CN114398763B - Random signal analysis experiment virtual simulation system and control method - Google Patents
Random signal analysis experiment virtual simulation system and control method Download PDFInfo
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Abstract
The invention belongs to the technical field of experimental network teaching of communication engineering, information engineering and the like, and discloses a random signal analysis experimental virtual simulation system and a control method, wherein the random signal analysis experimental virtual simulation system comprises the following components: the communication signal generation hardware circuit module is used for generating communication signals with different modulation modes; a noise generation module for generating a noise signal; the communication system hardware circuit module is used for realizing a linear system or a nonlinear system; and the signal analysis software module is used for realizing characteristic analysis of the communication signal. The invention adopts a virtual simulation experiment platform of a random signal analysis experiment combining software and hardware, which can solve the problem of overlarge investment of experimental equipment and the problem of incapability of aggregation; meanwhile, the student experiment time and the experiment place are flexible, and the student can perform experiments anytime and anywhere as long as the network and the notebook computer are provided.
Description
Technical Field
The invention belongs to the technical field of experimental network teaching of communication engineering, information engineering and the like, and particularly relates to a random signal analysis experimental virtual simulation system and a control method.
Background
At present, the random signal analysis experiment is an experimental course which is necessary to be repaired by related professions such as communication engineering, information engineering and the like, and the traditional random signal analysis experiment course utilizes a specially-developed experiment box and a specially-designed experiment item to analyze and test the working principle, composition and performance of each subsystem through teaching in a classroom, practice of students after class and teaching in a class, and teaching mode of answering in class, so that the students can recognize the characteristics of random signals in various communication systems. Through experiments, the using method of a conventional measuring instrument in the communication engineering is mastered; and the method is matched with the test key of the main performance index of the learning system of the typical experimental system, enriches and widens the knowledge of students on the aspect of qualitative and quantitative analysis of the system, and enables the students to receive engineering training.
However, with the continuous change of social environment, the technological development is continuous, and the traditional offline experimental mode cannot meet the experimental requirements. The traditional offline experiment mode needs to prepare a set of experiment equipment for each student doing experiments simultaneously, and because the total number of students is too large, even if batch teaching is carried out, the number of the sets of the experiment equipment needed to be prepared is not small, and the economic cost price ratio is large. In the traditional experiment mode, students must come to a laboratory to complete the experiment in a specified time, but in the current management mode of schools, "a life-time class chart" is implemented, and the course and the class time of each student are not completely the same, so that it is difficult to ensure that students in a class can enter the laboratory to complete the experiment at the same time.
Through the above analysis, the problems and defects existing in the prior art are as follows:
(1) The traditional offline experiment mode has larger economic cost price ratio.
(2) It is difficult to ensure that students in a class can enter a laboratory to complete experiments simultaneously in a traditional experiment mode.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a random signal analysis experiment virtual simulation system and a control method.
The invention is realized in such a way that the random signal analysis experiment virtual simulation control method comprises the following steps:
firstly, inputting account information into an experiment selection interface, and selecting an experiment equipment number to start an experiment;
secondly, selecting experimental projects; setting experimental parameters;
the third step, the virtual oscilloscope port drags the connection line to the signal port to be observed, and the virtual oscilloscope is connected with the signal to be observed;
fourth, observing the time domain waveform of the signal, and recording the amplitude of the observed signal; observing the waveform of the signal frequency domain;
fifthly, entering a random signal characteristic analysis module; calculating the average value of the random signals, reading the data displayed in the interface and recording the experimental result; calculating random signal variance, reading data displayed in an interface and recording an experiment result; calculating an autocorrelation function of the random signal, and storing an autocorrelation function waveform diagram displayed in the interface; selecting a power spectrum density estimation method, estimating the power spectrum density of the random signal, and storing a signal power spectrum density waveform chart displayed in an interface;
sixthly, performing random signal characteristic analysis MATLAB secondary development experiment: filling in hardware information when writing MATLAB codes according to the copied IP address and equipment number information of the remote equipment, writing MATLAB programs according to own interests and ideas to analyze the characteristics of signals, and storing experimental results;
seventh, generating signals to generate FPGA secondary development experiments, and writing FPGA hardware description language programs in a quick II software system; compiling, simulating and locking IO port pins in an FPGA compiling environment to generate an rbf target file; selecting a generated rbf target file, and loading the rbf target file to a secondary development platform; observing the waveform of the output signal by using a virtual oscilloscope;
and eighth step, uploading experiment reports and inquiring experiment results on line.
