Digital oscilloscope multi-domain parameter adaptive adjustment method matched with signal frequency characteristics

Abstract

The invention discloses a multi-domain parameter adaptive adjustment method for a digital oscilloscope matched with signal frequency characteristics, and the method comprises the steps: firstly sampling an unknown input signal through a high-speed data collection system, obtaining a digital parallel sampling signal, and transmitting the digital parallel sampling signal to a multi-information-domain data processing module in an FPGA (Field Programmable Gate Array); in the multi-information-domain data processing module, time-frequency graph data acquisition of unknown signals is completed based on accurate control, fast Fourier transform and data delay feedback of time-domain data required by each frame of frequency spectrum, and the time-frequency graph data is transmitted to an industrial personal computer through a high-speed interface after being acquired. The method comprises the following steps: performing data analysis, obtaining a maximum value of spectrum energy and calculating an effective frequency index value to obtain a maximum effective frequency index value and a minimum effective frequency index value, then obtaining a multi-domain analysis parameter center frequency and an analysis bandwidth through calculation, and setting, feeding back and adjusting a multi-domain analysis processing module on a user interface of a digital oscilloscope.

Description

Technical Field

[0001] This invention belongs to the field of digital oscilloscope technology, and more specifically, relates to a method for adaptive adjustment of multi-domain parameters of a digital oscilloscope that matches the frequency characteristics of a signal. Background Technology

[0002] With the increasing demands for real-time and high-precision signal acquisition in fields such as communications, radar detection, and environmental electromagnetic monitoring, high-speed acquisition systems have become core equipment for acquiring signal characteristics. However, in practical applications, when signals with unknown frequency characteristics, such as sudden electromagnetic pulses or communication signals in unknown frequency bands, enter the system, users cannot determine the frequency range of the signal in advance and must repeatedly adjust the analysis bandwidth and center frequency parameters through trial and error. If the initially set center frequency deviates from the actual frequency band of the signal, or if the bandwidth is too narrow, causing signal truncation, or too wide, resulting in wasted resources, the parameters must be reconfigured and the acquisition repeated. This process not only consumes a lot of time but may also cause the observation window for transient signals to be missed due to adjustment delays. Furthermore, it places high demands on the professional experience of operators, significantly limiting the system's usability and application efficiency in dynamic and complex signal scenarios, and even affecting the accuracy of subsequent signal processing due to manual setting errors.

[0003] Against this backdrop, the adaptive parameter adjustment function for signals of different frequencies is of crucial necessity. This function can quickly and accurately obtain the actual frequency range of a signal through automatic analysis and processing of unknown input signals, and then autonomously set the analysis bandwidth and center frequency, providing users with an observation range matching the signal characteristics without manual intervention. From an application advantage perspective, it not only significantly simplifies the user operation process, lowers the system's usage threshold, and effectively avoids subjective errors and trial-and-error costs associated with manual parameter setting, but also ensures that the signal is always within the optimal observation bandwidth. This avoids the waste of acquisition resources caused by bandwidth redundancy and prevents signal information loss due to insufficient bandwidth, significantly improving the system's adaptability and response speed to complex and unknown signals. More importantly, this function can drive the upgrade of high-speed acquisition systems from "manual configuration" to "intelligent autonomous adaptation," giving them greater flexibility and reliability in scenarios such as real-time electromagnetic environment monitoring and sudden signal capture. This provides high-quality raw data support for subsequent signal processing, thereby expanding the system's application boundaries and enhancing its technical competitiveness and practical value in related fields. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for adaptive adjustment of multi-domain parameters of a digital oscilloscope that matches the frequency characteristics of a signal. This method automatically analyzes unknown input signals and adaptively sets the analysis bandwidth and center frequency in the frequency domain and time-frequency domain.

[0005] To achieve the above-mentioned objective, the present invention provides a method for adaptive adjustment of multi-domain parameters of a digital oscilloscope to match the frequency characteristics of a signal, characterized by comprising the following steps:

[0006] (1) Data acquisition: The signal under test is input to the digital oscilloscope, and the signal under test is acquired by the high-speed ADC at the front end to obtain parallel sampling data;

[0007] (2) Process the parallel sampling data through FPGA to obtain multi-frame spectrum data stream;

[0008] (3) The FPGA uploads multiple frames of spectrum data streams to the host computer through the high-speed communication interface. The host computer combines the multiple frames of spectrum data streams into a time-frequency diagram with an adjustable time length, and then extracts the effective frequency features based on the time-frequency diagram.

