Adaptive high-precision acquisition method of intelligent oscilloscope

Abstract

The application discloses a self-adaptive high-precision acquisition method of an intelligent oscilloscope, wherein a spectrum feature distribution of a to-be-tested signal is extracted based on a spectrum sensing technology, then the type of the to-be-tested signal is judged according to the spectrum feature distribution, and a corresponding sampling architecture is adaptively matched according to different signal types, so that the adaptive dynamic configuration of a bandwidth and a sampling rate is realized; finally, the out-of-band noise in the acquisition data is refined and filtered by using adaptive filtering, and the effective observation data are obtained by automatically configuring an effective observation bandwidth, so that the acquisition precision is improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of oscilloscopes, and more particularly relates to an adaptive high-precision acquisition method of an intelligent oscilloscope. BACKGROUND

[0002] In radar, communication, navigation and other signal test scenarios, the signal frequency is as high as tens of GHz. Therefore, the acquisition system urgently needs higher sampling rate and bandwidth. However, there is a conflict between bandwidth and high resolution in the acquisition system. With the increase of the bandwidth of the acquisition system, more noise will be introduced, resulting in the decrease of the acquisition accuracy.

[0003] In the traditional acquisition system, the test resources are evenly distributed in the entire bandwidth, which means that the signals in the entire bandwidth range are acquired and processed. However, in most scenarios, the signals often have sparse characteristics in the frequency domain. The average allocation of bandwidth test resources will waste bandwidth resources and introduce unnecessary out-of-band noise, thereby reducing the acquisition performance. On the contrary, due to the limitation of the performance of a single analog-to-digital converter, the acquisition system usually adopts time interleaving (TI) technology, frequency interleaving (FI) technology, quantization interleaving (QI) technology, asynchronous time interleaving (ATI) technology, and digital bandwidth interleaving (DBI) technology to improve the sampling rate, bandwidth and resolution of the acquisition system. However, these interleaving technologies will also introduce non-ideal errors, thereby affecting the acquisition performance. In order to fully utilize the hardware resources to acquire the signals in the effective bandwidth and improve the acquisition accuracy, in recent years, people have begun to study the reconfigurable acquisition architecture. Tektronix adopts reconfigurable technology in the 6 series hybrid domain acquisition system to realize higher acquisition accuracy with smaller sampling rate and analog bandwidth. These reconfigurable technologies realize the reconfiguration of bandwidth and sampling rate in the acquisition system, and improve the acquisition accuracy.

[0004] However, the above-described reconfigurable technology still has several problems. The first problem is that it cannot adaptively match the signal characteristics to realize the automatic configuration of the acquisition system. At present, the acquisition configuration needs to be manually set according to different test scenarios. The second problem is that the adjustment of the system acquisition configuration and the final test result depend on the use proficiency of the test personnel, thereby limiting the acquisition performance. SUMMARY

[0005] The present application aims to overcome the deficiencies of the prior art and provide an adaptive high-precision acquisition method of an intelligent oscilloscope. Based on the spectrum sensing technology, the effective spectrum feature distribution of the signal is extracted, and then the oscilloscope adopts a multi-parameter adaptive matching sampling architecture to realize the adaptive dynamic configuration of bandwidth, sampling rate and resolution. At the same time, adaptive filtering is adopted to refine the out-of-band noise, improve the acquisition accuracy, and facilitate the effective observation of the bandwidth.

[0006] To achieve the above object, the application discloses an adaptive high-precision acquisition method of an intelligent oscilloscope, and has the following steps.

