CN112240956A - Weak signal capturing system and method for electronic communication network - Google Patents

Weak signal capturing system and method for electronic communication network Download PDF

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CN112240956A
CN112240956A CN202010939762.3A CN202010939762A CN112240956A CN 112240956 A CN112240956 A CN 112240956A CN 202010939762 A CN202010939762 A CN 202010939762A CN 112240956 A CN112240956 A CN 112240956A
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CN112240956B (en
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徐桂敏
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Hubei University of Education
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    • G01R29/02—Measuring characteristics of individual pulses, e.g. deviation from pulse flatness, rise time or duration
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • H—ELECTRICITY
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    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
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Abstract

The invention provides a system and a method for capturing weak signals of an electronic communication network, wherein the system comprises: the system comprises a signal collector, a controller, a processor, an integrator and a low-pass filter; the weak signal is captured by the signal collector and processed into a frame signal by the controller, and the frame signal is transmitted to the processor; the processor converts the frame signal to obtain an instruction decoding; the instruction decoding sequentially passes through an integrator and a low-pass filter to obtain a pulse data signal of the weak signal after sampling, frequency conversion and decoding; a method for processing a pulse data signal, comprising: frequency domain rearrangement, lower smoothing window function filtering, frequency domain down-sampling, weak signal positioning and estimation of an electronic communication network; the beneficial effects provided by the invention are as follows: the operation efficiency of the electronic communication network weak signal capturing system based on the sparse Fourier transform can be improved by more than 2 times, and the requirements of the electronic communication network on signal capturing are well met.

Description

Weak signal capturing system and method for electronic communication network
Technical Field
The invention relates to the field of electronic signal acquisition, in particular to a system and a method for capturing weak signals of an electronic communication network.
Background
With the development of communication networks, data information inside the system is more and more complex, network architectures are increasingly huge, and it becomes more difficult to receive and capture pulse data signals of weak signals of micro-intermediate frequency electronic communication networks. Capturing the weak signal of the micro-intermediate frequency electronic communication network is the first step of the electronic communication network, can well confirm communication network information, and realize the estimation of the code phase and carrier frequency of the received signal, thereby better determining the initial value. In recent years, a weak signal acquisition method of a micro-intermediate frequency electronic communication network mainly includes a time domain-based serial acquisition method, a frequency domain-based parallel frequency search acquisition method and a frequency domain-based parallel code phase search acquisition method, which have certain advantages, but have various different problems. Although the time domain serial capturing method has simple hardware equipment, the operation process is too long, a large amount of calculation is required, and errors are easy to occur; the parallel frequency search capture method based on the frequency domain can only realize parallel search in the direction of carrier frequency; the parallel code phase searching and capturing method based on the frequency domain is the most commonly used method at present, the method introduces a fast Fourier transform technology, and the capturing speed of weak signals of a communication micro-intermediate frequency electronic communication network is accelerated through parallel searching, but the requirement of the number of sampling points based on an FFT fast capturing algorithm is an integral power of 2.
Disclosure of Invention
In view of the above problems, the present invention provides a system and a method for capturing an intermediate frequency electronic weak signal in an electronic communication network by using sparse fourier transform in a design concept of a frequency domain-based parallel code phase search capture method. After the sparse characteristic of the signal in the frequency domain is analyzed, the sub-linear processing is completed by utilizing three steps of windowing, aliasing and reconstruction respectively. The sampling factors are selected and subjected to reinforced design, so that the complexity of the capturing process can be reduced, and the capturing efficiency can be enhanced.
