenna 1, signal processing module 2, accept filter 21, LNA amplifier 22, frequency mixer 23, radio-frequency filter 231, intermediate-frequency filter 232, analog-to-digital conversion module 3, frequency overlapped-resistable filter 31, A/D chip 32, FPGA standard identification module 4, magnitude extraction unit 41, median filter 42, feature acquiring unit 43, Classification and Identification unit 44.
Label identical in all of the figs indicates similar or corresponding feature or function.
Embodiment
The problem such as large for the amount of calculation existed in above-mentioned signal of communication standard identifying, discrimination is low, the signal of communication standard recognition system that the utility model provides, by the change utilizing FIR filter to detect the amplitude of signal of communication, frequency and phase place in real time on FPGA hardware platform, and by setting suitable threshold value on Classification and Identification unit, signal of communication is classified, realize identifying signal of communication rapidly when different signal to noise ratio, recognition speed is fast, and reliability is high.
In order to be illustrated more clearly in the technical solution of the utility model, first simply introduce the signal of communication kind and concept thereof that relate in the utility model below.
1) MFSK (the many first frequency shift keyings of multiple-frequency-shiftkeying) signal, utilizes the frequency transmission M metasymbol of sinusoidal carrier; Have stable envelope, band efficiency is low and noiseproof feature is good, is applicable to the channel of power limited and frequency band abundance.
2) MQAM/QAM (MultipleQuadratureAmplitudeModulation, M-ary Quadrature Amplitude is modulated) signal, utilizes the multiple amplitude combinations of two-way quadrature carrier to carry signal code.
3) MPSK (multiplephaseshiftkeying, phase shift keying) signal, utilizes the transmission of phase M metasymbol of sinusoidal carrier.
4) MASK (multipleamplitudeshiftkeying, polynary amplitude shift keying), utilizes the amplitude transfer M metasymbol of sinusoidal carrier.
In addition, in the following description to signal of communication standard recognition system of the present utility model, signal of communication comprises common satellite communication signals.
In order to describe the signal of communication standard recognition system that the utility model provides in detail, below with reference to accompanying drawing, specific embodiment of the utility model is described in detail.
Particularly, Fig. 1 shows the structure according to signal of communication standard recognition system of the present utility model.
As shown in Figure 1, the signal of communication standard recognition system that the utility model relates to comprises the signal receiving antenna 1, signal processing module 2, analog-to-digital conversion module 3 and the FPGA standard identification module 4 that connect successively; Wherein, signal of communication enters standard recognition system by signal receiving antenna 1, and signal receiving antenna 1 is mainly used in receiving communication signal; The signal of communication that signal receiving antenna 1 receives by signal processing module 2 carries out filtering, amplification and frequency-conversion processing; Wherein, signal of communication changes intermediate-freuqncy signal into after signal processing module 2 processes; Analog-to-digital conversion module 3 carries out filtering and digitized processing to the intermediate-freuqncy signal after signal processing module 2 process, and exports the digital quantity corresponding with signal of communication after digitized processing; The digital quantity that analog-to-digital conversion module 3 exports by FPGA standard identification module 4 carries out wavelet transform process, and the Variance feature obtained after wavelet transform process and pre-set threshold value is compared, and then realizes the Classification and Identification to signal of communication.
Particularly, signal processing module 2 comprises the receiving filter 21 connected successively, LNA amplifier (LowNoiseAmplifier, low noise amplifier) 22 and frequency mixer 23, in the process that signal processing module 2 processes at the signal of communication received signal receiving antenna 1, first the signal of communication received by receiving filter 21 pairs of signal receiving antennas 1 carries out filtering process, then by LNA amplifier 22, low noise amplification is carried out to the signal of communication after receiving filter filtering process, then the signal of communication after low noise amplification carries out mixing (frequency conversion) by frequency mixer 23, the signal after filter and amplification is made to down-convert to intermediate-freuqncy signal.