Further, the random signal analysis experiment virtual simulation control method utilizes a virtual oscilloscope to observe the time domain and frequency domain characteristics of signals.
Furthermore, the random signal analysis experiment virtual simulation control method has the function of secondary development based on FPGA and MATLAB, and supports students to design a hardware circuit and a software system according to own interests, so that signal generation and analysis experiments are completed.
Further, the experimental parameters include: carrier frequency, symbol rate.
Another object of the present invention is to provide a random signal analysis experiment virtual simulation system for implementing the random signal analysis experiment virtual simulation control method, the random signal analysis experiment virtual simulation system comprising:
the communication signal generation hardware circuit module is used for generating communication signals with different modulation modes;
a noise generation module for generating a noise signal;
the communication system hardware circuit module is used for realizing a linear system and a nonlinear system;
and the signal analysis software module is used for realizing characteristic analysis of the communication signal.
Further, the communication signal generation hardware circuit module comprises a digital modulation system and an analog modulation system; the digital modulation system comprises an ASK modulation system, an FSK modulation system, a BPSK modulation system, a QPSK modulation system and a 16QAM modulation system; the analog modulation system comprises an AM modulation system, an FM modulation system and a PM modulation system;
the noise generation software module comprises a normal distribution noise generation module, a Poisson distribution noise generation module and a Rayleigh distribution noise generation module.
Further, the communication system circuit module comprises a linear system circuit and a nonlinear system circuit, wherein the linear system circuit comprises a low-pass filter circuit, a high-pass filter circuit and a band-pass filter circuit, and the nonlinear circuit comprises a limiting amplifier circuit, a diode circuit and a mixer circuit;
the signal analysis software module performs calculation analysis on various random signal characteristics, and comprises a mean value calculation module of a random signal, a variance calculation module of the random signal, an autocorrelation function estimation module of the random signal and a power spectrum density estimation module of the random signal, wherein the estimation of the autocorrelation function comprises two methods of biased estimation and unbiased estimation, and the power spectrum density estimation adopts three methods of an autocorrelation function method, a Fourier transformation method and a segmentation average periodic chart method.
By combining all the technical schemes, the invention has the advantages and positive effects that: the invention adopts a virtual simulation experiment platform of a random signal analysis experiment combining software and hardware, which can solve the problem of overlarge investment of experimental equipment and the problem of incapability of aggregation; meanwhile, the student experiment time and the experiment place are flexible, and the student can perform experiments anytime and anywhere as long as the network and the notebook computer are provided.
The invention can reduce the investment of expensive experimental equipment in universities and can not be limited by experimental sites and experimental time in the process of experiments; the method has the functions of secondary development of the FPGA and the Matlab, the experimental content is expandable and customizable, and the method has strong flexibility; in the teaching process, students can intuitively know an analog modulation system and a digital modulation system through the virtual simulation experiment platform, and the signal characteristic analysis method is deeply understood; the test operation and the obtained data of the students can be checked and scored, so that the load of the teacher on the site for checking and scoring can be greatly reduced.
Drawings
Fig. 1 is a flowchart of a random signal analysis experiment virtual simulation control method provided by an embodiment of the invention.
FIG. 2 is a schematic diagram of a random signal analysis experiment virtual simulation system according to an embodiment of the present invention;
in fig. 2: 1. a communication signal generating hardware circuit module; 2. a noise generation module; 3. a communication system hardware circuit module; 4. and a signal analysis software module.
Fig. 3 is a schematic diagram of a random signal analysis experiment virtual simulation system provided by an embodiment of the present invention.
Fig. 4 is a schematic diagram of virtual oscilloscope match mode selection according to an embodiment of the present invention.
Fig. 5 is a cross-axis adjustment button of a virtual oscilloscope provided by an embodiment of the invention.
Fig. 6 is a view of a virtual oscilloscope vertical axis adjustment button provided by an embodiment of the present invention.
Fig. 7 is a schematic diagram of a virtual oscilloscope measuring signal frequency according to an embodiment of the present invention.
