Accelerated Scanning Method for EMI Receivers Based on Time-Domain Envelope Reconstruction

Abstract

This invention provides an accelerated scanning method for EMI receivers based on time-domain envelope reconstruction, belonging to the field of electromagnetic compatibility testing technology. The method includes: (1) dividing the scanning segment; (2) broadband time-domain signal acquisition; (3) high overlap rate short-time Fourier transform; (4) inverse short-time Fourier transform or overlapping addition; (5) performing digital detection; (6) system calibration compensation; and (7) spectrum splicing. This invention provides an accelerated scanning method for EMI receivers based on time-domain envelope reconstruction, aiming to solve the following technical problems existing in the time-domain scanning technology of EMI receivers: in measurements that require time-domain envelope information, such as quasi-peak detection, the accuracy of existing frequency domain approximation methods is insufficient; the detection accuracy of pulse signals, especially low repetition frequency pulse signals, is not high; information loss or introduction of spurious peaks due to edge effects during spectrum splicing; and the lack of ability to adaptively adjust scanning parameters according to signal characteristics.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic compatibility testing technology, and in particular to an accelerated scanning method for EMI receivers based on time-domain envelope reconstruction. Background Technology

[0002] Electromagnetic interference (EMI) receivers are core equipment in electromagnetic compatibility testing, used to measure conducted and radiated emissions generated by electronic devices. Traditional EMI receivers employ a stepped frequency scanning method, sequentially tuning the local oscillator, waiting for the filter to build up, performing detection measurements at each test frequency, and then moving to the next frequency. This sequential measurement method has the following technical problems:

[0003] (1) Low measurement efficiency: For measurements that require long dwell time, such as quasi-peak detection, each frequency point needs to stay for more than 1 second, and it takes several hours or even tens of hours to complete the full-band scan (such as 30MHz-1GHz).

[0004] (2) Risk of missing transient signals: In sequential scanning mode, if the pulse signal appears at a frequency point that has not yet been scanned by the local oscillator, the signal will be completely missed and cannot be detected.

[0005] (3) Strong hardware dependence: The measurement accuracy of traditional methods is highly dependent on the stability and consistency of analog filters, the equipment calibration is complicated, and the temperature drift has a great impact.

[0006] (4) Insufficient flexibility: The hardware RBW filter bank is fixed and cannot flexibly adjust the filter characteristics according to test requirements.

[0007] In recent years, time-domain scanning techniques based on Fast Fourier Transform have emerged, improving measurement speed through broadband acquisition and parallel processing. However, existing techniques typically employ frequency-domain amplitude sequence approximation when handling measurements requiring time-domain envelope information, such as quasi-peak detection, linear average detection, and root-mean-square average detection. This leads to a decrease in measurement accuracy for low-repetition-frequency pulse signals, making it difficult to meet compliance requirements of standards such as CISPR. Summary of the Invention

[0008] This invention provides an accelerated scanning method for EMI receivers based on time-domain envelope reconstruction, aiming to solve the following technical problems existing in the time-domain scanning technology of EMI receivers: the accuracy of existing frequency domain approximation methods is insufficient in measurements that require time-domain envelope information, such as quasi-peak detection; the detection accuracy of pulse signals, especially low repetition frequency pulse signals, is not high; information loss or spurious peaks are introduced due to edge effects during spectrum splicing; and there is a lack of ability to adaptively adjust scanning parameters according to signal characteristics.

[0009] To achieve the above objectives, the present invention adopts the following technical solution:

[0010] An accelerated scanning method for EMI receivers based on time-domain envelope reconstruction includes:

[0011] (1) Based on the user-defined start frequency, end frequency, target resolution bandwidth and detector type, divide the entire frequency band into several scanning segments and determine the center frequency of each scanning segment;

[0012] (2) For each scan segment, tune the preselected filter and the local oscillator frequency, perform broadband time-domain signal acquisition, and obtain the complex baseband signal of the scan segment;

[0013] (3) Perform a high overlap rate short-time Fourier transform on the complex baseband signal to obtain the instantaneous spectrum of each time frame, wherein the instantaneous spectrum contains complex information of each frequency point;

[0014] (4) For each frequency point, extract the complex sequence of the frequency point from the instantaneous spectrum of all time frames, perform inverse short-time Fourier transform or overlap and addition on the complex sequence, and reconstruct the time-domain envelope signal of the frequency point.

[0015] (5) Based on the detector type selected by the user, perform digital detection processing on the reconstructed time-domain envelope signal to obtain the measurement results of the frequency points;

[0016] (6) Apply system calibration compensation to the measurement results at all frequency points to obtain calibrated measurement results;

[0017] (7) The calibrated measurement results of all scanning segments are spliced ​​together to generate a complete continuous spectrum from the start frequency to the end frequency.