Frequency mixer 23 mainly refers to the signal mixing that the signal of communication that received by reception antenna 1 and local oscillator produce, time in the signal of mixing containing intermediate-freuqncy signal, and the intermediate-freuqncy signal needed for being obtained by intermediate-frequency filter.In an embodiment of the present utility model, frequency mixer 23 comprises radio-frequency filter 231, second low noise amplifier (not shown), local oscillator (in figure shown in LO1) and intermediate-frequency filter 232, and intermediate-frequency filter 232 is connected with the second low noise amplifier.The process of the signal of communication after the amplification of LNA amplifier being carried out to mixing comprises: first the signal of communication after amplifying through LNA amplifier is carried out filtering through radio-frequency filter 231, with the high-frequency interferencing signal in the signal of communication of decaying after the process of LNA amplifier; Then will amplify through the second low noise amplifier through the filtered signal of communication of radio-frequency filter 231, and then be multiplied with local oscillation signal and carry out mixing, export the signal of communication down-converting to intermediate-freuqncy signal finally by intermediate-frequency filter 232.Wherein, LO1 represents the signal (local oscillation signal) that local oscillator produces, and local oscillation signal is multiplied with signal of communication (radiofrequency signal) generation mixed frequency signal.
It should be noted that, receiving after radiofrequency signal carries out above-mentioned filtering, amplification and frequency-conversion processing to signal receiving antenna 1, this signal of communication is still analog signal.Conveniently FPGA (Field-ProgrammableGateArray, field programmable gate array) to the further process of signal of communication, the operation such as transmission or storage, after signal of communication is treated to intermediate-freuqncy signal, in the analog-to-digital conversion module 3 be connected the input of this intermediate-freuqncy signal with signal processing module 2, further analog-to-digital conversion process is carried out to intermediate-freuqncy signal.
Particularly, analog-to-digital conversion mainly refers to that common A/D converts, and is that analog signal is converted to digital signal, so that the conversion of the process such as computer or single-chip microcomputer.Communication signal frequency is higher, and A/D change-over circuit operating frequency is higher, and the digital signal figure place that conversion obtains is more, and the recovery accuracy of signal of communication also can be more accurate.In the utility model, A/D conversion has come mainly through A/D chip 32.Wherein, Fig. 2 shows the structure of the analog-to-digital conversion module according to the utility model embodiment.
As shown in Figure 2, the analog-to-digital conversion module 3 in the signal of communication standard recognition system that provides of the utility model comprises frequency overlapped-resistable filter (anti-aliasfilter) 31 and A/D chip 32; Frequency overlapped-resistable filter 31 carries out low-pass filtering treatment for the intermediate-freuqncy signal exported signal processing module 2, and the intermediate-freuqncy signal then after A/D chip 32 pairs of low-pass filtering treatment carries out digitized processing, and exports corresponding digital quantity; Wherein, digital quantity is the digital quantity corresponding with signal of communication or intermediate-freuqncy signal, and the intermediate-freuqncy signal after low-pass filtering is converted to the digital signal corresponding with it by A/D chip.
In an embodiment of the present utility model, intermediate-freuqncy signal after low-pass filtering is converted in the process of digital signal by A/D chip 32, can be lack sampling to the sampling of intermediate-freuqncy signal, be not more than 40MHz according to nyquist sampling theorem setting lack sampling frequency.According to sampling thheorem, a bandwidth is the analog signal of fb, and sampling rate fs is greater than 2fb, just can avoid the loss of information.Lack sampling is when testing equipment bandwidth ability deficiency, a kind of means taked, and is equivalent to the bandwidth increasing testing equipment, thus reaches the ability of higher frequency signal of can sampling.According to sampling theory, when sampling to sophisticated signal, if sample clock frequency is less than the twice of peak frequency in signal, then there will be a kind of phenomenon being called aliasing, when sample clock frequency is enough low, then can cause a kind of aliasing being called lack sampling.