[0007] (1) A signal source generates an input signal and inputs the input signal to the intelligent oscilloscope;

[0008] (2) The input signal is extracted in a real-time effective frequency spectrum range by a sparse Fourier transform loaded in the FPGA in the intelligent oscilloscope, and the effective frequency spectrum feature distribution of the input signal is obtained;

[0009] (3) The type of the input signal is determined according to the effective frequency spectrum feature distribution of the input signal, if the input signal is a wideband signal, step (4) is entered; if the input signal is a sparse signal, step (5) is entered;

[0010] (4) The input signal is collected in a full-bandwidth mode;

[0011] (4.1) The input signal is divided into four sub-band signals, and the bandwidths of the four sub-band signals are 0-6 GHz, 6-11 GHz, 11-16 GHz and 16-20 GHz in sequence;

[0012] (4.2) The frequencies of the analog local oscillator signals corresponding to the four sub-band signals during analog mixing are set as 0 GHz, 11.5 GHz, 10.5 GHz and 14.5 GHz in sequence; the analog local oscillator source generates analog local oscillator signals with the corresponding frequencies, and then the analog local oscillator signals are mixed with the corresponding sub-band signals;

[0013] (4.3) A digital local oscillator signal with the same frequency as the analog local oscillator signal is generated by a tunable numerical control oscillator NCO; then the analog signal after analog mixing is digitally mixed with the digital local oscillator signal, and a difference frequency signal and a sum frequency signal after digital mixing are obtained;

[0014] (4.4) The signal after digital mixing is filtered by an adaptive anti-image filter to remove the difference frequency signal introduced by up-conversion, and then the filtered signal is spliced; the spliced signal is sent to a host computer for display;

[0015] (5) The input signal is collected in an intelligent acquisition mode;

[0016] (5.1) Four sub-bands with bandwidths of 0-6 GHz, 6-11 GHz, 11-16 GHz and 16-20 GHz are set, and each sub-band is configured with four low-pass filters with bandwidths of 500 MHz, 2 GHz, 4 GHz and straight-through;

[0017] (5.2), judging which sub-band the input signal falls into according to the effective spectrum feature distribution of the input signal, then extracting the effective spectrum distribution of the corresponding sub-band, and extracting the effective frequency band interval according to the boundary value of the effective spectrum distribution, and finally reading the lowest frequency f low The analog local oscillator frequency f LO ;

[0018] (5.3), generating an analog local oscillator signal corresponding to the frequency f LO by controlling the clock division ratio of the phase-locked loop, and the analog mixer performs analog mixing on the input signal and the analog local oscillator signal to obtain an intermediate frequency signal;

[0019] (5.4), selecting a low-pass filter with a corresponding bandwidth according to the effective frequency band interval, and performing low-pass filtering on the intermediate frequency signal;

[0020] (5.5), the host computer generates the coefficient of the digital local oscillator according to the analog local oscillator frequency f LO , and then issues it to the adjustable numerical control oscillator NCO; the adjustable numerical control oscillator NCO generates a digital local oscillator signal with the same frequency as the analog local oscillator frequency f LO ;

[0021] (5.6), performing real-time digital mixing on the low-pass filtered signal and the digital local oscillator signal to obtain a digital mixed signal containing the difference frequency signal after digital mixing and the original input signal;

[0022] (5.7), the host computer generates adaptive anti-image filter coefficients according to the spectrum distribution boundary value of the sub-band and the effective frequency band interval, and the local oscillator frequency of the corresponding sub-band, and then issues them to the FPGA; the FPGA generates a real-time adaptive anti-image filter according to the issued coefficients; finally, the real-time adaptive anti-image filter is used to filter out the difference frequency signal after real-time digital mixing and other noise, and the original input signal is retained;

[0023] (5.8), after the signals falling into the sub-band are processed by (5.2)-(5.7), they are sent to the processing board for data splicing, and then the spliced signals are adaptively filtered, and finally sent to the host computer for display.

[0024] The purpose of the present application is achieved as follows:

[0025] The application discloses an adaptive high-precision acquisition method of an intelligent oscilloscope.

[0026] Meanwhile, the adaptive high-precision acquisition method of the intelligent oscilloscope also has the following beneficial effects:

[0027] (1) The acquisition architecture is adaptively configured according to the real-time spectrum characteristics of the to-be-tested signal, while the traditional acquisition system uniformly distributes test resources on the full bandwidth, which means that the signal is collected and processed in the full bandwidth range. Therefore, the average distribution of test resources wastes bandwidth, and the out-of-band noise also reduces the acquisition performance.