A weak signal capturing system of an electronic communication network specifically comprises: the system comprises a signal collector, a controller, a processor, an integrator and a low-pass filter;
the signal collector is connected with the controller through a CAN bus; the controller is electrically connected with the processor; the processor is electrically connected with the integrator; the integrator is electrically connected with the low-pass filter;
the signal collector is a dual-channel carrier collector and is used for collecting weak signals of the electronic communication network;
the controller is specifically a CAN controller and is used for receiving the weak signals of the electronic communication network acquired by the signal acquisition device and processing the weak signals of the electronic communication network into frame signals;
the processor is used for receiving the frame signal and converting the frame signal into an instruction decoding;
the integrator is used for performing low-pass filtering on pulse data signals of the intermediate-frequency electronic communication network weak signals;
the low-pass filter is used for eliminating errors generated by offset current in the operation and amplification process of pulse data signals of weak signals of the intermediate frequency electronic communication network by the system, so that direct current resistances generated by the in-phase input end and the reverse input end of the operation and amplification are the same;
pulse data signals of intermediate-frequency electronic weak signals in the electronic communication network are captured by the signal collector, processed into frame signals by the controller and transmitted to the processor through the CAN bus; the processor converts the frame signal to obtain an instruction decoding; and the instruction decoding sequentially passes through the integrator and the low-pass filter to obtain a pulse data signal of the intermediate-frequency electronic communication network weak signal after sampling, frequency conversion and decoding.
A weak signal capturing method of an electronic communication network is used for processing a pulse data signal of a weak signal of the intermediate frequency electronic communication network, and specifically comprises the following steps:
s101: frequency domain rearrangement; the pulse data signals of the intermediate frequency electronic communication network weak signals are N-dimensional vectors x (N), random parameters sigma and tau are obtained from the pulse data signals of the intermediate frequency electronic communication network weak signals for time domain transformation, and the time domain transformation result is shown as a formula (1):
q(n)＝x(σn+τ) (1)
in the formula (1), N represents the variation in the time domain, q (N) is the signal time domain transformation result, wherein sigma is an integer coprime to N, and tau belongs to [0, N-1 ];
root factor W of Fourier transform is introduced in formula (1)N＝e-j2π/NFrom the displacement properties and scaling properties of the fourier transform, equation (2) is derived:
Figure BDA0002673221590000031
in the formula (2), k represents a point with the coordinate k in the original signal spectrum; q (sigma k) represents a signal frequency domain rearrangement result; x (k) represents the Fourier transform of x (n);
s102: filtering by a lower smoothing window function; inputting q (n) into a Doherty-Chebyshev window function filter for filtering, and obtaining the result shown in formula (3):
y(n)＝q(n)g(n) (3)
in the formula (3), y (n) represents the result of q (n) passing through a Doherty-Chebyshev window function filter; g (n) represents a dolf-chebyshev window function;
s103: frequency domain down-sampling; aliasing is carried out on y (n) by adopting a preset factor p to obtain a frequency domain down-sampling result Z (k), which is shown in a formula (4):
Z(k)＝Y(kn/B) (4)
in formula (4), the signal y (N) has a length of N; the parameter B is an integral multiple of N; y (k) is the result of y (n) discrete Fourier transform; z (k) is the result of down-sampling the signal frequency domain at equal intervals of N/B;
s104: carrying out Hash mapping; and performing hash mapping on the result B, wherein the formula (5) is as follows:
hσ′(k)＝round(σ′kB/n) (5)
in formula (5), round (·) represents a rounding function; σ' represents a preset offset; h isσ′(k) Representing a hash function;
s105: weak signal positioning of an electronic communication network; recording the maximum spectrum peak value in all Z (k), taking the maximum spectrum peak value as a set J, and obtaining a primitive image set H of the J through Hash reverse mapping, wherein the set H satisfies the formula (6):
H＝{k∈[n]|hσ′(k)∈J} (6)
s106: estimating; and estimating the intermediate frequency electronic communication network weak signal obtained by positioning, and obtaining the spectrum of the lower smoothing window function in sigma' to finish the capture of the intermediate frequency electronic weak signal in the electronic communication network.
The beneficial effects provided by the invention are as follows: the operation efficiency of the electronic communication network weak signal capturing system based on the sparse Fourier transform can be improved by more than 2 times, and the requirements of the electronic communication network on signal capturing are well met.