[0018] In this specification, in step (2), for quasi-peak detection, linear average detection, or root mean square average detection, the acquisition time of the broadband time-domain signal acquisition is greater than or equal to the dwell time specified in the CISPR standard.

[0019] In this specification, the complex baseband signal obtained in step (2) is obtained by performing digital downconversion and anti-aliasing filtering on the acquired time-domain signal to obtain the complex baseband signal; the instantaneous spectrum of each time frame in step (3) is obtained by mapping the baseband frequency to the radio frequency.

[0020] In this specification, the overlap rate of the high overlap rate short-time Fourier transform in step (3) is greater than or equal to 90%; the frame length of the fast Fourier transform is determined according to the target resolution bandwidth so that the equivalent resolution bandwidth is equal to the target resolution bandwidth; the fast Fourier transform is then performed after applying a window function to the data of each frame for weighting.

[0021] In this specification, when performing inverse short-time Fourier transform or overlap-add processing on the complex sequence at each frequency point in step (4), the amplitude information and phase information of the complex sequence are used simultaneously to reconstruct the time-domain envelope signal containing amplitude changes over time.

[0022] In this specification, the digital detection processing in step (5) includes:

[0023] If the detector type selected by the user is quasi-peak detection, the charging time constant, discharging time constant and mechanical time constant defined by the CISPR standard are applied to perform quasi-peak detection simulation on the reconstructed time-domain envelope signal to obtain quasi-peak measurement results;

[0024] If the user selects peak detection as the detector type, the maximum value of the reconstructed time-domain envelope signal during the entire acquisition time is calculated to obtain the peak measurement result.

[0025] If the detector type selected by the user is linear average detection, the arithmetic mean of the reconstructed time-domain envelope signal is calculated to obtain the linear average measurement result.

[0026] If the user selects the root mean square (RMS) average detector type, the RMS value of the reconstructed time-domain envelope signal is calculated to obtain the RMS average measurement result.

[0027] In this specification, the system calibration compensation in step (6) includes:

[0028] Based on the pre-stored system frequency response calibration curve, amplitude correction is performed on the measurement results at each frequency point;

[0029] Based on the difference between the actual resolution bandwidth and the target resolution bandwidth, a normalization correction is performed using an equivalent noise bandwidth correction factor.

[0030] Temperature compensation is performed based on real-time temperature sensor data and a temperature drift compensation coefficient.

[0031] In this specification, the spectrum splicing in step (7) specifically includes: identifying the overlapping frequency region between adjacent scan segments, designing a trapezoidal weighting function, performing weighted averaging on the calibrated measurement results of the two adjacent segments in the overlapping region, and then connecting all the processed data of the scan segments in frequency order.

[0032] In this specification, after processing one scan segment, the acquisition parameters for the next scan segment are dynamically adjusted based on the real-time signal characteristics of the current scan segment; the dynamic adjustment includes:

[0033] Calculate the signal density of the current scan segment, where the signal density is the proportion of the number of frequency points whose measured value exceeds the noise floor plus 6 dB to the total number of frequency points in the current scan segment;

[0034] If the signal density is lower than the first threshold, the acquisition bandwidth of the fast Fourier transform is reduced in the next scan segment.

[0035] If the signal density is higher than the second threshold, the overlap rate of the short-time Fourier transform will be increased to over 95% in the next scan segment.

[0036] If a large number of pulse signals are detected, the model parameters of the quasi-peak detector are dynamically adjusted.

[0037] In this specification, the first threshold is 5%, and the second threshold is 30%; the reduction in the acquisition bandwidth increases the frequency resolution.

[0038] In summary, the present invention has at least the following beneficial effects:

[0039] (1) Improve the measurement accuracy of pulse signals: By reconstructing the time domain envelope of each frequency point from the STFFT results and performing quasi-peak detection simulation on the envelope, the problem of inaccurate measurement of low PRF pulses by the traditional frequency domain approximation method is overcome, and the measurement accuracy is improved by more than 30%.

[0040] (2) Ensure standard compliance: The reconstructed time domain envelope can be directly detected using the time constant defined by the CISPR standard, ensuring that the measurement results are consistent with those of traditional step-scan receivers and meeting the requirements of CISPR16-1-1 and other standards.

[0041] (3) Significantly improve scanning speed: Under the premise of meeting the quasi-peak detection dwell time requirement of 1 second, the scanning speed is increased by 100-1000 times compared with the traditional step scanning through broadband parallel processing, and the QP measurement time of the 30MHz-1GHz full-band is shortened from several hours to tens of seconds.

[0042] (4) Improve transient signal capture capability: High overlap rate (≥90%) ensures that the pulse signal can be completely captured by at least one FFT frame no matter where it appears on the time axis, with a capture probability close to 100%.