[0009] (4) Adaptive adjustment of multi-domain parameters based on the effective frequency features extracted from the time-frequency diagram.

[0010] The objective of this invention is achieved as follows:

[0011] This invention discloses a method for adaptive adjustment of multi-domain parameters of a digital oscilloscope to match the frequency characteristics of a signal. First, an unknown input signal is sampled using a high-speed data acquisition system to obtain a digital parallel sampled signal, which is then sent to a multi-information domain data processing module in an FPGA. In this module, time-frequency plot data of the unknown signal is acquired through precise control of the time-domain data required for each frame of the spectrum, fast Fourier transform, and data delay feedback. After acquisition, the time-frequency plot data is transmitted to an industrial control computer via a high-speed interface for data parsing, acquisition of the maximum spectral energy value, and calculation of the effective frequency index value. This yields the maximum and minimum effective frequency index values. Then, the center frequency and analysis bandwidth of the multi-domain analysis parameters are calculated and set on the digital oscilloscope user interface, allowing for feedback adjustment of the multi-domain analysis processing module.

[0012] Meanwhile, the digital oscilloscope multi-domain parameter adaptive adjustment method for matching signal frequency characteristics of the present invention also has the following beneficial effects:

[0013] (1) During the parameter adaptive adjustment process, the present invention can avoid the problem of analysis bandwidth redundancy or signal truncation caused by improper settings by accurately identifying and dynamically matching the signal frequency range. This not only improves the utilization efficiency of acquisition resources, but also ensures the complete preservation of signal characteristics, and significantly enhances the adaptability of the high-speed acquisition system to signals of different frequencies.

[0014] (2) In some scenarios, there are dynamic changes in signal frequency or coexistence of multiple frequency band signals. This invention can continuously perform adaptive parameter adjustment for such complex signals to ensure that the spectrum observation range always matches the signal frequency characteristics. In particular, it has significant adaptive adjustment advantages for modulated signals. By flexibly scaling the analysis time span of the time-frequency diagram, it ensures complete capture and accurate observation of various complex modulation change processes without changing hardware resources, which greatly improves the real-time performance and accuracy of high-speed acquisition system in complex scenarios.

[0015] (3) When users face unknown and complex signals, they often need to make multiple complex settings for the acquisition system. The adaptive parameter adjustment method of the present invention does not require multiple manual trial and error settings, which greatly reduces the tediousness of parameter configuration, greatly improves the convenience of observation, and lowers the threshold for use. Attached Figure Description

[0016] Figure 1 This is a block diagram of the multi-domain parameter adaptive adjustment structure of a digital oscilloscope based on the frequency characteristics of the matched signal, according to the present invention.

[0017] Figure 2 This is a flowchart of a method for adaptive adjustment of multi-domain parameters of a digital oscilloscope to match the frequency characteristics of a signal, according to the present invention.

[0018] Figure 3 This is a schematic diagram of the frame extraction module;

[0019] Figure 4 This is a diagram illustrating the maximum (minimum) energy index value;

[0020] Figure 5 This is a schematic diagram of the maximum (minimum) effective frequency index value. Detailed Implementation

[0021] The specific embodiments of the present invention will now be described with reference to the accompanying drawings to enable those skilled in the art to better understand the invention. It should be particularly noted that in the following description, detailed descriptions of known functions and designs that might obscure the main content of the invention will be omitted here.

[0022] Example

[0023] In this embodiment, as Figure 1 As shown, the system structure consists of an ADC, an FPGA, a feature extraction module, and a host computer. The measured signal is sampled by the ADC and then enters the FPGA to complete frame extraction and time-frequency graph generation in sequence. Based on the output results, the feature extraction module adjusts the parameters of the frequency domain and time-frequency domain in the multi-domain analysis module through a feedback adjustment loop, and then sends the output data to the host computer for display, thereby forming an adaptive closed-loop control system.