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FIG. 1 is a schematic diagram of a weak signal acquisition system of an electronic communication network according to the present invention;
FIG. 2 is a diagram of a signal collector of the present invention;
FIG. 3 is a block diagram of the controller of the present invention;
FIG. 4 is a block diagram of the low pass filter of the present invention;
FIG. 5 is a flow chart of a weak signal acquisition method of an electronic communication network according to the present invention;
fig. 6 is a graph of the successful acquisition of weak signals in the electronic communication network of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be further described with reference to the accompanying drawings.
Referring to fig. 1, an embodiment of the present invention provides a system for capturing a weak signal in an electronic communication network, which includes the following components:
the system comprises a signal collector, a controller, a processor, an integrator and a low-pass filter;
the signal collector is connected with the controller through a CAN bus; the controller is electrically connected with the processor; the processor is electrically connected with the integrator; the integrator is electrically connected with the low-pass filter;
the signal collector is a dual-channel carrier collector and is used for collecting weak signals of the electronic communication network;
the controller is specifically a CAN controller and is used for receiving the weak signals of the electronic communication network acquired by the signal acquisition device and processing the weak signals of the electronic communication network into frame signals;
the processor is used for receiving the frame signal and converting the frame signal into an instruction decoding;
the integrator is used for performing low-pass filtering on pulse data signals of the intermediate-frequency electronic communication network weak signals;
the low-pass filter is used for eliminating errors generated by offset current in the operation and amplification process of pulse data signals of weak signals of the intermediate frequency electronic communication network by the system, so that direct current resistances generated by the in-phase input end and the reverse input end of the operation and amplification are the same;
pulse data signals of intermediate-frequency electronic weak signals in the electronic communication network are captured by the signal collector, processed into frame signals by the controller and transmitted to the processor through the CAN bus; the processor converts the frame signal to obtain an instruction decoding; and the instruction decoding sequentially passes through the integrator and the low-pass filter to obtain a pulse data signal of the intermediate-frequency electronic communication network weak signal after sampling, frequency conversion and decoding.
Referring to fig. 2, the signal collector structurally includes a cloud service platform, a first carrier wave master control gateway (carrier wave master control gateway 1 in fig. 2), a second carrier wave master control gateway (carrier wave master control gateway 2 in fig. 2), an ARM master control unit, a first front end device (front end device 1 in fig. 2), a second front end device (front end device 2 in fig. 2), a first carrier wave unit (carrier wave unit 1 in fig. 2), and a corresponding RISC carrier wave processing channel, a second carrier wave unit (carrier wave unit 2 in fig. 2), and a corresponding RISC carrier wave processing channel;
the cloud service platform is connected with the first carrier wave master control gateway and the second carrier wave master control gateway in a wireless mode; the first carrier gateway is connected with the second carrier unit and the corresponding RISC carrier processing channel through a live wire and a zero line; the second carrier gateway is connected with the first carrier unit and the corresponding RISC carrier processing channel through a live wire and a zero line;
the ARM main control unit is electrically connected with the first front-end equipment, the second front-end equipment, the first carrier unit and the corresponding RISC carrier processing channel, and the second carrier unit and the corresponding RISC carrier processing channel.
Referring to fig. 3, the controller has a structure including: CPU, CPU interface memory management unit, RAM, control/status register interrupt logic unit, control logic unit, sending buffer, CAN core, temporary receiving buffer, receiving filter and CAN server;
the CPU is electrically connected with the CPU interface memory management unit; the CPU memory management unit is electrically connected with the control/state register interrupt logic unit, the RAM and the CAN core; the control logic unit is electrically connected with the CPU interface memory management unit, the control/state register interrupt logic unit and the sending buffer; the sending buffer is in nuclear power connection with the CAN; the CAN core is electrically connected with the temporary receiving buffer; the temporary receiving buffer is electrically connected with the receiving filter; the CAN core is electrically connected with the CAN server.
The processor comprises a storage unit, an input unit and an output unit; the input unit is electrically connected with the storage unit; the storage unit is electrically connected with the output unit; the input unit receives the frame signal and transmits the frame signal to the storage unit for storage; the storage unit converts the frame signal into an instruction decoding, transmits the instruction decoding to the output unit, and outputs the instruction decoding by the output unit.