Fig. 8 is a schematic diagram of a random signal analysis "MATLAB secondary development" function provided by an embodiment of the present invention.
Fig. 9 is an information prompt box of MATLAB secondary development equipment provided by the embodiment of the present invention.
Fig. 10 is a schematic diagram of a random signal analysis "FPGA secondary development" function provided by an embodiment of the present invention.
FIG. 11 is an illustration of the secondary development operation of an FPGA provided by an embodiment of the present invention.
Fig. 12 is a schematic diagram of an FPGA secondary development module provided in an embodiment of the present invention.
Fig. 13 is a schematic diagram of FPGA secondary development signal measurement according to an embodiment of the present invention.
Fig. 14 is a student operation interface of the virtual simulation experiment platform provided by the embodiment of the invention.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Aiming at the problems existing in the prior art, the invention provides a random signal analysis experiment virtual simulation system and a control method, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the random signal analysis experiment virtual simulation control method provided by the invention comprises the following steps:
s101: inputting account information into an experiment selection interface, and selecting an experiment equipment number to start an experiment;
s102: selecting an experiment item; setting experimental parameters;
s103: the virtual oscilloscope port drags the connection line to the signal port to be observed, and the virtual oscilloscope is connected with the signal to be observed;
s104: observing the time domain waveform of the signal, and recording the amplitude of the observed signal; observing the waveform of the signal frequency domain;
s105: entering a random signal characteristic analysis module; calculating the average value of the random signals, reading the data displayed in the interface and recording the experimental result; calculating random signal variance, reading data displayed in an interface and recording an experiment result; calculating an autocorrelation function of the random signal, and storing an autocorrelation function waveform diagram displayed in the interface; selecting a power spectrum density estimation method, estimating the power spectrum density of the random signal, and storing a signal power spectrum density waveform chart displayed in an interface;
s106: random signal characterization "MATLAB secondary development" experiment: filling in hardware information when writing MATLAB codes according to the copied information such as the IP address, the equipment number and the like of the remote equipment, writing MATLAB programs according to own interests and ideas to analyze the characteristics of signals, and storing experimental results;
s107: generating a signal to generate an FPGA secondary development experiment, and writing an FPGA hardware description language program in a Quartz II software system; compiling, simulating and locking IO port pins in an FPGA compiling environment to generate an rbf target file; selecting a generated rbf target file, and loading the rbf target file to a secondary development platform; observing the waveform of the output signal by using a virtual oscilloscope;
s108: and uploading an experiment report on line, and inquiring the experiment result.
Other steps may be performed by those skilled in the art of the method for controlling the random signal analysis experiment virtual simulation provided by the present invention, and the method for controlling the random signal analysis experiment virtual simulation provided by the present invention in fig. 1 is merely a specific embodiment.
As shown in fig. 2, the random signal analysis experiment virtual simulation system provided by the present invention includes:
the communication signal generating hardware circuit module 1 is used for generating communication signals with different modulation modes.
A noise generation module 2 for generating a noise signal.
The communication system hardware circuit module 3 is used for realizing a linear system or a nonlinear system.
And the signal analysis software module 4 is used for realizing characteristic analysis of the communication signal.
The technical scheme of the invention is further described below with reference to specific embodiments.
Example 1:
in an embodiment of the invention: the communication signal generating hardware circuit module 1 comprises a digital modulation system and an analog modulation system, wherein the digital modulation system comprises an ASK modulation system, an FSK modulation system, a BPSK modulation system, a QPSK modulation system and a 16QAM modulation system; the analog modulation system comprises an AM modulation system, an FM modulation system and a PM modulation system.
Example 2:
in an embodiment of the invention: the noise generation software module 2 may generate random noise with several different distributions, and specifically includes a normal distribution noise generation module, a poisson distribution noise generation module, and a rayleigh distribution noise generation module.
Example 3:
in an embodiment of the invention: the communication system circuit block 3 includes a linear system circuit including a low-pass filter circuit, a high-pass filter circuit, and a band-pass filter circuit, and a nonlinear system circuit including a limiting amplifier circuit, a diode circuit, and a mixer circuit.
