Channel equalization method based on frequency sampling method

Abstract

The invention provides a channel equalization method based on a frequency sampling method, and the method comprises the steps: solving a frequency domain quotient through the frequency response of a to-be-equalized channel and a reference channel, obtaining the frequency of an ideal equalization filter through a band-pass filter and a frequency domain entropy, carrying out the IFFT of the ideal equalization filter, and carrying out the iteration for a plurality of times according to the performance of the channel. According to the method, an ideal equalization filter coefficient can be obtained, and based on the obtained ideal equalization filter coefficient, an actual equalization filter is constructed through an FIR filter model to complete equalization of a to-be-equalized channel. According to the method, inverse operation of a matrix of a conventional frequency domain least square method is avoided, the complexity of the algorithm is reduced, and the method can be realized in real time in engineering. Meanwhile, by means of a band-pass filter and an iteration mode, the equalization precision is further improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of radar signal processing, in particular to a channel equalization method based on frequency sampling method. BACKGROUND

[0002] Software radio technology, through the combination of software and hardware, provides a configuration scheme of multi-mode, multi-band, multi-function, effective and economic wireless network. It can not only be applied to the field of communication, but also has more applications in the field related to radio engineering, such as radar, navigation, broadcast television, etc. The hardware part usually contains multiple radio frequency channels, and each radio frequency channel contains power amplifiers, mixers, filters, A / D converters and other analog devices. Due to its own nature, analog devices will have inconsistencies in different temperature, humidity and other environments, resulting in amplitude and phase inconsistencies between channels.

[0003] In order to correct the error caused by channel mismatch, the mismatch of each channel can be compensated by inserting an equalization filter in the channel. The solution of the equalization filter is divided into time domain algorithm and frequency domain algorithm. The time domain algorithm includes Wiener filter method, LMS method and RLS adaptive algorithm. The time domain adaptive filter algorithm avoids the inversion of matrix and reduces the complexity of the algorithm, but also has the problem of insufficient precision. The frequency domain algorithm includes frequency domain least square fitting method and frequency sampling method (also known as Fourier transform method). The frequency domain least square method overcomes the problem of insufficient precision and has high precision, but the calculation workload is large and is not conducive to engineering implementation. The frequency sampling method is more susceptible to out-of-band noise and signal signal-to-noise ratio, and its performance is not as good as that of the frequency domain least square method, but it avoids the inversion of matrix and has small amount of calculation, so it is more suitable for engineering implementation. SUMMARY

[0004] The purpose of the present application is to provide a channel equalization method based on frequency sampling method, to improve the equalization performance, reduce the calculation amount and facilitate engineering implementation.

[0005] To achieve the above purpose, the present application provides a channel equalization method based on frequency sampling method, which comprises: Step 1, obtaining the sampling signals of multiple channels, transforming the sampling signals of multiple channels to the frequency domain by FFT to obtain the frequency domain signals of multiple channels; setting one channel as a reference channel, and taking the frequency of the reference channel as the ideal frequency domain, and the other channels as the channels to be equalized; for each channel to be equalized, calculating the frequency domain quotient; Step 2, designing a band-pass filter, obtaining the ideal equalization filter frequency of the channel to be equalized according to the band-pass filter and the frequency domain quotient; sampling the ideal equalization filter frequency to obtain the ideal equalization filter frequency sampling value, and determining the transfer function of the ideal equalization filter according to the ideal equalization filter frequency sampling value; Step 3, iteration is performed according to channel performance to make the amplitude mismatch and phase mismatch of the equalized signal meet the threshold requirement, and an ideal equalization filter transmission function meeting the design requirement is obtained; Step 4, IFFT transformation is performed on the transmission function of the ideal equalization filter to obtain the ideal equalization filter coefficients of the to-be-equalized channel; Step 5, based on the obtained ideal equalization filter coefficients of each to-be-equalized channel, an actual equalization filter is constructed through a FIR filter model to complete the equalization of the to-be-equalized channel.