[0043] (5) Good spectrum continuity: By weighted averaging of overlapping regions, the edge effect between segments is eliminated, avoiding false peaks or information loss introduced by spectrum splicing, and the spectrum continuity error is less than 0.5dB.

[0044] (6) Adaptive optimization improves efficiency: The scanning parameters are dynamically adjusted according to the signal density and characteristics, and the scanning speed is further optimized while ensuring measurement accuracy, resulting in an overall efficiency improvement of 20-50%. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a schematic diagram of the EMI receiver accelerated scanning method based on time-domain envelope reconstruction involved in this invention.

[0047] Figure 2 This is a schematic diagram of the high overlap rate STFFT processing involved in this invention.

[0048] Figure 3 This is a schematic diagram of the time-domain envelope reconstruction and parallel detection processing involved in this invention. Detailed Implementation

[0049] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the embodiments of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0050] The following disclosure provides many different implementations or examples for carrying out different structures of the embodiments of the present invention. To simplify the disclosure of the embodiments of the present invention, specific examples of components and arrangements are described below. Of course, these are merely examples and are not intended to limit the embodiments of the present invention. Furthermore, reference numerals and / or reference letters may be repeated in different examples of the embodiments of the present invention; such repetition is for simplification and clarity and does not in itself indicate a relationship between the various implementations and / or arrangements discussed.

[0051] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0052] like Figure 1 As shown, this embodiment provides an accelerated scanning method for EMI receivers based on time-domain envelope reconstruction, including:

[0053] (1) Based on the user-defined start frequency, end frequency, target resolution bandwidth and detector type, divide the entire frequency band into several scanning segments and determine the center frequency of each scanning segment;

[0054] (2) For each scan segment, tune the preselected filter and the local oscillator frequency, perform broadband time-domain signal acquisition, and obtain the complex baseband signal of the scan segment;

[0055] (3) Perform a high overlap rate short-time Fourier transform on the complex baseband signal to obtain the instantaneous spectrum of each time frame, wherein the instantaneous spectrum contains complex information of each frequency point;

[0056] (4) For each frequency point, extract the complex sequence of the frequency point from the instantaneous spectrum of all time frames, perform inverse short-time Fourier transform or overlap and addition on the complex sequence, and reconstruct the time-domain envelope signal of the frequency point.

[0057] (5) Based on the detector type selected by the user, perform digital detection processing on the reconstructed time-domain envelope signal to obtain the measurement results of the frequency points;

[0058] (6) Apply system calibration compensation to the measurement results at all frequency points to obtain calibrated measurement results;

[0059] (7) The calibrated measurement results of all scanning segments are spliced ​​together to generate a complete continuous spectrum from the start frequency to the end frequency.

[0060] In some embodiments, in step (2), for quasi-peak detection, linear average detection, or root mean square average detection, the acquisition time of the broadband time-domain signal acquisition is greater than or equal to the dwell time specified in the CISPR standard.

[0061] In some embodiments, the complex baseband signal obtained in step (2) is obtained by performing digital down-conversion and anti-aliasing filtering on the acquired time-domain signal to obtain the complex baseband signal; the instantaneous spectrum of each time frame in step (3) is obtained by mapping the baseband frequency to the radio frequency.

[0062] In some embodiments, the overlap rate of the high overlap rate short-time Fourier transform in step (3) is greater than or equal to 90%; the frame length of the fast Fourier transform is determined according to the target resolution bandwidth, so that the equivalent resolution bandwidth is equal to the target resolution bandwidth; the fast Fourier transform is then performed after applying a window function to the data of each frame for weighting.

[0063] In some embodiments, when performing inverse short-time Fourier transform or overlap-add processing on the complex sequence at each frequency point in step (4), the amplitude information and phase information of the complex sequence are used simultaneously to reconstruct the time-domain envelope signal containing amplitude changes over time.

[0064] In some embodiments, the digital detection processing in step (5) includes:

[0065] If the detector type selected by the user is quasi-peak detection, the charging time constant, discharging time constant and mechanical time constant defined by the CISPR standard are applied to perform quasi-peak detection simulation on the reconstructed time-domain envelope signal to obtain quasi-peak measurement results;

[0066] If the user selects peak detection as the detector type, the maximum value of the reconstructed time-domain envelope signal during the entire acquisition time is calculated to obtain the peak measurement result.

[0067] If the detector type selected by the user is linear average detection, the arithmetic mean of the reconstructed time-domain envelope signal is calculated to obtain the linear average measurement result.

[0068] If the user selects the root mean square (RMS) average detector type, the RMS value of the reconstructed time-domain envelope signal is calculated to obtain the RMS average measurement result.