Referring to FIG. 4, the low pass filter includes resistors R1-R5, capacitors C1-C2, and an operational amplifier; one end of the resistor R5 is connected with the output of the processor; the other end of the resistor R5 is electrically connected with one end of the resistor R4, one end of the capacitor C2 and one end of the capacitor C1 respectively; the other end of the capacitor C1 is grounded; the other end of the resistor R4 is electrically connected with the output end of the operational amplifier and one end of the resistor R3 respectively; the other end of the capacitor C2 is electrically connected with the non-inverting input end of the operational amplifier and the first end of the resistor R1 respectively; the other end of the resistor R1 is grounded; the other end of the resistor R3 is electrically connected with the inverting input end of the operational amplifier and one end of the resistor R2 respectively; the other end of the resistor R2 is grounded. The gain relationship of the low pass filter is shown in table 1.
TABLE 1 relationship between Low pass Filter order and gain
Figure BDA0002673221590000071
Referring to fig. 5, a weak signal capturing method for an electronic communication network is used for processing a pulse data signal obtained by the capturing system, and in the embodiment of the present application, a MATLAB is used for processing based on a sparse fourier transform method, which specifically includes the following steps:
s101: frequency domain rearrangement; the pulse data signals of the intermediate frequency electronic communication network weak signals are N-dimensional vectors x (N), random parameters sigma and tau are obtained from the pulse data signals of the intermediate frequency electronic communication network weak signals for time domain transformation, and the time domain transformation result is shown as a formula (1):
q(n)＝x(σn+τ) (1)
in the formula (1), N represents the variation in the time domain, q (N) is the signal time domain transformation result, wherein sigma is an integer coprime to N, and tau belongs to [0, N-1 ];
root factor W of Fourier transform is introduced in formula (1)N＝e-j2π/NFrom the displacement properties and scaling properties of the fourier transform, equation (2) is derived:
Figure BDA0002673221590000072
in the formula (2), k represents a point with the coordinate k in the original signal spectrum; q (sigma k) represents a signal frequency domain rearrangement result; x (k) represents the Fourier transform of x (n);
s102: filtering by a lower smoothing window function; inputting q (n) into a Doherty-Chebyshev window function filter for filtering, and obtaining the result shown in formula (3):
y(n)＝q(n)g(n) (3)
in the formula (3), y (n) represents the result of q (n) passing through a Doherty-Chebyshev window function filter; g (n) represents a dolf-chebyshev window function;
s103: frequency domain down-sampling; aliasing is carried out on y (n) by adopting a preset factor p to obtain a frequency domain down-sampling result Z (k), which is shown in a formula (4):
Z(k)＝Y(kn/B) (4)
in formula (4), the signal y (N) has a length of N; the parameter B is an integral multiple of N; y (k) is the result of y (n) discrete Fourier transform; z (k) is the result of down-sampling the signal frequency domain at equal intervals of N/B;
s104: carrying out Hash mapping; and performing hash mapping on the result B, wherein the formula (5) is as follows:
hσ′(k)＝round(σ′kB/n) (5)
in formula (5), round (·) represents a rounding function; σ' represents a preset offset; h isσ′(k) Representing a hash function;
s105: weak signal positioning of an electronic communication network; recording the maximum spectrum peak value in all Z (k), taking the maximum spectrum peak value as a set J, and obtaining a primitive image set H of the J through Hash reverse mapping, wherein the set H satisfies the formula (6):
H＝{k∈[n]|hσ′(k)∈J} (6)
s106: estimating; and estimating the intermediate frequency electronic communication network weak signal obtained by positioning, and obtaining the spectrum of the lower smoothing window function in sigma' to finish the capture of the intermediate frequency electronic weak signal in the electronic communication network.
The working effect of the weak signal capturing system in the electronic communication network based on the sparse Fourier transform is compared with that of a traditional weak signal capturing system in the electronic communication network based on the fast Fourier transform, and an experimental result is analyzed.