[0006] Further, the step 1 comprises: Step 11, a wideband calibration linear frequency modulation signal is designed, the wideband calibration linear frequency modulation signal is input into each channel, and the sampling signals of the multiple channels are obtained: ; ; ; wherein, is a wideband calibration linear frequency modulation signal, is a signal form represented by an Euler formula, B is a signal bandwidth, T is a signal pulse width, and k is a relative size or proportion of the signal bandwidth and the pulse width, is an equalization system sampling rate; The wideband calibration linear frequency modulation signal is input into the reference channel, the reference channel is collected, and the collected signal of the reference channel is obtained ; wherein n is a quantization value of a sampling time; The wideband calibration linear frequency modulation signal is input into the to-be-equalized channel, the to-be-equalized channel is collected, and the collected signal of the to-be-equalized channel is obtained ; wherein, is the sampling signal of the i-th to-be-equalized channel, is a serial number of the to-be-equalized channel, and N is a total number of to-be-equalized channels; Step 12, the sampling signal of the to-be-equalized channel is windowed, and a part of the signal is intercepted to obtain a windowed signal: ; wherein, is a windowed signal; is a time domain window; Step 13, the windowed signal of the to-be-equalized channel is subjected to FFT transformation to obtain a frequency domain signal of the to-be-equalized channel , wherein ω is a frequency; Step 14, based on the frequency signal of the to-be-equalized channel , the frequency signal of the reference channel is given, and the frequency domain quotient of each to-be-equalized channel is calculated: ; ; wherein, is the frequency domain quotient of the ith channel to be equalized; H ref (ω) is the frequency signal of the all-pass filter; L is the order of the all-pass filter, is the time domain form of the all-pass filter expressed by Euler formula.

[0007] Further, the step 2 comprises: Step 21, designing a band-pass filter: According to the bandwidth of the channel, the sampling rate and the carrier signal frequency, a band-pass filter is constructed by a direct type FIR filter ; Step 22, obtaining the frequency domain quotient H by the band-pass filter, to obtain the ideal equalization filter frequency: ; wherein, H m (ω) is the ideal equalization filter frequency; m is the channel serial number of the ideal equalization filter, ; Step 23, sampling the ideal equalization filter frequency to obtain M frequency sampling values of the ideal equalization filter : ; wherein, is the serial number of the discrete frequency sampling point, M is the total number of sampling points; Step 24, determining the transfer function of the ideal equalization filter according to the frequency sampling values of the ideal equalization filter: According to the sampling theorem, the transfer function of the ideal equalization filter is: ; wherein, is the transfer function designed by taking the unit sampling sequence obtained by IDFT on as the unit impulse response; IDFT is inverse discrete Fourier transform; Z is the complex number domain representation of discrete Fourier transform, wherein ; is the rotation factor of IDFT.

[0008] Further, the iteration according to the channel performance in the step 3 is specifically: ; wherein, represents the performance of the channel, The frequency response sample of the ideal equalization filter for the i-th channel; The frequency response sample of the ideal equalization filter for the reference channel; The amplitude mismatch; The phase mismatch.

[0009] Further, the step 3 comprises: According to the design requirements, the constraints of the iteration of the predetermined channel performance are performed, so that the amplitude mismatch and the phase mismatch of the equalized signal meet the threshold value requirements, the threshold value comprises an amplitude mismatch threshold and a phase mismatch threshold, and a designed ideal equalization filter is obtained; the specific constraint conditions are: The absolute value of the difference between the amplitude mismatch average value and 1 is less than 0.1V; The absolute value of the difference between the amplitude mismatch variance and 0 is less than 0.1V; The absolute value of the difference between the phase mismatch average value and 0 is less than 0.1°; The absolute value of the difference between the phase mismatch variance and 0 is less than 0.1°.

[0010] Further, the step 3 further comprises: Initializing an iteration counter C1, the initial value of C1 is 1; and setting the iteration number C2; According to the designed ideal equalization filter, the amplitude mismatch value and the phase mismatch value of the equalized signal are calculated, and the values are compared with the constraint conditions: If the variance, the average value of the signal amplitude and the variance and the average value of the phase are all less than the threshold value, it is indicated that the performance of the ideal equalization filter meets the requirements; otherwise, C1 is added by 1, and the step 2 is repeated until the design requirements are met or the maximum value of C1 exceeds .

[0011] Further, the step 4 comprises: The transmission function of the ideal equalization filter is subjected to IFFT transformation, and the corresponding ideal equalization filter coefficient is obtained: ; Wherein, The ideal equalization filter coefficient.

[0012] Compared with the prior art, the present application has the following beneficial effects: (1) The present application uses the frequency sampling method and IFFT calculation to obtain the filter coefficient of the ideal equalization filter, and the complexity of the algorithm is very low, which is very easy to realize in engineering; (2) The present application uses a band-pass filter to intercept the frequency, and the sideband signal is subjected to smoothing processing, which reduces the error of the frequency sampling method and improves the design accuracy of the band-pass filter; (3) The application uses the equalization effect evaluation method to iterate the ideal equalization filter, and improves the equalization effect. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 A flowchart of a channel equalization method based on a frequency sampling method is provided in the application; Figure 2 A practical equalization filter structure diagram is provided in the application. DETAILED DESCRIPTION

[0014] In order to make the above-mentioned purposes, features and advantages of the application more obvious and easy to understand, the specific embodiments of the application will be described in detail below in combination with the drawings. In the following description, a large number of specific details are set forth in order to facilitate a full understanding of the application. However, the application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the concept of the application, so the application is not limited by the specific embodiments disclosed below.