[0028] (2) The effective observation bandwidth is automatically configured according to the real-time spectrum characteristics of the to-be-tested signal, the introduced noise is reduced, and the acquisition precision is improved. Compared with the traditional full-bandwidth mode, the application is more flexible, realizes a high hardware resource utilization rate, and can adapt to the problem of insufficient precision of the current variable signal type.

[0029] (3) After the local oscillator is simulated to reduce the signal frequency, more points are collected under the condition of the same ADC resource, the signal is more accurate, the load of the ADC is reduced, digital signal processing is more convenient, and the low-frequency signal is easy to filter and process by using a low-pass filter.

[0030] (4) The real-time adaptive filter is used to filter the out-of-band noise, and the noise is further reduced. Other filtering methods cannot filter the noise of the invalid signal noise band.

[0031] (5) The anti-image filter, the local oscillator signal generated by the analog phase-locked loop and the NCO generated local oscillator signal used in the application are all adaptive and real-time, and are not limited.

[0032] (6) The traditional precision improvement is based on post-processing, and does not have real-time performance. The application can be processed in real time after the signal is input, and the acquisition and processing performance is not reduced. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 It is a flow chart of the adaptive high-precision acquisition method of the intelligent oscilloscope.

[0034] Figure 2 The input signal with noise;

[0035] Figure 3 spectrum of input signal with noise

[0036] Figure 4 intelligently collected signal DETAILED DESCRIPTION

[0037] The specific embodiments of the present application will be described below with reference to the accompanying drawings, so that those skilled in the art can better understand the present application. It should be particularly noted that in the following description, when the detailed description of known functions and designs may obscure the main content of the present application, these descriptions will be omitted here.

[0038] EMBODIMENT

[0039] Figure 1 is a flow chart of an adaptive high-precision acquisition method of an intelligent oscilloscope.

[0040] In this embodiment, as shown in Figure 1 The present application is an adaptive high-precision acquisition method of an intelligent oscilloscope, comprising the following steps:

[0041] (1) The signal source generates an input signal and inputs it to the intelligent oscilloscope;

[0042] (2) In the intelligent oscilloscope, the input signal is extracted in real time in the effective frequency spectrum range by the sparse Fourier transform loaded in the FPGA, and the effective frequency spectrum feature distribution of the input signal is obtained;

[0043] (3) The type of the input signal is determined according to the effective frequency spectrum feature distribution of the input signal, if the input signal is a wideband signal, then step (4) is entered; if the input signal is a sparse signal, then step (5) is entered;

[0044] In this embodiment, after the FPGA obtains the real-time frequency spectrum feature information of the signal, it can determine whether the oscilloscope adopts a full-bandwidth mode or an intelligent acquisition mode using the frequency spectrum feature information, and configure hardware resources according to different modes.

[0045] (4) The input signal is acquired in the full-bandwidth mode;

[0046] (4.1) The input signal is divided into 4 sub-band signals, and the bandwidths of the 4 sub-band signals are 0-6GHz, 6-11GHz, 11-16GHz and 16-20GHz in turn;

[0047] (4.2), the corresponding analog local oscillator signal frequency of the 4 sub-band signals is 0Ghz, 11.5Ghz, 10.5Ghz and 14.5Ghz in turn; the analog local oscillator source generates the analog local oscillator signal of the corresponding frequency, and then performs analog mixing with the corresponding sub-band signal;

[0048] In the embodiment, each sub-band corresponds to an analog local oscillator source, and each analog local oscillator source generates an analog local oscillator signal of a corresponding frequency in the corresponding sub-band, for example, the analog local oscillator source corresponding to the third sub-band generates an analog local oscillator signal of 10.5Ghz;

[0049] (4.3), a digital local oscillator signal with the same frequency as the analog local oscillator signal is generated by an adjustable numerical control oscillator NCO; then the analog signal after analog mixing is digitally mixed with the digital local oscillator signal to obtain a digital mixed signal containing a difference frequency signal and a sum frequency signal;

[0050] (4.4), the signal after digital mixing is filtered by an adaptive anti-image filter to remove the difference frequency signal introduced by up-conversion, and then the filtered signal is spliced, and the spliced signal is sent to the host computer for display;