In order to solve the problem of frequency alias, before discretization collection is carried out to intermediate-freuqncy signal of the present utility model, first by the frequency content higher than 1/2 sample frequency in frequency overlapped-resistable filter 31 filtering intermediate-freuqncy signal, avoid false frequency to mix in signal of communication, guarantee integrality and the authenticity of signal.
Then, by A/D chip 32, analog-to-digital conversion and digitized processing are carried out to the intermediate-freuqncy signal after frequency overlapped-resistable filter 31 processes, and the digital quantity obtained after exporting sampling processing, intermediate-freuqncy signal after analog-to-digital conversion module 3 processes is converted into the digital quantity that analog-to-digital conversion module 3 exports, this digital quantity is further stored in the ROM (Read-OnlyMemory of FPGA standard identification module 4, read-only memory) in, and carry out subsequent treatment.
Particularly, Fig. 3 shows the FPGA standard identification module structure according to the utility model embodiment.
As shown in Figure 3, FPGA standard identification module 4 comprises magnitude extraction unit 41, filter 42, feature acquiring unit 43, comparing unit and the Classification and Identification unit 44 of connecting successively; The digital quantity exported through analog-to-digital conversion module 3 is stored in the ROM of magnitude extraction unit 41, then by wavelet transform (Discretewavelettransform), the digital quantity stored is carried out to the extraction of Variance feature.Wherein, magnitude extraction unit 41, for storing the digital quantity that analog-to-digital conversion module exports, and extracts the discrete wavelet transform coefficients amplitude of signal of communication by wavelet transform; Filter 42, for carrying out filtering process to the discrete wavelet transform coefficients amplitude extracted; Feature acquiring unit 43, for the Variance feature according to the discrete wavelet transform coefficients amplitude obtaining communication signal after medium filtering process; Comparing unit, for the Variance feature of acquisition and pre-set threshold value being compared, and obtains comparative result; Classification and Identification unit 43, for the comparative result that obtains according to comparing unit to signal of communication Classification and Identification.
It should be noted that, in the process that Variance feature obtains, first discrete haar wavelet transform is carried out to the digital quantity that magnitude extraction unit stores, extract the discrete wavelet transform coefficients amplitude of signal of communication; Then, medium filtering process is carried out to the discrete wavelet transform coefficients amplitude extracted; Finally, the Variance feature corresponding with signal of communication is obtained according to the discrete wavelet transform coefficients amplitude after medium filtering process.
At present, FPGA can construct multiple performance element, and these performance elements can run with the demand of satisfied application simultaneously, and FPGA has certain advantage in the task of process computation-intensive, but relative DSP, and what have more complicated relates to flow process.In system for real-time signal processing, the data volume of the Signal Pretreatment algorithm process of low layer is large, high to the requirement of processing speed, but when high in the clouds structure is relatively simple, is suitable for carrying out hardware implementing by FPGA, can takes into account speed and flexibility simultaneously.The feature of high-rise Processing Algorithm is that handled data volume lower level algorithm is few, but the control structure of algorithm is complicated, be applicable to the dsp chip that arithmetic speed is high, addressing system is flexible, communication mechanism is powerful realize, in the utility model, carry out hardware implementing mainly through FPGA, speed and the flexibility thereof of Signal analysis can be ensured.
Particularly, analog intermediate frequency signal after filtering with analog-to-digital conversion after, be stored in the form of digital quantity in the ROM of magnitude extraction unit 41, the digital quantity be stored in ROM carries out two kinds of different process simultaneously; Wherein, digital quantity is compared by the first comparison circuit and the first threshold values, obtains the first comparative result; Meanwhile, compared by the second comparison circuit and the second threshold values, obtain the second comparative result; First comparative result and the second comparative result input Classification and Identification unit 44 simultaneously, and Classification and Identification unit 44 carries out Classification and Identification according to twice comparative result to signal of communication.Wherein, in the first comparison circuit, first, digital quantity is carried out discrete wavelet transform coefficients magnitude extraction, then carry out filtering through median filter 42, obtain Variance feature, and the first threshold values of the Variance feature of acquisition and setting is compared; In the second comparison circuit, first, digital quantity is carried out amplitude normalized, then carry out filtering through median filter 42, obtain Variance feature, and the second threshold values of this Variance feature and setting is compared; The comparative result of two-way Variance feature all inputs Classification and Identification unit 44, finally realizes the Classification and Identification to signal of communication by Classification and Identification unit 44.