Setting the frequency in the communication network data to be 10.125MHz, setting the sampling frequency to be 29.412MHz, completing the verification process of the system on a software receiver, setting the search range of the frequency spectrum to be between-8 and 8, setting the step length of the frequency spectrum search to be 800Hz, setting the length of the electronic communication network to be T, setting the values of T to be 1ms, 2ms and 5ms respectively, setting the values of the sampling factors P to be 1, 2 and 4, selecting different capture systems to capture the sampling factors with different values respectively, and calculating the capture result.
When T ═ 1ms, the capture results obtained are shown in table 2 below:
table 2 pulse data signal capturing result of weak signal of electronic network communication intermediate frequency electronic communication network (T ═ 1ms)
Figure BDA0002673221590000091
When T is 2ms, the obtained capture results of the conventional system and the system of the present application are shown in table 3 below:
table 3 pulse data signal capturing result of weak signal of electronic network communication intermediate frequency electronic communication network (T2 ms)
Figure BDA0002673221590000092
When T is 5ms, the obtained capture results of the conventional system and the system of the present application are shown in table 4 below:
table 4 pulse data signal capturing result of weak signal of electronic network communication intermediate frequency electronic communication network (T ═ 5ms)
Figure BDA0002673221590000093
As can be seen from the analysis of tables 2 to 4, when T is 1ms, the operation efficiency of the system of the present application is about 1.64 times that of the conventional system; when T is 2ms, the operation efficiency of the system is about 2.41 times that of the traditional system; when T is 5ms, the operation efficiency of the system is about 2.52 times that of the traditional system, and the operation efficiency improvement effect of the electronic communication network weak signal capturing system based on sparse Fourier transform is more obvious along with the increase of the length N of the captured data.
Referring to fig. 6, fig. 6 is a schematic diagram illustrating a successful weak signal acquisition result in the electronic communication network according to the present invention.
In a word, the conventional weak signal acquisition system of the electronic communication network has high requirement on the accuracy of the acquisition factor p, so that the acquisition error is large, the acquisition speed is low, and the positioning time of a communication network receiver is seriously influenced. On the basis of a capturing system of weak signals of an electronic communication network of fast Fourier transform, sparse Fourier transform without sub-linear operation is adopted, a new capturing system is set, a signal collector, a controller, a processor, an integrator and a low-pass filter are respectively introduced to form a hardware structure of the system, and the capturing process is realized through operation steps of frequency domain rearrangement, window function filtering, Hash mapping, frequency domain down sampling, positioning, estimation and the like.
Experimental results show that compared with the traditional capturing system, the operation efficiency of the capturing system of the weak signals of the electronic communication network based on the sparse Fourier transform can be improved by more than 2 times, and the requirements of the electronic communication network on signal capturing can be well met.
The key points of the technology of the invention are as follows:
1. the capture system designed by the invention is an ultra-large scale integrated circuit, the working state of the processor is controlled by the operation core and the control core, and the processor mainly comprises three core units, namely a storage unit, an input unit and an output unit. Outputting each instruction from the memory, transferring to the instruction register to generate instruction decoding, and finishing different micro-operations by the instruction decoding, thereby further controlling each operation of the whole system, wherein each instruction has a plurality of bytes, and analyzing fields of different addresses according to the operation code field to process different signals.
2. The weak signal capturing of the electronic communication network is a three-dimensional searching process, information needing to be searched comprises a communication code, a code phase and a carrier frequency, when the number phase of the communication code is the same as that of a local address, the carrier frequency obtained locally is the same as that of the weak signal of the communication network, and a strong correlation value can be generated between the carrier frequency and the weak signal of the communication network.
3. In the two-dimensional searching process, a peak value appears in the signal, the peak value has a remarkable characteristic, and compared with the integral values of other searching units, the integral value of the weak signal is obviously higher, which can also prove that the weak signal is successfully captured, and all captured network weak signal output values have sparsity.