[0069] In some embodiments, the system calibration compensation in step (6) includes:

[0070] Based on the pre-stored system frequency response calibration curve, amplitude correction is performed on the measurement results at each frequency point;

[0071] Based on the difference between the actual resolution bandwidth and the target resolution bandwidth, a normalization correction is performed using an equivalent noise bandwidth correction factor.

[0072] Temperature compensation is performed based on real-time temperature sensor data and a temperature drift compensation coefficient.

[0073] In some embodiments, the spectrum splicing in step (7) specifically includes: identifying the overlapping frequency region between adjacent scan segments, designing a trapezoidal weighting function, performing weighted averaging on the calibrated measurement results of the two adjacent segments in the overlapping region, and then connecting the processed data of all scan segments in frequency order.

[0074] In some embodiments, after processing a scan segment, the acquisition parameters for the next scan segment are dynamically adjusted based on the real-time signal characteristics of the current scan segment; the dynamic adjustment includes:

[0075] Calculate the signal density of the current scan segment, where the signal density is the proportion of the number of frequency points whose measured value exceeds the noise floor plus 6 dB to the total number of frequency points in the current scan segment;

[0076] If the signal density is lower than the first threshold, the acquisition bandwidth of the fast Fourier transform is reduced in the next scan segment.

[0077] If the signal density is higher than the second threshold, the overlap rate of the short-time Fourier transform will be increased to over 95% in the next scan segment.

[0078] If a large number of pulse signals are detected, the model parameters of the quasi-peak detector are dynamically adjusted.

[0079] In some embodiments, the first threshold is 5% and the second threshold is 30%; the reduction in acquisition bandwidth increases the frequency resolution.

[0080] The technical concept of this invention is as follows:

[0081] An accelerated scanning method for EMI receivers based on time-domain envelope reconstruction includes: dividing the frequency band according to user-defined scanning parameters and determining the center frequency of each scanning segment; acquiring a broadband time-domain signal for each scanning segment to obtain a complex baseband signal; performing a high-overlap-rate short-time Fourier transform on the complex baseband signal to obtain the instantaneous spectrum of each time frame; for each frequency point, extracting a complex sequence from the instantaneous spectrum of all time frames to reconstruct the time-domain envelope signal of that frequency point, and performing digital detection processing on the reconstructed time-domain envelope to obtain the measurement result of that frequency point; applying system calibration compensation to the measurement results of all frequency points; stitching together the spectrum of the measurement results of all scanning segments to generate a complete continuous spectrum; and outputting the final spectrum.

[0082] (1) Based on the user-defined starting frequency Termination frequency Target resolution bandwidth Calculate the total scan bandwidth based on the detector type. And based on the FFT acquisition bandwidth Determine the number of scan segments Generate the center frequency of each segment , This indicates the total number of scanning segments (i.e., the number of segments) in the entire frequency band.

[0083] (2) For each scan segment, perform the following sub-steps:

[0084] Tuning the preselection filter to the center frequency of the current segment And set the local oscillator frequency to downconvert this frequency band to baseband;

[0085] Start the high-speed analog-to-digital converter at the sampling rate. Continuous acquisition of time-domain signals, acquisition time The determination is based on the detector type and dwell time requirements, for quasi-peak detection, linear average detection, and root mean square-average detection. ≥CISPR-specified dwell time (usually greater than 1 second);

[0086] The acquired time-domain signal is digitally down-converted and subjected to anti-aliasing filtering to obtain a complex baseband signal. , length is .

[0087] (3) For complex baseband signals Perform a high overlap rate short-time Fourier transform:

[0088] Determine the FFT frame length This makes the equivalent resolution bandwidth ,in The equivalent noise bandwidth factor for the window function;

[0089] Given frame overlap rate And determine the frame shift step size. and total number of frames ;

[0090] Apply window functions (Preferred Kaiser window, β value optimized based on target shape factor) Weighting of each frame of data;

[0091] Perform an FFT transform on each windowed frame of data to obtain the first frame. Instantaneous spectrum of a frame ,in For frequency index, Corresponding baseband frequency ;

[0092] Mapping baseband frequency to radio frequency: .

[0093] See also Figure 2 Processing diagram.

[0094] (4) For each frequency point Perform the following sub-steps to reconstruct its temporal envelope and perform detection:

[0095] Extract the complex sequence of the frequency point from the instantaneous spectrum of all frames. ;

[0096] The time-domain envelope signal at this frequency point can be reconstructed by performing an inverse short-time Fourier transform on the complex sequence or by using an overlap-add algorithm. ;

[0097] Depending on the detector type selected by the user, the time-domain envelope signal Execute the corresponding digital detection algorithm:

[0098] For peak detection: Calculate Maximum value during the entire acquisition time .

[0099] For quasi-peak detection: apply the charging time constant T1 (1ms), discharging time constant T2 (160ms), and mechanical time constant Tm (160ms) defined by the CISPR standard, to... Quasi-peak detection simulation was performed to obtain : Quasi-peak detection result (quasi-peak measurement value) at the k-th frequency point.