[0051] (5), the input signal is collected in an intelligent collection mode;

[0052] (5.1), 4 sub-bands with bandwidths of 0-6GHz, 6-11GHz, 11-16GHz and 16-20GHz are set, and each sub-band is configured with four low-pass filters with bandwidths of 20MHz, 1GHz, 2GHz and pass-through;

[0053] (5.2), according to the effective frequency spectrum characteristic distribution of the input signal, it is determined which sub-bands the input signal falls into, then the effective frequency spectrum distribution of the corresponding sub-band is extracted, and according to the boundary value of the effective frequency spectrum distribution, the effective frequency band interval is extracted, and finally the lowest frequency f low of the effective frequency band interval is read; LO

[0054] The calculation method of the analog local oscillator frequency f LO is as follows:

[0055] First, the spectrum characteristics of the input signal are input to determine which sub-bands the input signal falls into, assuming that the spectrum of the input signal falls into the third and fourth sub-bands, then the spectrum distribution of the third and fourth sub-bands is extracted, and according to the boundary value of the spectrum distribution, the effective frequency band interval is extracted, and finally the lowest frequency f low of the effective frequency band interval is read, in the embodiment, the lowest frequency f low ​, respectively 6GHz and 11GHz, and then respectively into the following formula to calculate the third, fourth two sub-band analog local oscillator frequency f LO ;

[0056]

[0057] (5.3), by controlling the clock division ratio of the phase-locked loop to make the analog local oscillator source generate the corresponding frequency f LO analog local oscillator signal, the analog mixer performs analog mixing on the input signal and the analog local oscillator signal to obtain an intermediate frequency signal;

[0058] In this embodiment, for example, the frequency spectrum of the input signal falls into the third and fourth two sub-bands, then the corresponding analog local oscillator frequencies f LO of the third and fourth two sub-bands are calculated according to the frequency f of the input signal, respectively; the corresponding analog local oscillator sources of the third and fourth two sub-bands generate analog local oscillator signals with corresponding frequencies f LO ; then the sub-band signals falling into the third sub-band are analog mixed with the analog local oscillator frequency corresponding to the third sub-band, and similarly, the sub-band signals falling into the fourth sub-band are analog mixed with the analog local oscillator frequency corresponding to the fourth sub-band, and finally the two intermediate frequency signals obtained are processed subsequently;

[0059] (5.4), according to the effective frequency band interval, a low-pass filter with a corresponding bandwidth is selected to ensure that the bandwidth of the low-pass filter can cover the effective frequency band interval and the boundary of the intermediate frequency signal. The intermediate frequency signal is low-pass filtered to filter out high-frequency noise and noise caused by signal conditioning of the channel itself;

[0060] In this embodiment, assuming that the bandwidth of the intermediate frequency signal is Δw, if Δw<500MHz, a 500MHz low-pass filter is selected; if the bandwidth of the intermediate frequency signal is 500MHz<Δw≤2GHz, a 2GHz low-pass filter is selected; if the bandwidth of the intermediate frequency signal is 2GHz<Δw≤4GHz, a 4GHz low-pass filter is selected; if the bandwidth of the intermediate frequency signal is Δw>4GHz, a low-pass filter with a bandwidth of straight through is selected;

[0061] (5.5), the host computer generates the coefficients of the digital local oscillator according to the analog local oscillator frequency f LO , and then issues them to the adjustable numerical control oscillator NCO; the adjustable numerical control oscillator NCO generates a digital local oscillator signal with the same frequency as the analog local oscillator frequency f LO according to the coefficients of the digital local oscillator;

[0062] (5.6), the low-pass filtered signal is real-time digitally mixed with the digital local oscillator signal to obtain a digital mixed difference frequency signal and the original input signal;

[0063] (5.7) The host computer generates adaptive anti-mirror filter coefficients based on the spectral distribution boundary value and effective frequency band range of the sub-band and the local oscillator frequency of the corresponding sub-band, and then sends them down to the FPGA; the FPGA generates a real-time adaptive anti-mirror filter based on the sent coefficients; finally, the real-time adaptive anti-mirror filter is used to filter out the difference frequency signal and other noise after real-time digital mixing, and retains the original input signal.