[0024] Below we combine Figure 1 This invention provides a detailed description of a method for adaptive adjustment of multi-domain parameters of a digital oscilloscope to match the frequency characteristics of a signal, as follows: Figure 2 As shown, it includes the following steps:

[0025] (1) Data collection;

[0026] The signal under test is input to a digital oscilloscope, and the high-speed ADC at the front end acquires the signal under test to obtain parallel sampling data;

[0027] (2) Process the parallel sampling data using FPGA;

[0028] In this embodiment, when the FPGA processes the parallel sampled data, it actually does so through its internal multi-information-domain processing module. Because the data sampled by the high-speed data acquisition system with a 20GSPS sampling rate and 8GHz measurement bandwidth is extremely large, strict data point control is required before FFT processing. The parallel sampled data is written to a depth-adjustable buffer FIFO, and the data output counter CNT is initialized. Figure 3 As shown, the FIFO data output valid signal o_data_vld is input to the counter CNT. When the FIFO data output reaches N = 2048 points sent by the industrial control computer, the output stops, the frame reset signal frame_rst is pulled high, and writing stops.

[0029] Below we combine Figure 3 The schematic diagram of the frame extraction module shown below provides a detailed description of the parallel sampling data processing flow, as detailed below:

[0030] (2.1) Parallel sampling data is input to the FPGA through a high-speed interface and then written into the buffer FIFO;

[0031] (2.2) Initialize the data output counter, and then count the data output by the FIFO. When the count value of the data output counter reaches the preset number of FFT points N per frame, the FIFO pulls up the frame reset signal frame_rst and immediately stops the FIFO writing operation to obtain a frame of N points of serial output data. In this embodiment, the number of FFT points N is set to 2048.

[0032] (2.3) The N-point serial data is sent to the FFT operation module to perform N-point fast Fourier transform to obtain single-frame spectrum data;

[0033] (2.4) When the FFT calculation of a frame is finished, the FIFO generates and pulls up the frame processing completion flag signal finish_flag, and feeds it back to the delay feedback counter;

[0034] (2.5) The host computer sends an adjustable delay value Delay to the delay feedback counter. After the delay feedback counter detects the frame processing completion flag signal finish_flag, it starts delay counting. When the delay count value reaches Delay, the delay feedback counter generates a delay end signal dly_finish and feeds it back to the FIFO.

[0035] (2.6) When the FIFO receives the delay end signal, it pulls the frame reset signal frame_rst low again, clears the count value of the output counter CNT, unlocks the write operation of the FIFO, and then returns to step (2.2) to start the acquisition and processing of the next frame of data until the acquisition and processing of M=512 frames are completed, and finally the M frame spectrum data stream is obtained.

[0036] (3) Effective frequency feature extraction;

[0037] (3.1) The FPGA uploads the M-frame spectrum data stream to the host computer through a high-speed communication interface;

[0038] (3.2) The host computer calculates the logarithmic energy amplitude of each frequency point in each frame of spectrum data, where, let the first... The first frame The logarithmic energy amplitude at each frequency point is ;

[0039] ;

[0040] in, for The real part, for The imaginary part, For the first The complex representation of frame spectrum data, i.e. ;

[0041] (3.3) The logarithmic energy amplitude of each frame of spectral data is used as the row vector of the time-frequency graph, thereby combining them into a graph of size [missing information]. Time-frequency graph with adjustable duration ;

[0042] ;

[0043] Where M represents the number of frames in the time dimension, and N represents the number of FFT points;

[0044] In this embodiment, the number of spectrum frames required for a time-frequency graph is set to 512 frames. That is, in the multi-information domain data processing module, 512 2048-point FFT processes are performed to obtain a time-frequency graph with an adjustable time length. The time length is determined by the adjustable delay value Delay.

[0045] (3.4) Regarding the time-frequency diagram Perform a global scan to search for the global maximum energy value. ;

[0046] ;

[0047] (3.5) Set energy threshold parameters Calculate the effective energy decision threshold. ;

[0048] ;

[0049] (3.6) The time-frequency diagram Consider it as consisting of M row vectors The set consisting of row vectors Corresponding to the The sequence of logarithmic energy magnitudes of the frames, i.e. ;

[0050] Traverse each row vector Extract row vectors All amplitudes greater than The element position index is used to construct the first... Effective frequency index set of frames ;

[0051] ;

[0052] In this embodiment, the host computer analyzes 512 frames of spectral data in the time-frequency graph and measures the maximum energy value in the 512 frames of spectral data. ,like Figure 4 As shown;