[0100] For linear average value detection: calculate arithmetic mean .

[0101] If RMS average value detection is used: Calculate root mean square value .

[0102] For all frequency points The above detection process is executed in parallel to obtain the measurement results of all frequency points within this segment.

[0103] See also Figure 3 Processing diagram.

[0104] (5) Apply system calibration to the measurement results obtained in step (4):

[0105] Frequency response compensation: based on the pre-stored system frequency response calibration curve. Amplitude correction is performed on the measurement results at each frequency point;

[0106] RBW calibration: Normalization correction is performed based on the difference between the actual RBW and the target RBW, especially for noise and impulse signals, applying the ENBW correction factor;

[0107] Temperature compensation: Apply a temperature drift compensation coefficient based on real-time temperature sensor data.

[0108] (6) After processing all scan segments, perform spectrum stitching:

[0109] Identify the overlapping frequency regions and overlap widths between adjacent segments. ,when hour;

[0110] Design a trapezoidal weighting function In the segment edge region, the weight decreases linearly from 1 to 0, and the weights in the overlapping region sum to 1;

[0111] For each frequency point in the overlapping region, the measurement results of the two adjacent segments are weighted and averaged according to the weighting function;

[0112] After processing all segments, the data is concatenated in frequency order to generate a sequence from... arrive The complete continuous spectrum.

[0113] (7) Dynamically adjust the scanning parameters according to the real-time signal characteristics:

[0114] Signal density estimation: Calculate the frequency occupancy rate of the current segment, that is, the proportion of frequency points whose measured value exceeds the noise floor by 6dB.

[0115] If the signal density is below the threshold If the FFT acquisition bandwidth is reduced to 5% in the next segment, the frequency resolution will be increased.

[0116] If the signal density is higher than the threshold If the overlap rate is 30%, then the overlap rate should be appropriately increased to over 95% in the next segment to enhance the pulse capture capability.

[0117] If a large number of pulse signals are detected, the model parameters of the quasi-peak detector are dynamically adjusted to optimize the response speed.

[0118] In some embodiments, the specific implementation of step (4) of "performing inverse short-time Fourier transform or overlapping addition processing on the complex sequence to reconstruct the time-domain envelope signal of the frequency point" is as follows:

[0119] Solution A: Reconstruction based on Inverse Short-Time Fourier Transform (ISTFT):

[0120] For the The complex sequence of frequency points is as follows: ,in This represents the total number of frames in the short-time Fourier transform during step (3). Reconstruct the time-domain envelope signal at this frequency point. Includes the following sub-steps:

[0121] (A1) The construction length is complex vectors ;

[0122] (A2) implement Point-wise inverse fast Fourier transform (IFFT) yields a complex time-domain sequence. , :

[0123] ;

[0124] (A3) Take The magnitude of the signal is used to obtain the time-discrete envelope signal at that frequency point:

[0125] ;

[0126] (A4) Based on the frame shift step size in step (3) and sampling rate Discrete envelope Mapped to the actual timeline, i.e. ,in This is for rounding down.

[0127] Option B: Reconstruction based on Overlapping Addition (OLA):

[0128] For the The time-domain envelope signal of each frequency point is reconstructed using the overlap-addition method. The specific steps are as follows:

[0129] (B1) Obtain the frame shift step size of the short-time Fourier transform in step (3). Window function (length is) );

[0130] (B2) For each frame ( ) complex number Construct a length of The frequency domain vector, where the first... The value at each frequency point is The remaining frequency points are zero, then execute. Point IFFT yields the temporal contribution of the frame. , :

[0131] The inverse transform at a single frequency point is simplified to a complex exponent;

[0132] In fact, since there is only one non-zero frequency point, the inverse transform result is:

[0133] ;

[0134] (B3) Multiply by window function Perform weighted adjustments;

[0135] (B4) The temporal contribution of all frames is calculated according to the frame shift step size. Superposition yields the complete time-domain complex sequence:

[0136] ;

[0137] (B5) Take The modulus value is used to obtain the discrete envelope. Then, it is mapped to a continuous-time envelope according to the sampling rate. .

[0138] Of the two schemes above, scheme A involves less computation and is suitable for real-time processing; scheme B has higher accuracy and is suitable for offline high-precision measurement.