Example 4:
in an embodiment of the invention: the signal analysis software module 4 can perform calculation analysis on various random signal characteristics, including a mean value calculation module of the random signal, a variance calculation module of the random signal, an autocorrelation function estimation module of the random signal, and a power spectrum density estimation module of the random signal, wherein the estimation of the autocorrelation function has two methods of biased estimation and unbiased estimation, and the power spectrum density estimation can adopt three methods of an autocorrelation function method, a fourier transform method and a piecewise average periodic chart method.
Example 5:
in an embodiment of the invention: the random signal analysis experiment virtual simulation system provided by the invention can observe the time domain and frequency domain characteristics of signals by using the virtual oscilloscope.
Example 6:
in an embodiment of the invention: the random signal analysis experiment virtual simulation system provided by the invention also has the function of secondary development based on FPGA and MATLAB, and supports students to design a hardware circuit and a software system according to own interests so as to complete signal generation and analysis experiments.
Example 7:
the invention provides a random signal analysis experiment virtual simulation control method, which specifically comprises the following steps:
first, registering: filling in information such as names, academic numbers, professions, classes and the like, registering account numbers, and acquiring experimental rights;
secondly, logging in an experimental platform: after entering a virtual simulation platform of a random signal analysis experiment, inputting account information into an experiment selection interface, and selecting an experiment equipment number to start an experiment;
thirdly, selecting experimental items: selecting an experimental item, such as selecting an "ASK signal generation and analysis experiment";
fourth, parameter setting: setting experimental parameters such as carrier frequency, symbol rate and the like;
fifth step, virtual instrument connection: clicking a virtual oscilloscope port, dragging a connecting wire to a signal port to be observed, and connecting the virtual oscilloscope with the signal to be observed;
sixth, observing the time domain waveform of the signal: moving a mouse to a virtual oscilloscope position, clicking a left key, opening an oscilloscope window, observing a signal time domain waveform, and recording the amplitude value of the observed signal;
seventh, observing the waveform of the signal frequency domain:
1) Clicking a 'math' button in the virtual oscilloscope, selecting an 'FFT' mode, and selecting a signal channel to be observed, such as 'CH 1';
2) The mouse moves to a horizontal axis zoom button in the virtual oscilloscope, clicks a left button of the mouse, slides a mouse wheel, and adjusts a time window to a proper size;
3) Moving the mouse to a vertical axis scaling button of the oscillography corresponding channel, clicking a left button of the mouse, sliding a mouse wheel, and adjusting the amplitude to a proper size; after the transverse axis and the longitudinal axis are adjusted, the frequency domain waveform of the selected channel signal can be observed;
4) Measurement of signal frequency: the mouse moves to the position of the cursor, clicks the left button of the mouse, drags the cursor to the peak point of the signal frequency domain waveform, reads the value at the upper right corner of the oscilloscope (as shown in fig. 5), and can obtain the central frequency of the measured signal;
eighth, click the "random signal characteristic analysis" button, enter the random signal characteristic analysis module;
1) Clicking a mean button to calculate the mean value of the random signal, reading the data displayed in the interface and recording the experimental result;
2) Clicking a variance button to calculate random signal variance, reading data displayed in an interface and recording an experiment result;
3) Clicking an 'autocorrelation function' button, calculating an autocorrelation function of a random signal, and storing an autocorrelation function waveform diagram displayed in an interface;
4) Clicking a power spectrum density button, selecting a power spectrum density estimation method, estimating the power spectrum density of the random signal, and storing a signal power spectrum density waveform chart displayed in an interface;
ninth step, random signal characteristic analysis "MATLAB secondary development" experiment:
1) Clicking a button of 'MATLAB secondary development', and entering a MATLAB secondary development module;
2) After clicking the MATLAB secondary development button, the platform pops up a device information prompt box, indicates the information such as the ip address, the port number, the user identification code and the like of the current device, clicks the one-key copy button, and copies the device information;
3) Filling in hardware information when writing MATLAB codes according to the copied information such as the IP address, the equipment number and the like of the remote equipment, writing MATLAB programs according to own interests and ideas to analyze the characteristics of signals, and storing experimental results;
tenth step, signal generation 'FPGA secondary development' experiment
1) Clicking an FPGA secondary development button, and entering an FPGA secondary development module;
2) After clicking the 'FPGA secondary development' button, the platform pops up the FPGA secondary development operation instruction, and writes the FPGA hardware description language program in the Quartz II software system according to the operation instruction.