4. In the code phase, software realizes the cyclic correlation of a frequency domain, thereby realizing the capture function and improving the capture efficiency. The sparse Fourier transform technology fully utilizes the sparse characteristic of signals in a frequency domain, simplifies a fast Fourier transform algorithm, improves the operation process, and obtains the same frequency spectrum analysis effect graph but with low operation complexity by the sparse Fourier transform algorithm. The sparse Fourier transform algorithm completes the capture process by utilizing the steps of frequency domain rearrangement, window function filtering, Hash mapping, frequency domain down sampling, positioning, estimation and the like.
The beneficial effects provided by the invention are as follows: the operation efficiency of the electronic communication network weak signal capturing system based on the sparse Fourier transform can be improved by more than 2 times, and the requirements of the electronic communication network on signal capturing are well met.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (6)

1. A weak signal acquisition system of an electronic communication network is characterized in that: the method specifically comprises the following steps: the system comprises a signal collector, a controller, a processor, an integrator and a low-pass filter;
the signal collector is connected with the controller through a CAN bus; the controller is electrically connected with the processor; the processor is electrically connected with the integrator; the integrator is electrically connected with the low-pass filter;
the signal collector is a dual-channel carrier collector and is used for collecting weak signals of the electronic communication network;
the controller is specifically a CAN controller and is used for receiving the weak signals of the electronic communication network acquired by the signal acquisition device and processing the weak signals of the electronic communication network into frame signals;
the processor is used for receiving the frame signal and converting the frame signal into an instruction decoding;
the integrator is used for performing low-pass filtering on pulse data signals of the intermediate-frequency electronic communication network weak signals;
the low-pass filter is used for eliminating errors generated by offset current in the operation and amplification process of pulse data signals of weak signals of the intermediate frequency electronic communication network by the system, so that direct current resistances generated by the in-phase input end and the reverse input end of the operation and amplification are the same;
pulse data signals of intermediate-frequency electronic weak signals in the electronic communication network are captured by the signal collector, processed into frame signals by the controller and transmitted to the processor through the CAN bus; the processor converts the frame signal to obtain an instruction decoding; and the instruction decoding sequentially passes through the integrator and the low-pass filter to obtain a pulse data signal of the intermediate-frequency electronic communication network weak signal after sampling, frequency conversion and decoding.
2. A weak signal acquisition system of an electronic communication network as claimed in claim 1, characterized in that:
the signal collector structurally comprises a cloud service platform, a first carrier master control gateway, a second carrier master control gateway, an ARM master control unit, first front-end equipment, second front-end equipment, a first carrier unit, a corresponding RISC carrier processing channel, a second carrier unit and a corresponding RISC carrier processing channel;
the cloud service platform is connected with the first carrier wave master control gateway and the second carrier wave master control gateway in a wireless mode; the first carrier gateway is connected with the second carrier unit and the corresponding RISC carrier processing channel through a live wire and a zero line; the second carrier gateway is connected with the first carrier unit and the corresponding RISC carrier processing channel through a live wire and a zero line;
the ARM main control unit is electrically connected with the first front-end equipment, the second front-end equipment, the first carrier unit and the corresponding RISC carrier processing channel, and the second carrier unit and the corresponding RISC carrier processing channel.
3. A weak signal acquisition system of an electronic communication network as claimed in claim 1, characterized in that:
the controller, its structure includes: CPU, CPU interface memory management unit, RAM, control/status register interrupt logic unit, control logic unit, sending buffer, CAN core, temporary receiving buffer, receiving filter and CAN server;
the CPU is electrically connected with the CPU interface memory management unit; the CPU memory management unit is electrically connected with the control/state register interrupt logic unit, the RAM and the CAN core; the control logic unit is electrically connected with the CPU interface memory management unit, the control/state register interrupt logic unit and the sending buffer; the sending buffer is in nuclear power connection with the CAN; the CAN core is electrically connected with the temporary receiving buffer; the temporary receiving buffer is electrically connected with the receiving filter; the CAN core is electrically connected with the CAN server.