In other words, the first comparison circuit carries out discrete wavelet transform coefficients magnitude extraction, medium filtering, Variance feature acquisition successively to digital quantity, and the Variance feature of acquisition and the first threshold values is compared, the first comparative result input Classification and Identification unit 44 of acquisition; Second comparison circuit carries out amplitude normalized, discrete wavelet transform coefficients magnitude extraction, medium filtering, Variance feature acquisition successively to digital quantity, and the Variance feature of acquisition and the second threshold values are compared, the the second comparative result input Classification and Identification unit 44 obtained, final Classification and Identification unit 44 is according to the standard classification of the first comparative result and the second comparative result determination signal of communication.
It should be noted that, in a preferred implementation of signal of communication standard recognition system of the present utility model, wavelet transformation can be discrete haar wavelet transform, or other types can obtain the wavelet transform of wavelet transformation Variance feature.Wherein, pre-set threshold value can be obtained by matlab emulation.
Wherein, when magnitude extraction unit 44 pairs of digital quantities carry out wavelet transform, there are two kinds of situations.One, when amplitude normalized not being carried out to digital quantity, if need the signal of communication of standard identification to be MASK, the signal of MQAM or MFSK, when utilizing discrete haar wavelet transform to carry out Variance feature extraction to this signal of communication, signal after median filter 42 filtering process is the value fluctuated up and down, the Variance feature of this signal is larger, if need the signal of communication of standard identification to be the signal of MPSK, the signal approximation after median filter 42 filtering process then extracted is steady state value, the Variance feature of this signal is less, the signal that signal of communication is MPSK can be distinguished in this way.
They are two years old, after amplitude normalized is carried out to digital quantity, when utilizing discrete haar wavelet transform to carry out Variance feature extraction to signal of communication, if need the signal of communication of standard identification to be the signal of MASK, MQAM, when then extracting the Variance feature of signal, the signal after median filter 42 filtering process is still the value fluctuated up and down, if signal is the signal of MFSK, the signal approximation after median filter 42 filtering process then extracted is steady state value, so just can distinguish MFSK signal.If modulation signal is MASK or MQAM signal, then need to carry out discrete haar wavelet transform again to this signal, when extracting Variance feature, the Variance feature of MQAM signal, apparently higher than the Variance feature of MASK signal, so just can distinguish 4 kinds of dissimilar modulation signals.Finally, FPGA hardware platform utilize discrete wavelet transform coefficients amplitude Variance feature carry out Classification and Identification as characteristic value.After identifying the classification of signal of communication, demodulation can be carried out according to corresponding demodulation method to it, and obtain original communication signal, and then realize reliable communication.
In other words, in the process processed analog-to-digital conversion module output digital quantity, first digital quantity is stored in the ROM of magnitude extraction unit 41, then carries out two-way process to this digital quantity; Wherein, a circuit-switched data obtains through discrete wavelet transform coefficients magnitude extraction, medium filtering, Variance feature (first variance feature), and the first threshold values that is last and setting compares; Another circuit-switched data compares through amplitude normalization, discrete wavelet transform coefficients magnitude extraction, medium filtering, Variance feature (second variance feature) acquisition, the second threshold values that is last and setting; The comparative result of two-way digital quantity all inputs Classification and Identification unit 44 and carries out signal of communication classification.
Wherein, the first situation: first variance feature compares with the first threshold values of setting, and the two difference is greater than zero, and second variance feature compares with the second threshold values of setting, the two difference is less than zero; Now, can confirm that signal of communication is QAM or ASK signal.