3) Compiling, simulating and locking IO port pins in an FPGA compiling environment to generate an rbf target file;
4) Loading an FPGA program file: and (3) moving the mouse to a chip icon in the secondary development module, clicking a left button of the mouse, popping up a file loading dialog box, selecting the rbf target file generated in the step (3), and loading the rbf target file to the secondary development platform.
5) Observing the waveform of the output signal by using a virtual oscilloscope: the mouse moves to the test hole position in the virtual oscilloscope, the left button of the mouse is clicked to drag to the input pin or the output pin end of the secondary development module, the mouse is loosened, the left button of the mouse is used for clicking the virtual oscilloscope screen area, and the virtual instrument is unfolded, so that the tested signal waveform can be observed.
Eleventh step, submitting an experiment report: after the experiment is completed, the students write experiment reports, and click an 'upload report' button in the virtual simulation experiment platform to upload the experiment reports.
Twelfth, inquiring experiment results: clicking the "inquiry score" button in the experimental platform can inquire the experimental score.
The technical scheme of the invention is further described below with reference to the accompanying drawings.
As shown in FIG. 3, the software and hardware combined virtual simulation experiment platform of the random signal analysis experiment provided by the invention comprises a hardware circuit module for generating communication signals, a noise generation module, a communication system hardware circuit module and a signal analysis software module.
The hardware circuit module for generating communication signals in the virtual simulation experiment platform of the random signal analysis experiment of software and hardware comprises a digital modulation system and an analog modulation system, wherein the digital modulation system comprises an ASK modulation system, an FSK modulation system, a BPSK modulation system, a QPSK modulation system and a 16QAM modulation system; the analog modulation system comprises an AM modulation system, an FM modulation system and a PM modulation system;
the noise generation software module in the virtual simulation experiment platform of the random signal analysis experiment of the software and the hardware can generate random noise with different distributions, and specifically comprises a normal distribution noise generation module, a Poisson distribution noise generation module and a Rayleigh distribution noise generation module;
the communication system circuit module in the virtual simulation experiment platform of the random signal analysis experiment of the software and the hardware comprises a linear system circuit and a nonlinear system circuit, wherein the linear system comprises a low-pass filter circuit, a high-pass filter circuit and a band-pass filter circuit, and the nonlinear circuit comprises a limiting amplifier circuit, a diode circuit and a mixer circuit;
the virtual simulation experiment platform of the random signal analysis experiment of software and hardware can observe the time domain and frequency domain characteristics of signals by using a virtual oscilloscope;
the signal analysis software module in the virtual simulation experiment platform of the random signal analysis experiment of software and hardware can carry out calculation analysis on various random signal characteristics, and the method comprises a mean value calculation module of random signals, a variance calculation module of random signals, an autocorrelation function estimation module of random signals and a power spectrum density estimation module of random signals, wherein the estimation of the autocorrelation function is in a biased estimation mode and an unbiased estimation mode, and the power spectrum density estimation can adopt three methods of an autocorrelation function method, a Fourier transformation method and a segmentation average periodic graph method.
The virtual simulation experiment platform of the random signal analysis experiment of the software and the hardware also has the function of secondary development based on the FPGA and the MATLAB, and supports students to design a hardware circuit and a software system according to own interests so as to complete the signal generation and analysis experiment.
The operation method of the virtual simulation experiment platform provided by the invention comprises the following steps:
s1: registering: filling in information such as names, academic numbers, professions, classes and the like, registering account numbers, and obtaining experimental rights.
S2: logging in an experiment platform: after entering a virtual simulation platform of the random signal analysis experiment, inputting account information into an experiment selection interface, and selecting an experiment equipment number to start an experiment.
S3: experimental project selection: the experimental program is selected, such as "ASK signal generation and analysis experiments".
S4: parameter setting: experimental parameters such as carrier frequency, symbol rate, etc. are set.
S5: virtual instrument wiring: clicking the virtual oscilloscope port, dragging the connecting wire to the signal port to be observed, and connecting the virtual oscilloscope with the signal to be observed.
S6: observing the time domain waveform of the signal: and (3) moving the mouse to a virtual oscilloscope position, clicking a left key, opening an oscilloscope window, observing the time domain waveform of the signal, and recording the amplitude value of the observed signal.