[0139] In some embodiments, the "overlap width" mentioned in step (6) The derivation process of “” is as follows:

[0140] Let the full frequency range be Total bandwidth Divide the entire frequency band into There are 1 scan segment, and the FFT acquisition bandwidth of each scan segment is 1. (That is, the frequency width covered by a single broadband acquisition). To ensure seamless coverage and inter-segment overlap, the center frequency of each segment... satisfy:

[0141] ;

[0142] The center frequency spacing between adjacent segments is The overlap width is defined as the intersection length of the frequency coverage ranges of adjacent segments, i.e.:

[0143] ;

[0144] because Organized This formula ensures that: when hour, ;when As the overlap width increases, it approaches the value of the previous value. This ensures a smooth transition between segments. The trapezoidal weighting function ensures that the sum of the measurement weights in the overlapping area is always 1, effectively suppressing edge effects.

[0145] In some embodiments, the calculation and application method of the "Equivalent Noise Bandwidth (ENBW) Correction Factor" is as follows:

[0146] Let the sequence of window functions used in step (3) be... , Then ENBW correction factor Defined as:

[0147] ;

[0148] For white noise signals, the power spectral density needs to be divided by . To correct noise power; for pulse signals, the amplitude correction factor is... Specifically, for the measurement results at each frequency point in step (5) (Amplitude squared value), corrected amplitude for:

[0149] , corresponding to pulse signal; , corresponding to noise signal;

[0150] Preferably, the Kaiser window is selected. )hour, When using Hanning windows, In this embodiment, the window function type is automatically calculated. The value is then applied to the calibration.

[0151] In some embodiments, the specific implementation methods of "detecting a large number of pulse signals" and "dynamically adjusting the model parameters of the quasi-peak detector" are as follows:

[0152] (a) Detection method for a large number of pulse signals:

[0153] The time-domain envelope signal reconstructed from the current scan segment ( (For the frequency point index), calculate the derivative of its amplitude. The derivative exceeds a positive threshold per unit time. The number of rising edges. If the average rising edge density across all frequency points... If the signal count is 10 times per second, it is considered a "large number of pulse signals".

[0154] Alternatively, a frequency domain method can be used: calculate the spectral flatness of the current scan segment's spectrum. ,in For the first Power at each frequency point. If This indicates that the spectrum has obvious pulse characteristics, and it is determined to be a large number of pulse signals.

[0155] (b) Dynamic adjustment of quasi-peak detector model parameters:

[0156] The digital model of the quasi-peak detector is based on a first-order RC charging and discharging circuit, and its state update equation is:

[0157] ;

[0158] in The sampling period is The charging time constant. This is the discharge time constant. Standard CISPR 16-1-1 specifies... ms, ms (corresponding to the product of discharge resistance and capacitance).

[0159] When a large number of pulse signals are detected, the dynamic adjustment strategy is as follows:

[0160] Adjust the charging time constant to The upper limit is ms;

[0161] Adjust the discharge time constant to The lower limit is ms;

[0162] Mechanical time constant (The damping of the indicator head) remains unchanged, still being... ms.

[0163] This adjustment enables the quasi-peak detector to respond faster under fast pulse trains, avoiding saturation distortion, while still meeting the basic requirements of CISPR for pulse response characteristics.

[0164] In some embodiments, in order to eliminate the envelope reconstruction error introduced by the window function and overlap processing, a phase-preserving compensation factor is further applied after performing the inverse short-time Fourier transform or overlap-addition reconstruction in step (4). This factor is calculated based on the phase consistency of the instantaneous spectrum of each frame in step (3):

[0165] ;

[0166] in This represents the inter-frame time difference. The reconstructed temporal envelope signal is corrected as follows:

[0167] ;

[0168] in This is the average of the phase change rate across all frequency points. The preset compensation strength coefficient (range 0.5~1.5) effectively suppresses the pseudo-modulation distortion introduced by STFFT overlap processing, reducing the root mean square error between the reconstructed envelope and the real time-domain envelope by more than 20%.

[0169] In some embodiments, the window function in step (3) is a Kaiser window, whose shape parameters are... It is not fixed, but rather adaptively determined based on the dynamic characteristics of the signal in the current scan segment. The specific method is as follows:

[0170] Calculate the complex baseband signal of the current scan segment peak average .

[0171] like dB (high-pulsivity signal), select To achieve higher sidelobe attenuation (>100dB) and suppress pulse spectrum leakage.

[0172] like dB (noise-like signal), selection This reduces the main lobe width and improves frequency resolution.

[0173] In other cases, select .

[0174] The time-domain expression for the Kaiser window is:

[0175] ;

[0176] in This is a modified zero-order Bessel function of the first kind. This adaptive window function selection method significantly enhances the adaptability of STFFT to different signals while maintaining a high overlap rate.

[0177] In some embodiments, the overlap rate in step (3) It is not fixed at ≥90%, but rather dynamically calculated based on the pulse density and spectral change rate of the current scan segment. The optimization function is defined as:

[0178] ;

[0179] The number of pulses detected per unit time (the detection method can be found in the above embodiments); This represents the total number of STFFT frames.

[0180] The average rate of change of the spectrum over time is calculated from the Euclidean distance between the instantaneous spectra of adjacent frames.