[0015] Embodiment one: The application provides a channel equalization method based on a frequency sampling method, as shown in the figure, the method comprises: Figure 1 Step 1, obtaining a multi-channel sampling signal, transforming the multi-channel sampling signal to the frequency domain through FFT to obtain a multi-channel frequency domain response; setting one channel as a reference channel, and taking the frequency domain response of the reference channel as an ideal frequency domain response, and the other channels as equalization channels; for each equalization channel, calculating a frequency domain quotient; Step 11, designing a wideband calibration linear frequency modulation signal, inputting the wideband calibration linear frequency modulation signal into each channel to obtain a multi-channel sampling signal: Among them, the wideband calibration linear frequency modulation signal, the signal form expressed by the Euler formula; B is the signal bandwidth, which is consistent with the bandwidth of the equalization channel; T is the signal pulse width; k is the relative size or proportion of the signal bandwidth and the pulse width, is the sampling rate of the equalization system; inputting the wideband calibration linear frequency modulation signal into the reference channel, collecting the reference channel to obtain a reference channel collection signal ; wherein n is the quantization value of the sampling time; inputting the wideband calibration linear frequency modulation signal into the equalization channel, collecting the equalization channel to obtain an equalization channel sampling signal ; wherein​​​​ is the sampling signal of the i-th channel to be equalized, is the serial number of the channel to be equalized, and N is the total number of channels to be equalized; Step 12, windowing the sampling signal of the channel to be equalized, cutting the signal part, and obtaining a windowed signal: ; wherein, is the windowed signal; is the sampling signal of the channel to be equalized; is the time domain window; Step 13, performing FFT transformation on the windowed signal of the channel to be equalized to obtain the frequency domain data of the channel to be equalized , wherein ω is the frequency, and FFT is the fast Fourier transform; Step 14, based on the frequency signal of the channel to be equalized , and given the frequency signal of the reference channel , the frequency domain quotient of each channel to be equalized is calculated: ; ; wherein, is the frequency domain quotient of the i-th channel to be equalized; H ref (ω) is the frequency signal of the all-pass filter; L is the order of the filter, is the time domain form of the all-pass filter represented by the Euler formula.

[0016] Further explanation, because the FIR filter in engineering will introduce time delay, in order to make the signal through different channels align, the all-pass filter is introduced in the reference channel, so that the delay of different channels is consistent.

[0017] Step 2, design a band-pass filter; according to the band-pass filter and the frequency domain quotient, obtain the ideal equalization filter frequency of the channel to be equalized; sample the ideal equalization filter frequency to obtain the sampled ideal equalization filter frequency response, and determine the transfer function of the ideal equalization filter according to the sampled ideal equalization filter frequency response; Step 21, design a band-pass filter; According to the bandwidth, sampling rate and carrier signal frequency of the channel, a band-pass filter is constructed by a direct type FIR filter ; Step 22, pass the frequency domain quotient through the band-pass filter to obtain the ideal equalization filter frequency: ; wherein, H m(ω) is the frequency of the ideal equalizer filter; H w (ω) represents the bandpass filter; m is the channel number; Step 23: Sample the frequency of the ideal equalizer filter. Equally spaced sampling is performed to obtain M frequency sample values ​​for the ideal equalization filter. : ; in, The discrete frequency sampling point number; M is the total number of sampling points; Step 24: Determine the transfer function of the ideal equalizer based on the frequency sampled values ​​of the ideal equalizer. According to the sampling theorem, the transfer function of an ideal equalizer filter is: ; in, To The unit sample sequence obtained by performing the IDFT is used as the transfer function designed for the unit impulse response. IDFT stands for Inverse Discrete Fourier Transform; Z is the complex-domain representation of the Discrete Fourier Transform, where... , is the twiddle factor of IDFT; like Figure 2 As shown, the time-domain form of the filter is constructed based on the transfer function of the ideal equalizer filter. In the figure, the signal is input to the reference channel and the channel to be equalized via a power divider. In the channel to be equalized, the signal passes through the frequency signal of the channel to be equalized. Signal received later .Signal The input equalization filter performs equalization filtering on the signal, that is, the signal is time-delayed. (can be simplified to () )) respectively with the corresponding filter coefficients Multiply and sum to obtain the corresponding channel output. In the reference channel, the frequency signal of the channel. and all-pass filter The corresponding channel output is obtained as .