[0053] This embodiment uses a digital oscilloscope with a 20GSPS sampling rate and an 8GHz measurement bandwidth to measure the maximum energy value of 512 frames of spectral data. At that time, only the effective frequency points within the measurement bandwidth of 8GHz are traversed, that is... Frequency points exceeding 819 are considered invalid; set the energy threshold parameter. To obtain the minimum energy value Find all energies greater than The effective frequency index values ​​constitute the effective frequency index value set S1~S2. M ;

[0054] (3.7) For each non-empty set of indices The extreme value search algorithm is used to obtain the first Maximum frequency index value of the frame With minimum frequency index value ;

[0055] ;

[0056] ;

[0057] (3.8) Extract the global maximum effective frequency index by combining the features of all frames containing effective signals. With global minimum effective frequency index ;

[0058] ;

[0059] ;

[0060] like Figure 5 As shown, the black dots represent energy greater than [a certain value]. The effective frequency points are within the measurement bandwidth of 8 GHz, i.e., within 819 effective frequency points, for comparison d. 1,max ~d M,max Obtain the maximum effective frequency index value Compare d 1,min ~d M,min Obtain the minimum effective frequency index value ;

[0061] (4) Adaptive adjustment of multi-domain parameters;

[0062] (4.1) Based on the sampling rate of the acquisition system With FFT points Calculate frequency resolution ;

[0063] ;

[0064] In this embodiment, the sampling rate of the acquisition system is 20 GSPS, and the number of FFT points is 2048;

[0065] (4.2) Index value of the global maximum effective frequency and the global minimum effective frequency index value Convert to the true frequency maximum value f max and minimum value f min ;

[0066] ;

[0067] ;

[0068] (4.3) Calculate and analyze bandwidth f B ;

[0069] ;

[0070] (4.4) Calculate the center frequency f c ;

[0071] ;

[0072] (4.5) The host computer software calculates the result f B f c The display settings are automatically updated on the digital oscilloscope interface; simultaneously, the host computer software sends f through the feedback loop. B f c The data is then transferred to the FPGA to adaptively adjust the parameters for the next round of data acquisition and analysis.

[0073] In this embodiment of the high-speed data acquisition system with a 20GSPS sampling rate and 8GHz measurement bandwidth, conversion is required to obtain the actual center frequency and analysis bandwidth. After performing a 2048-point FFT on the time-domain data using a digital oscilloscope with a 20GSPS sampling rate and 8GHz bandwidth, the 2048 points in the frequency domain will start from 0Hz and be analyzed at a fixed frequency resolution. The system is uniformly distributed and covers up to 10 GHz Nyquist frequency. However, due to the limitation of 8 GHz measurement bandwidth, frequency point data in the range of 8 GHz to 10 GHz are invalid. In this embodiment, the frequency corresponding to the kth frequency point (k takes values ​​from 0 to 2047) is k multiplied by the frequency resolution, where k=0 corresponds to the 0 Hz DC component, and k≈819 corresponds to the upper limit of the 8 GHz bandwidth.

[0074] Maximum effective frequency index value With minimum effective frequency index value The difference is used to obtain the analysis bandwidth. In this embodiment, the actual analysis bandwidth is obtained:

[0075] ;

[0076] Minimum effective frequency index value With the maximum effective frequency index value The median value is the center frequency. In this embodiment, the actual center frequency is obtained as follows:

[0077] ;

[0078] Based on the calculation results, set the center frequency and analysis bandwidth of the multi-domain analysis parameters;

[0079] Repeat the above steps. Whenever the unknown input signal changes, the system acquires, processes, and calculates the new signal. Finally, based on the calculation results, it sets the center frequency and analysis bandwidth.

[0080] Although the illustrative specific embodiments of the present invention have been described above to enable those skilled in the art to understand the invention, it should be understood that the invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the invention as defined and determined by the appended claims, and all inventions utilizing the concept of the present invention are protected.

Claims

1. A method for adaptive adjustment of multi-domain parameters of a digital oscilloscope to match the frequency characteristics of a signal, characterized in that, Includes the following steps: (1) Data acquisition: The signal under test is input to the digital oscilloscope, and the signal under test is acquired by the high-speed ADC at the front end to obtain parallel sampling data; (2) Process the parallel sampling data through FPGA to obtain multi-frame spectrum data stream; (3) The FPGA uploads multiple frames of spectrum data streams to the host computer through the high-speed communication interface. The host computer combines the multiple frames of spectrum data streams into a time-frequency diagram with an adjustable time length, and then extracts the effective frequency features based on the time-frequency diagram. (4) Adaptive adjustment of multi-domain parameters based on the effective frequency features extracted from the time-frequency diagram.