The second situation: first variance feature compares with the first threshold values of setting, and the two difference is less than zero, and second variance feature compares with the second threshold values of setting, the two difference is less than zero; Now, can confirm that signal of communication is psk signal.
The third situation: first variance feature compares with the first threshold values of setting, and the two difference is greater than zero, and second variance feature compares with the second threshold values of setting, the two difference is greater than zero; Now, can confirm that signal of communication is fsk signal.
The signal of communication standard recognition system that the utility model provides, carries out Variance feature extraction by discrete haar wavelet transform to conventional satellite communication signals MASK, MPSK, QAM, MFSK signal etc.; Then, FPGA utilize FIR filter realize discrete haar wavelet transform, this conversion discrimination when signal to noise ratio is lower is high, and can identify conventional satellite communication signals under the condition without the need to any priori, there is volume little, the advantages such as identification kind is many, and reliability is high, process in real time.
Can be found out by above-mentioned execution mode, the signal of communication standard recognition system that the utility model provides, by reception antenna obtaining communication signal, then by the down-converted of signal processing module, the signal of communication received is made to be converted into analog intermediate frequency signal, and by analog-to-digital conversion module, analog-to-digital conversion is carried out to this analog intermediate frequency signal, obtain corresponding digital signal, then this digital signal input FPGA standard identification module is carried out discriminator; Under different signal to noise ratio, the change of the amplitude of signal of communication, frequency and phase place can be detected in real time, and eventually through setting the suitable discriminator of threshold values realization to signal of communication on Classification and Identification unit, the Signal analysis to satellite communication signals can be realized under without any the condition of priori, volume is little, identification kind is many, and reliability is high, and can process in real time.
The signal of communication standard recognition system according to the utility model proposes is described in an illustrative manner above with reference to accompanying drawing.But, it will be appreciated by those skilled in the art that the signal of communication standard recognition system that above-mentioned the utility model is proposed, various improvement can also be made on the basis not departing from the utility model content.Therefore, protection range of the present utility model should be determined by the content of appending claims.
Claims (9)
1. a signal of communication standard recognition system, is characterized in that, comprising:
Signal receiving antenna, for receiving communication signal;
Signal processing module, is connected with described signal receiving antenna, carries out filtering, amplification and frequency-conversion processing for the signal of communication received described signal receiving antenna; Wherein, described signal of communication becomes intermediate-freuqncy signal after signal processing module process;
Analog-to-digital conversion module, is connected with described signal processing module, to carry out filtering and digitized processing to the intermediate-freuqncy signal after described signal processing module process, and exports corresponding digital quantity;
FPGA standard identification module, be connected with described analog-to-digital conversion module, for described digital quantity is carried out wavelet transform process, and the Variance feature obtained after wavelet transform process and pre-set threshold value are compared, according to comparative result to described signal of communication Classification and Identification.
2. signal of communication standard recognition system as claimed in claim 1, it is characterized in that, described signal processing module comprises:
Receiving filter, carries out filtering process for the signal of communication received described signal receiving antenna;
LNA amplifier, is connected with described receiving filter, for carrying out low noise amplification process to through the filtered signal of communication of described receiving filter;
Frequency mixer, is connected with described LNA amplifier, for carrying out frequency-conversion processing to the signal of communication after described LNA amplifier amplification.
3. signal of communication standard recognition system as claimed in claim 2, it is characterized in that, described frequency mixer comprises:
Radio-frequency filter, for the high-frequency interferencing signal in the signal of communication of decaying after the process of described LNA amplifier;
Second low noise amplifier, is connected with described radio-frequency filter, for carrying out low noise amplification process to by the signal of communication after described radio-frequency filter process;
Intermediate-frequency filter, is connected with described second low noise amplifier, to obtain intermediate-freuqncy signal from the signal of communication after described second low noise amplifier process.