4. A weak signal acquisition system of an electronic communication network as claimed in claim 1, characterized in that: the processor comprises a storage unit, an input unit and an output unit; the input unit is electrically connected with the storage unit; the storage unit is electrically connected with the output unit; the input unit receives the frame signal and transmits the frame signal to the storage unit for storage; the storage unit converts the frame signal into an instruction decoding, transmits the instruction decoding to the output unit, and outputs the instruction decoding by the output unit.
5. A weak signal acquisition system of an electronic communication network as claimed in claim 1, characterized in that: the low-pass filter comprises resistors R1-R5, capacitors C1-C2 and an operational amplifier; one end of the resistor R5 is connected with the output of the processor; the other end of the resistor R5 is electrically connected with one end of the resistor R4, one end of the capacitor C2 and one end of the capacitor C1 respectively; the other end of the capacitor C1 is grounded; the other end of the resistor R4 is electrically connected with the output end of the operational amplifier and one end of the resistor R3 respectively; the other end of the capacitor C2 is electrically connected with the non-inverting input end of the operational amplifier and the first end of the resistor R1 respectively; the other end of the resistor R1 is grounded; the other end of the resistor R3 is electrically connected with the inverting input end of the operational amplifier and one end of the resistor R2 respectively; the other end of the resistor R2 is grounded.
6. An electronic communication network weak signal acquisition method is applied to any one electronic communication network weak signal acquisition system of claims 1-5, and is characterized in that: the method for processing the pulse data signal of the intermediate frequency electronic weak signal in the intermediate frequency electronic communication network specifically comprises the following steps:
s101: frequency domain rearrangement; the pulse data signals of the intermediate frequency electronic communication network weak signals are N-dimensional vectors x (N), random parameters sigma and tau are obtained from the pulse data signals of the intermediate frequency electronic communication network weak signals for time domain transformation, and the time domain transformation result is shown as a formula (1):
q(n)＝x(σn+τ) (1)
in the formula (1), N represents the variation in the time domain, q (N) is the signal time domain transformation result, wherein sigma is an integer coprime to N, and tau belongs to [0, N-1 ];
root factor W of Fourier transform is introduced in formula (1)N＝e-j2π/NFrom the displacement properties and scaling properties of the fourier transform, equation (2) is derived:
Figure FDA0002673221580000031
in the formula (2), k represents a point with the coordinate k in the original signal spectrum; q (sigma k) represents a signal frequency domain rearrangement result; x (k) represents the Fourier transform of x (n);
s102: filtering by a lower smoothing window function; inputting q (n) into a Doherty-Chebyshev window function filter for filtering, and obtaining the result shown in formula (3):
y(n)＝q(n)g(n) (3)
in the formula (3), y (n) represents the result of q (n) passing through a Doherty-Chebyshev window function filter; g (n) represents a dolf-chebyshev window function;
s103: frequency domain down-sampling; aliasing is carried out on y (n) by adopting a preset factor p to obtain a frequency domain down-sampling result Z (k), which is shown in a formula (4):
Z(k)＝Y(kn/B) (4)
in formula (4), the signal y (N) has a length of N; the parameter B is an integral multiple of N; y (k) is the result of y (n) discrete Fourier transform; z (k) is the result of down-sampling the signal frequency domain at equal intervals of N/B;
s104: carrying out Hash mapping; and performing hash mapping on the result B, wherein the formula (5) is as follows:
hσ′(k)＝round(σ′kB/n) (5)
in formula (5), round (·) represents a rounding function; σ' represents a preset offset; h isσ′(k) Representing a hash function;
s105: weak signal positioning of an electronic communication network; recording the maximum spectrum peak value in all Z (k), taking the maximum spectrum peak value as a set J, and obtaining a primitive image set H of the J through Hash reverse mapping, wherein the set H satisfies the formula (6):
H＝{k∈[n]|hσ′(k)∈J} (6)
s106: estimating; and estimating the intermediate frequency electronic communication network weak signal obtained by positioning, and obtaining the spectrum of the lower smoothing window function in sigma' to finish the capture of the intermediate frequency electronic weak signal in the electronic communication network.
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