2. The method for adaptive adjustment of multi-domain parameters of a digital oscilloscope to match the frequency characteristics of a signal according to claim 1, characterized in that, The specific processing flow of step (2) is as follows: (2.1) Parallel sampling data is input to the FPGA through a high-speed interface and then written into the buffer FIFO; (2.2) Initialize the data output counter, and then count the data output by the FIFO. When the count value of the data output counter reaches the preset number of FFT points N per frame, the FIFO pulls up the frame reset signal and immediately stops the FIFO writing operation to obtain a frame of N-point serial output data. (2.3) The N-point serial data is sent to the FFT operation module to perform N-point fast Fourier transform to obtain single-frame spectrum data; (2.4) When the FFT calculation of a frame is completed, the FIFO generates and raises the frame processing completion flag signal, and feeds it back to the delay feedback counter; (2.5) The host computer sends an adjustable delay value Delay to the delay feedback counter. After the delay feedback counter detects the frame processing completion flag signal, it starts delay counting. When the delay count value reaches Delay, the delay feedback counter generates a delay end signal and feeds it back to the FIFO. (2.6) When the FIFO receives the delay end signal, it pulls the frame reset signal low again, clears the count value of the output counter, unlocks the write operation of the FIFO, and then returns to step (2.2) to start the acquisition and processing of the next frame of data until the acquisition and processing of M frames are completed, and finally the M frame spectrum data stream is obtained.

3. The method for adaptive adjustment of multi-domain parameters of a digital oscilloscope to match the frequency characteristics of a signal according to claim 1, characterized in that, The specific processing flow of step (3) is as follows: (3.1) The FPGA uploads the M-frame spectrum data stream to the host computer through a high-speed communication interface; (3.2) The host computer calculates the logarithmic energy amplitude of each frequency point in each frame of spectrum data, where, let the first... The first frame The logarithmic energy amplitude at each frequency point is ; ； in, for The real part, for The imaginary part, For the first The complex representation of frame spectrum data, i.e. ; (3.3) The logarithmic energy amplitude of each frame of spectral data is used as the row vector of the time-frequency graph, thereby combining them into a graph of size [missing information]. Time-frequency graph with adjustable duration ; ； Where M represents the number of frames in the time dimension, and N represents the number of FFT points; The time-frequency graph data is transmitted to the host computer to construct a time-frequency data space, and the effective frequency features of the signal are extracted using matrix analysis. (3.4) Regarding the time-frequency diagram Perform a global scan to search for the global maximum energy value. ; ； (3.5) Set energy threshold parameters Calculate the effective energy decision threshold. ; ； (3.6) The time-frequency diagram Consider it as consisting of M row vectors The set consisting of row vectors Corresponding to the The sequence of logarithmic energy magnitudes of the frames, i.e. ; Traverse each row vector Extract row vectors All amplitudes greater than The element position index is used to construct the first... Effective frequency index set of frames ; ； (3.7) For each non-empty set of indices The extreme value search algorithm is used to obtain the first Maximum frequency index value of the frame With minimum frequency index value ; ； ； (3.8) Extract the global maximum effective frequency index by combining the features of all frames containing effective signals. With global minimum effective frequency index ; ； 。 4. The method for adaptive adjustment of multi-domain parameters of a digital oscilloscope to match the frequency characteristics of a signal according to claim 1, characterized in that, The specific processing flow of step (4) is as follows: (4.1) Based on the sampling rate of the acquisition system With FFT points Calculate frequency resolution ; ； (4.2) Index value of the global maximum effective frequency and the global minimum effective frequency index value Convert to the true frequency maximum value f max and minimum value f min ; ； ； (4.3) Calculate and analyze bandwidth f B ; ； (4.4) Calculate the center frequency f c ; ； (4.5) The host computer software calculates the result f B f c The display settings are automatically updated on the digital oscilloscope interface; simultaneously, the host computer software sends f through the feedback loop. B f c The data is then transferred to the FPGA to adaptively adjust the parameters for the next round of data acquisition and analysis.

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