[0064] (5.8) After processing the signals falling into each sub-band through (5.2) to (5.7), the signals are sent to the processing board for data splicing. The spliced ​​signals are then subjected to digital adaptive filtering and finally sent to the host computer for display.

[0065] In this embodiment, subbands with signal spectrum falling within the band are selected for data stitching, while subbands without signal spectrum falling within the band are turned off and not stitched together to reduce spurious noise. Furthermore, since analog filters cannot further refine the filtering of out-of-band noise within the effective frequency band, a digital adaptive noise suppression filter is needed. This allows for the filtering of noise from invalid signal noise bands using an adaptive bandpass filter.

[0066] Example

[0067] Input a signal with a frequency range of 13.2GHz-13.4GHz and 16.2GHz-16.4GHz to the oscilloscope via a signal source, such as... Figure 2 As shown; the signal spectrum characteristics obtained by the FPGA after sparse Fourier transform are 13.2GHz-13.4GHz and 16.2GHz-16.4GHz, as... Figure 3 As shown, all selections are in intelligent acquisition mode;

[0068] In intelligent acquisition mode, based on the characteristics of the signal spectrum distribution, sub-bands with specific signal spectrum distributions and variable local oscillator values ​​are selected. The signal spectrum characteristics obtained by the FPGA are 13.2GHz-13.4GHz and 16.2GHz-16.4GHz. Because it falls within the 11-16GHz range, it falls into the third sub-band; because it falls within the 16-20GHz range, it falls into the fourth sub-band. The calculated local oscillator frequencies for the third sub-band are 13.2GHz and for the fourth sub-band are 16.2GHz. Since the effective bandwidth of the signal is Δw = 200MHz, a low-pass filter with a bandwidth of 500MHz is selected.

[0069] Then, the intermediate frequency signal is passed through an analog low-pass filter with a passband cutoff frequency of 500MHz to filter out high-frequency noise and noise caused by signal conditioning in the channel itself;

[0070] Subsequently, the filtered analog signal is fed to the ADC. The signal is reconstructed on the FPGA. Digital up-conversion is achieved by multiplying the intermediate frequency signal with a digital local oscillator. The frequency of the digital local oscillator is generated by a numerically controlled oscillator (NCO) whose coefficients are generated by the host computer and downloaded to the digital hardware. After storage, the NCO reads the coefficients and generates the signal. The third sub-band local oscillator signal is 13.2 GHz and the fourth sub-band local oscillator signal is 16.2 GHz. LO The same digital local oscillator signal; the coefficients of the digital local oscillator are generated by the host computer and downloaded to the digital hardware. After storage, the numerically controlled oscillator (NCO) reads the coefficients and generates the signal. The third sub-band local oscillator signal is 13.2 GHz and the fourth sub-band local oscillator signal is 16.2 GHz.

[0071] According to the boundary values 13.2 GHz, 13.4 GHz, 16.2 GHz, 16.4 GHz and the LO values, i.e. the third sub-band local oscillator signal is 13.2 GHz and the fourth sub-band local oscillator signal is 16.2 GHz, and the effective frequency band interval 200 MHz, the host computer designs and generates adaptive anti-image filter coefficients, which are downloaded to the FPGA, stored, and then read and generated to generate a real-time adaptive anti-image filter. The real-time adaptive anti-image filter filters out the difference frequency signal after digital mixing, retains the original input signal and filters out other noise. The filtered signal is sent to the processing board for data splicing. Sub-band selection is performed to select the sub-band where the signal spectrum falls for data splicing, and the sub-band where the signal spectrum does not fall is closed and does not perform data splicing to reduce stray noise. Since the analog filter cannot further refine the effective frequency band out-of-band noise, a digital adaptive noise suppression filter is needed. The adaptive bandpass filter filters out the invalid signal noise band, i.e. the noise of 13.4 GHz-16.2 GHz, to obtain Figure 4 The collected signal is shown in the host computer and then sent to the host computer for display.