4. signal of communication standard recognition system as claimed in claim 1, it is characterized in that, described analog-to-digital conversion module comprises:
Frequency overlapped-resistable filter, carries out low-pass filtering treatment for the described intermediate-freuqncy signal exported described signal processing module;
A/D chip, is connected with described frequency overlapped-resistable filter, so that the described intermediate-freuqncy signal after described frequency overlapped-resistable filter low-pass filtering treatment is converted to digital signal, and exports corresponding digital quantity.
5. signal of communication standard recognition system as claimed in claim 4, is characterized in that,
The A/D chip of described analog-to-digital conversion module be sampled as lack sampling, described lack sampling frequency is not more than 40MHz.
6. signal of communication standard recognition system as claimed in claim 1, it is characterized in that, described FPGA standard identification module comprises:
Magnitude extraction unit, for storing the digital quantity that described analog-to-digital conversion module exports, and extracts the discrete wavelet transform coefficients amplitude of described signal of communication by wavelet transform;
Filter, carries out medium filtering process for the discrete wavelet transform coefficients amplitude extracted described magnitude extraction unit;
Feature acquiring unit, obtains the Variance feature of described signal of communication for the discrete wavelet transform coefficients amplitude after carrying out medium filtering process according to described filter;
Comparing unit, for the Variance feature of described feature acquiring unit acquisition and pre-set threshold value being compared, and obtains comparative result;
Classification and Identification unit, for the comparative result that obtains according to described comparing unit to described signal of communication Classification and Identification.
7. signal of communication standard recognition system as claimed in claim 6, is characterized in that,
The digital quantity that described analog-to-digital conversion module exports is stored in the ROM of described magnitude extraction unit; Further,
Digital quantity in described ROM is compared by the first comparison circuit and the first threshold values, and obtains the first comparative result, meanwhile, is compared, and obtain the second comparative result by the second comparison circuit and the second threshold values; Described Classification and Identification unit, according to described first comparative result and the second comparative result, carries out Classification and Identification to described signal of communication.
8. signal of communication standard recognition system as claimed in claim 7, is characterized in that,
Described first comparison circuit carries out discrete wavelet transform coefficients magnitude extraction, medium filtering, Variance feature acquisition process successively to described digital quantity, and the Variance feature of acquisition and described first threshold values are compared, the first comparative result of acquisition inputs described Classification and Identification unit;
Described second comparison circuit carries out amplitude normalization, discrete wavelet transform coefficients magnitude extraction, medium filtering, Variance feature acquisition process successively to described digital quantity, and the Variance feature of acquisition and described second threshold values are compared, the second comparative result of acquisition inputs described Classification and Identification unit.
9. signal of communication standard recognition system as claimed in claim 8, is characterized in that,
Described discrete wavelet transformer is changed to discrete haar wavelet transform.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104796366A (en) * | 2015-04-10 | 2015-07-22 | 长春理工大学 | Communication signal system identification system and method |
| CN109429036A (en) * | 2017-09-01 | 2019-03-05 | 齐心 | A kind of counter system of video monitoring transmission |
| CN111343114A (en) * | 2020-02-18 | 2020-06-26 | 中国电子科技集团公司第二十研究所 | Modulation type identification method of modulation signal |
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2015
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104796366A (en) * | 2015-04-10 | 2015-07-22 | 长春理工大学 | Communication signal system identification system and method |
| CN104796366B (en) * | 2015-04-10 | 2018-09-11 | 长春理工大学 | Signal of communication standard identifying system and method |
| CN109429036A (en) * | 2017-09-01 | 2019-03-05 | 齐心 | A kind of counter system of video monitoring transmission |
| CN111343114A (en) * | 2020-02-18 | 2020-06-26 | 中国电子科技集团公司第二十研究所 | Modulation type identification method of modulation signal |
| CN111343114B (en) * | 2020-02-18 | 2022-05-17 | 中国电子科技集团公司第二十研究所 | Modulation type identification method of modulation signal |
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