[0181] When pulses are dense or the spectrum changes rapidly, the overlap rate automatically increases to 98% or even 99% to ensure that transient signals are not lost; when the signal is stable, the overlap rate is maintained at 90% to save computational resources. This dynamic optimization function achieves an optimal balance between scanning speed and pulse acquisition probability.

[0182] In some embodiments, before performing step (7) spectral stitching, energy normalization calibration is performed on the overlapping region of adjacent scan segments to eliminate inter-segment amplitude jumps caused by inconsistencies in the amplitude-frequency response of the preselected filter or local oscillator phase noise. Specific method:

[0183] Set scan segment and In the overlapping frequency region The measurement results are as follows: and Calculate the energy ratio:

[0184] ;

[0185] like If the deviation from 1 exceeds a preset threshold (e.g., 5%), then the first... Multiply all measurement results of the segment by a correction factor (Voltage domain) or (Power domain) to ensure consistent average energy across overlapping regions. This energy normalization step, performed before trapezoidal weighted averaging, further reduces spectral continuity error from 0.5 dB to within 0.1 dB.

[0186] The embodiments described above are for illustrative purposes only and are not intended to limit the invention. Therefore, any changes in numerical values ​​or substitutions of equivalent elements should still fall within the scope of this invention.

[0187] The above detailed description will enable those skilled in the art to understand that the present invention can indeed achieve the aforementioned objectives and has complied with the provisions of the Patent Law.

[0188] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention. The above descriptions are merely preferred embodiments of the invention and are not intended to limit the invention. It should be noted that any modifications, equivalent substitutions, and improvements made within the spirit and principles of the invention should be included within the scope of protection of the invention.

[0189] It should be noted that the above description of the process is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to the process under the guidance of this specification. However, these modifications and changes remain within the scope of this specification.

[0190] The basic concepts have been described above. Obviously, for those skilled in the art who have read this application, the above disclosure is merely illustrative and does not constitute a limitation of this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are suggested in this application, and therefore, such modifications, improvements, and corrections still fall within the spirit and scope of the exemplary embodiments of this application.

[0191] Furthermore, this application uses specific terms to describe its embodiments. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of this application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different positions in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this application can be appropriately combined.

[0192] Furthermore, those skilled in the art will understand that aspects of this application can be described and illustrated through several patentable types or situations, including any new and useful combination of processes, machines, products, or substances, or any new and useful improvements thereof. Therefore, aspects of this application can be implemented entirely in hardware, entirely in software (including firmware, resident software, microcode, etc.), or a combination of hardware and software. All of the above hardware or software can be referred to as a “unit,” “module,” or “system.” Furthermore, aspects of this application can take the form of a computer program product embodied in one or more computer-readable media, wherein computer-readable program code is contained therein.

[0193] The computer program code required for the operation of each part of this application can be written in any one or more programming languages, including object-oriented programming languages ​​such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, and Python; general programming languages ​​such as C; Visual Basic, Fortran2103, Perl, COBOL2102, PHP, and ABAP; dynamic programming languages ​​such as Python, Ruby, and Groovy; or other programming languages. This program code can run entirely on the user's computer, or as a standalone software package on the user's computer, or partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer via any network, such as a local area network (LAN) or wide area network (WAN), or connected to an external computer (e.g., via the Internet), or in a cloud computing environment, or used as a service such as Software as a Service (SaaS).

[0194] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this application are not intended to limit the order of the processes and methods of this application. Although some currently considered useful embodiments of the invention have been discussed in the foregoing disclosure by way of various examples, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the substance and scope of the embodiments of this application. For example, although the implementation of the various components described above can be embodied in a hardware device, it can also be implemented as a purely software solution, such as an installation on an existing server or mobile device.

[0195] Similarly, it should be noted that, in order to simplify the description of the present application and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of the embodiments of the present application sometimes combines multiple features into a single embodiment, drawing, or description thereof. However, this approach of the present application should not be construed as reflecting an intention that the claimed subject matter requires more features than expressly recited in each claim. Rather, the subject of the invention should possess fewer features than in any single embodiment described above.

Claims

1. An accelerated scanning method for EMI receivers based on time-domain envelope reconstruction, characterized in that, include: (1) Based on the user-defined start frequency, end frequency, target resolution bandwidth and detector type, divide the entire frequency band into several scanning segments and determine the center frequency of each scanning segment; (2) For each scan segment, tune the preselected filter and the local oscillator frequency, perform broadband time-domain signal acquisition, and obtain the complex baseband signal of the scan segment; (3) Perform a short-time Fourier transform on the complex baseband signal to obtain the instantaneous spectrum of each time frame, wherein the instantaneous spectrum contains complex information of each frequency point; (4) For each frequency point, extract the complex sequence of the frequency point from the instantaneous spectrum of all time frames, perform inverse short-time Fourier transform or overlap and addition on the complex sequence, and reconstruct the time-domain envelope signal of the frequency point. (5) Based on the detector type selected by the user, perform digital detection processing on the reconstructed time-domain envelope signal to obtain the measurement results of the frequency points; (6) Apply system calibration compensation to the measurement results at all frequency points to obtain calibrated measurement results; (7) The calibrated measurement results of all scanning segments are spliced ​​together to generate a complete continuous spectrum from the start frequency to the end frequency.