[0072] Although the above describes the specific embodiments of the present application in order to facilitate the understanding of the present application by those skilled in the art, it should be clear that the present application is not limited to the scope of the specific embodiments, and for those skilled in the art, it is obvious that various changes are within the spirit and scope of the present application defined and determined by the appended claims, and all inventions utilizing the concept of the present application are within the scope of protection.

Claims

1. An adaptive high-precision acquisition method for an intelligent oscilloscope, characterized in that, Includes the following steps: (1) The signal source generates the input signal and inputs it into the smart oscilloscope; (2) In the intelligent oscilloscope, the effective spectrum range of the input signal is extracted in real time by the sparse Fourier transform loaded in the FPGA to obtain the effective spectrum feature distribution of the input signal; (3) Determine the type of input signal based on the effective spectral characteristics of the input signal. If the input signal is a wideband signal, proceed to step (4); if the input signal is a sparse signal, proceed to step (5). (4) Acquire the input signal in full bandwidth mode; (4.1) Divide the input signal into 4 sub-band signals; (4.2) Set the frequency of the analog local oscillator signal corresponding to the four sub-band signals when performing analog mixing. The analog local oscillator source generates the analog local oscillator signal of the corresponding frequency, and then performs analog mixing with the corresponding sub-band signal. (4.3) A digital local oscillator signal with the same frequency as the analog local oscillator signal is generated by an adjustable numerically controlled oscillator (NCO); then the analog signal after analog mixing is digitally mixed with the digital local oscillator signal to obtain the difference frequency signal and the sum frequency signal after digital mixing. (4.4) The signal after digital mixing is filtered out by an adaptive anti-mirror filter to remove the difference frequency signal introduced by the up-conversion, and then the filtered signal is combined and sent to the host computer for display. (5) The input signal is acquired in intelligent acquisition mode; (5.1) Set up 4 sub-bands, each of which is equipped with four low-pass filters with bandwidths of 500MHz, 2GHz, 4GHz and pass-through; (5.2) Determine which sub-bands the input signal falls into based on the effective spectral characteristic distribution of the input signal, then extract the effective spectral distribution of the corresponding sub-band, and extract the effective frequency band interval based on the boundary values ​​of the effective spectral distribution. Finally, read the lowest frequency of the effective frequency band interval. Calculate the simulated local oscillator frequency ; (5.3) By controlling the clock division ratio of the phase-locked loop, the analog local oscillator generates the corresponding frequency f. LO The analog local oscillator signal is used to perform analog mixing between the input signal and the analog local oscillator signal to obtain the intermediate frequency signal. (5.4) Select a low-pass filter with the corresponding bandwidth according to the effective frequency band range, and perform low-pass filtering on the intermediate frequency signal; (5.5) The host computer calculates the simulated local oscillator frequency. The coefficients of the digital local oscillator are generated and then sent to the adjustable numerically controlled oscillator (NCO). The adjustable numerically controlled oscillator (NCO) generates a frequency based on the coefficients of the digital local oscillator and the analog local oscillator frequency f. LO The same digital local oscillator signal; (5.6) The low-pass filtered signal is digitally mixed with the digital local oscillator signal in real time to obtain the difference frequency signal containing the digitally mixed signal and the original input signal; (5.7) The host computer generates adaptive anti-mirror filter coefficients based on the spectral distribution boundary value and effective frequency band range of the sub-band and the local oscillator frequency of the corresponding sub-band, and then sends them to the FPGA; the FPGA generates a real-time adaptive anti-mirror filter based on the sent coefficients; finally, the real-time adaptive anti-mirror filter is used to filter out the difference frequency signal and other noise after real-time digital mixing, and retains the original input signal. (5.8) After processing the signals falling into each sub-band through (5.2)~(5.7), the signals are sent to the processing board for data splicing, and then the spliced ​​signals are subjected to adaptive filtering and finally sent to the host computer for display.

2. The adaptive high-precision acquisition method for an intelligent oscilloscope according to claim 1, characterized in that, The simulated local oscillator frequency f LO The calculation method is as follows: 。

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