S7: observing the frequency domain waveform of the signal:
s7.1, clicking a 'math' button in the virtual oscilloscope, selecting an 'FFT' mode, and selecting a signal channel to be observed, such as 'CH 1', as shown in FIG. 4;
s7.2: the mouse moves to a horizontal axis zoom button (shown in figure 5) in the virtual oscilloscope, clicks a left mouse button, slides a mouse wheel, and adjusts a time window to a proper size;
s7.3: moving the mouse to a vertical axis zoom button (shown in figure 6) of the oscillography corresponding channel, clicking a left button of the mouse, sliding a mouse wheel, and adjusting the amplitude to a proper size; after the transverse axis and the longitudinal axis are adjusted, the frequency domain waveform of the selected channel signal can be observed;
s7.4: measurement of signal frequency: the mouse moves to the position of the cursor, the left button of the mouse is clicked, the cursor is dragged to the peak point of the signal frequency domain waveform, and the value at the upper right corner of the oscilloscope (shown in fig. 7) is read, so that the central frequency of the measured signal can be obtained.
S8: clicking a random signal characteristic analysis button to enter a random signal characteristic analysis module;
s8.1: clicking a mean button to calculate the mean value of the random signal, reading the data displayed in the interface and recording the experimental result;
s8.2: clicking a variance button to calculate random signal variance, reading data displayed in an interface and recording an experiment result;
s8.3: clicking an 'autocorrelation function' button, calculating an autocorrelation function of a random signal, and storing an autocorrelation function waveform diagram displayed in an interface;
s8.4: clicking a power spectrum density button, selecting a power spectrum density estimation method, estimating the power spectrum density of the random signal, and storing a signal power spectrum density waveform chart displayed in an interface.
S9: random signal characterization "MATLAB secondary development" experiment:
s9.1: clicking a 'MATLAB secondary development' button, and entering a MATLAB secondary development module as shown in figure 8;
s9.2: after clicking the "MATLAB secondary development" button, the platform pops up the device information prompt box (as shown in fig. 9), indicates the information such as the ip address, port number and user identification code of the current device, clicks the "one-key copy" button, and copies the information.
S9.3: according to information such as signal IP address, equipment number and the like of the remote equipment, which are popped up by the simulation platform, hardware information is filled in when MATLAB codes are written, then MATLAB programs are written according to interests and ideas of the users to analyze the characteristics of the signals, and experimental results are stored.
S10: signal generation 'FPGA secondary development' experiment
S10.1: clicking an FPGA secondary development button, and entering an FPGA secondary development module as shown in FIG. 10;
s10.2: after clicking the 'FPGA secondary development' button, the platform pops up the FPGA secondary development operation instruction (as shown in figure 11), and writes the FPGA hardware description language program in the quick II software system according to the operation instruction;
s10.3: compiling, simulating and locking IO port pins in an FPGA compiling environment to generate an rbf target file;
s10.4: loading an FPGA program file: the mouse moves to a chip icon in the secondary development module, as shown in fig. 12, a left button of the mouse is clicked, a file loading dialog box is popped up, and the rbf target file generated in S10.3 is selected and loaded to the secondary development platform;
s10.5: observing the waveform of the output signal by using a virtual oscilloscope: the mouse is moved to the test hole position in the virtual oscilloscope, the left button of the mouse is clicked to drag to the input pin or the output pin end of the secondary development module, the mouse is loosened, the left button of the mouse is used for clicking on the virtual oscilloscope screen area, the virtual instrument is unfolded, the tested signal waveform can be observed, and the signal measurement schematic diagram is shown in fig. 13.
S11: submitting an experiment report: after the experiment is completed, the students write the experiment report, and click on an 'upload report' button in the virtual simulation experiment platform to upload the experiment report, as shown in fig. 14.
S12: inquiring experiment achievement: clicking the "inquiry score" button in the experimental platform can inquire the experimental score.
It should be noted that the embodiments of the present invention can be realized in hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or special purpose design hardware. Those of ordinary skill in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such as provided on a carrier medium such as a magnetic disk, CD or DVD-ROM, a programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The device of the present invention and its modules may be implemented by hardware circuitry, such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., as well as software executed by various types of processors, or by a combination of the above hardware circuitry and software, such as firmware.