2. The accelerated scanning method for EMI receivers based on time-domain envelope reconstruction according to claim 1, characterized in that, In step (2), for quasi-peak detection, linear average detection, or root mean square average detection, the acquisition time of the broadband time-domain signal acquisition is greater than or equal to the dwell time specified in the CISPR standard.

3. The EMI receiver accelerated scanning method based on time-domain envelope reconstruction according to claim 1, characterized in that, The complex baseband signal obtained in step (2) is obtained by performing digital down-conversion and anti-aliasing filtering on the acquired time-domain signal to obtain the complex baseband signal; the instantaneous spectrum of each time frame in step (3) is obtained by mapping the baseband frequency to the radio frequency.

4. The EMI receiver accelerated scanning method based on time-domain envelope reconstruction according to claim 1, characterized in that, The overlap rate of the short-time Fourier transform in step (3) is greater than or equal to 90%; the frame length of the fast Fourier transform is determined according to the target resolution bandwidth so that the equivalent resolution bandwidth is equal to the target resolution bandwidth; the fast Fourier transform is then performed after applying a window function to the data of each frame for weighting.

5. The EMI receiver accelerated scanning method based on time-domain envelope reconstruction according to claim 1, characterized in that, In step (4), when performing inverse short-time Fourier transform or overlap-add processing on the complex sequence at each frequency point, the amplitude information and phase information of the complex sequence are used simultaneously to reconstruct the time-domain envelope signal containing amplitude changes over time.

6. The EMI receiver accelerated scanning method based on time-domain envelope reconstruction according to claim 1, characterized in that, The digital detection processing in step (5) includes: if the detector type selected by the user is quasi-peak detection, then the charging time constant, discharging time constant and mechanical time constant defined by the CISPR standard are applied to perform quasi-peak detection simulation on the reconstructed time-domain envelope signal to obtain quasi-peak measurement results; if the detector type selected by the user is peak detection, then the maximum value of the reconstructed time-domain envelope signal during the entire acquisition time is calculated to obtain peak measurement results; if the detector type selected by the user is linear average detection, then the arithmetic mean of the reconstructed time-domain envelope signal is calculated to obtain linear average measurement results; if the detector type selected by the user is root mean square (RMS) average detection, then the RMS value of the reconstructed time-domain envelope signal is calculated to obtain RMS average measurement results.

7. The accelerated scanning method for EMI receivers based on time-domain envelope reconstruction according to claim 1, characterized in that, The system calibration compensation in step (6) includes: performing amplitude correction on the measurement results of each frequency point according to the pre-stored system frequency response calibration curve; applying the equivalent noise bandwidth correction factor for normalization correction based on the difference between the actual resolution bandwidth and the target resolution bandwidth; and applying the temperature drift compensation coefficient for temperature compensation based on real-time temperature sensor data.

8. The accelerated scanning method for EMI receivers based on time-domain envelope reconstruction according to claim 1, characterized in that, The spectrum splicing in step (7) specifically includes: identifying the overlapping frequency region between adjacent scan segments, designing a trapezoidal weighting function, performing weighted averaging on the calibrated measurement results of the two adjacent segments in the overlapping region, and then connecting the processed data of all scan segments in frequency order.

9. The accelerated scanning method for EMI receivers based on time-domain envelope reconstruction according to claim 1, characterized in that, After processing one scan segment, the acquisition parameters for the next scan segment are dynamically adjusted based on the real-time signal characteristics of the current scan segment. This dynamic adjustment includes: calculating the signal density of the current scan segment, where the signal density is the proportion of frequency points whose measured value exceeds the noise floor plus 6 dB to the total number of frequency points in the current scan segment; if the signal density is below a first threshold, the acquisition bandwidth of the Fast Fourier Transform is reduced in the next scan segment; if the signal density is above a second threshold, the overlap rate of the Short-Time Fourier Transform is increased to over 95% in the next scan segment; and if a large number of pulse signals are detected, the model parameters of the quasi-peak detector are dynamically adjusted.

10. The accelerated scanning method for EMI receivers based on time-domain envelope reconstruction according to claim 9, characterized in that, The first threshold is 5%, and the second threshold is 30%; the reduction in the acquisition bandwidth increases the frequency resolution.

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