The foregoing is merely illustrative of specific embodiments of the present invention, and the scope of the invention is not limited thereto, but any modifications, equivalents, improvements and alternatives falling within the spirit and principles of the present invention will be apparent to those skilled in the art within the scope of the present invention.
Claims (5)
1. The random signal analysis experiment virtual simulation control method is characterized by comprising the following steps of:
firstly, inputting account information into an experiment selection interface, and selecting an experiment equipment number to start an experiment;
secondly, selecting experimental projects; setting experimental parameters;
the third step, the virtual oscilloscope port drags the connection line to the signal port to be observed, and the virtual oscilloscope is connected with the signal to be observed;
fourth, observing the time domain waveform of the signal, and recording the amplitude of the observed signal; observing the waveform of the signal frequency domain;
fifthly, entering a random signal characteristic analysis module; calculating the average value of the random signals, reading the data displayed in the interface and recording the experimental result; calculating random signal variance, reading data displayed in an interface and recording an experiment result; calculating an autocorrelation function of the random signal, and storing an autocorrelation function waveform diagram displayed in the interface; selecting a power spectrum density estimation method, estimating the power spectrum density of the random signal, and storing a signal power spectrum density waveform chart displayed in an interface;
sixthly, performing random signal characteristic analysis MATLAB secondary development experiment: filling in hardware information when writing MATLAB codes according to the copied IP address and equipment number information of the remote equipment, writing MATLAB programs according to own interests and ideas to analyze the characteristics of signals, and storing experimental results;
seventh, generating signals to generate FPGA secondary development experiments, and writing FPGA hardware description language programs in a Quartz II software system; compiling, simulating and locking IO port pins in an FPGA compiling environment to generate an rbf target file; selecting a generated rbf target file, and loading the rbf target file to a secondary development platform; observing the waveform of the output signal by using a virtual oscilloscope;
eighth step, uploading experiment reports on line and inquiring experiment results;
the random signal analysis experiment virtual simulation control method utilizes a virtual oscilloscope to observe the time domain and frequency domain characteristics of signals;
the random signal analysis experiment virtual simulation control method has the function of secondary development based on FPGA and MATLAB, and supports students to design a hardware circuit and a software system according to own interests so as to complete signal generation and analysis experiments.
2. The random signal analysis experiment virtual simulation control method according to claim 1, wherein the experiment parameters include: carrier frequency, symbol rate.
3. A random signal analysis experiment virtual simulation system for implementing the random signal analysis experiment virtual simulation control method of any one of claims 1 to 2, characterized in that the random signal analysis experiment virtual simulation system comprises:
the communication signal generation hardware circuit module is used for generating communication signals with different modulation modes;
a noise generation module for generating a noise signal;
the communication system hardware circuit module is used for realizing a linear system or a nonlinear system;
and the signal analysis software module is used for realizing characteristic analysis of the communication signal.
4. The stochastic signal analysis experiment virtual simulation system of claim 3, wherein the communication signal generation hardware circuit module comprises a digital modulation system and an analog modulation system; the digital modulation system comprises an ASK modulation system, an FSK modulation system, a BPSK modulation system, a QPSK modulation system and a 16QAM modulation system; the analog modulation system comprises an AM modulation system, an FM modulation system and a PM modulation system;
the noise generation software module comprises a normal distribution noise generation module, a Poisson distribution noise generation module and a Rayleigh distribution noise generation module.
5. The stochastic signal analysis experiment virtual simulation system of claim 3, wherein the communication system circuit module comprises a linear system circuit and a nonlinear system circuit, wherein the linear system comprises a low pass filter circuit, a high pass filter circuit, a band pass filter circuit, and the nonlinear circuit comprises a limiting amplifier circuit, a diode circuit, and a mixer circuit;
the signal analysis software module performs calculation analysis on various random signal characteristics, and comprises a mean value calculation module of a random signal, a variance calculation module of the random signal, an autocorrelation function estimation module of the random signal and a power spectrum density estimation module of the random signal, wherein the estimation of the autocorrelation function comprises two methods of biased estimation and unbiased estimation, and the power spectrum density estimation adopts three methods of an autocorrelation function method, a Fourier transformation method and a segmentation average periodic chart method.
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