[0018] Step 3: Iterate according to the channel performance to make the amplitude mismatch and phase mismatch of the equalized signal meet the threshold requirements, and obtain the designed ideal equalization filter transfer function; The iteration is based on channel performance, specifically: ; in, Indicates the performance of the channel. the frequency sample of the ideal equalization filter for the i-th channel; the frequency sample of the ideal equalization filter for the reference channel; the amplitude mismatch, the closer the mean value is to 1 and the closer the variance is to 0, the better the amplitude performance of the channel is; the phase mismatch, the closer the mean value and the variance are to 0, the better the phase performance of the channel is; iterating the predetermined channel performance according to the design requirement to make the amplitude mismatch and the phase mismatch of the equalized signal meet the threshold requirement, the threshold including an amplitude mismatch threshold and a phase mismatch threshold, to obtain a designed ideal equalization filter; the specific constraint conditions are: the absolute value of the difference between the mean value of the amplitude mismatch and 1 is less than 0.1V; the absolute value of the difference between the variance of the amplitude mismatch and 0 is less than 0.1V; the absolute value of the difference between the mean value of the phase mismatch and 0 is less than 0.1°; the absolute value of the difference between the variance of the phase mismatch and 0 is less than 0.1°.

[0019] It should be noted that the amplitude mismatch and phase mismatch threshold can be designed according to actual requirements.

[0020] initializing an iteration counter C1, the initial value of C1 being 1; setting the iteration number C2; performing equalization processing according to the designed ideal equalization filter, calculating the amplitude mismatch value and the phase mismatch value of the equalized signal, and comparing them with the constraint conditions: if the variance, mean value of the signal amplitude and the variance, mean value of the phase are all less than the threshold, it is considered that the equalization filter performance meets the requirement, otherwise C1 is increased by 1 and step 2 is repeated until the design requirement is met or the maximum value of C1 exceeds .

[0021] Step 4: performing IFFT transformation on the transfer function of the ideal equalization filter to obtain the ideal equalization filter coefficients of the channel to be equalized: ; wherein, is the ideal equalization filter coefficient; IDFT() is the inverse discrete Fourier transform, and IFFT is the inverse fast Fourier transform.

[0022] Step 5: constructing the actual equalization filter through the FIR filter model with the obtained ideal equalization filter coefficients of each channel to be equalized, to complete the equalization of the channel to be equalized.

[0023] Further illustrate, in this embodiment, first due to the characteristics of the analog channel left and right asymmetry, using carrier signal to obtain the frequency domain quotient of the channel to be equalized and reference signal, so as to further improve the performance of equalization. Then using band pass filter to intercept the frequency response of the ideal equalization filter, the sideband signal is smoothed, the error of frequency sampling method is reduced, and the design precision of the filter is improved. Finally, the method of IFFT is used to obtain the equalization filter coefficient, which avoids matrix inversion and approximation algorithm, reduces the complexity of equalization filter solution, and is beneficial to engineering implementation.

[0024] For those skilled in the art, various corresponding changes and modifications can be made according to the above technical solutions and concepts, and all these changes and modifications should be included in the protection scope of the claims of the present application.

Claims

1. A method of channel equalization based on frequency sampling method, characterized in that, The method comprises: Step 1, obtaining a multi-channel sampling signal, transforming the multi-channel sampling signal to a frequency domain through FFT to obtain a multi-channel frequency domain signal; setting a channel as a reference channel, and taking the frequency of the reference channel as an ideal frequency domain, and other channels as to-be-equalized channels; for each to-be-equalized channel, calculating a frequency domain quotient; Step 2, designing a band-pass filter, obtaining an ideal equalization filter frequency of the to-be-equalized channel according to the band-pass filter and the frequency domain quotient; sampling the ideal equalization filter frequency to obtain an ideal equalization filter frequency sample value, and determining a transmission function of the ideal equalization filter according to the ideal equalization filter frequency sample value; Step 3, iteratively according to channel performance, so that amplitude mismatch and phase mismatch of the equalized signal meet threshold value requirements, and an ideal equalization filter transmission function meeting design requirements is obtained; Step 4, performing IFFT transformation on the transmission function of the ideal equalization filter to obtain ideal equalization filter coefficients corresponding to the to-be-equalized channel; Step 5, constructing an actual equalization filter through a FIR filter model based on the obtained ideal equalization filter coefficients of each to-be-equalized channel, and completing equalization of the to-be-equalized channel.

2. The method of claim 1, wherein, The step 1 comprises: Step 11, designing a wideband calibration linear frequency modulation signal, and connecting the wideband calibration linear frequency modulation signal into each channel to obtain a multi-channel sampling signal; ； ； ； wherein, is a wideband calibration chirp signal, is a signal form expressed in Euler's formula, B is the signal bandwidth, T is the signal pulse width, k is the relative size or ratio of the signal bandwidth to the pulse width, is the equalization system sampling rate; The broadband calibration linear frequency modulation signal is input into the reference channel, and the reference channel is collected to obtain a collection signal of the reference channel ; wherein n is a quantization value of the sampling time; The broadband calibration linear frequency modulation signal is input into the channel to be equalized, and the channel to be equalized is collected to obtain a collected signal of the channel to be equalized ; wherein, is a sample signal of the i th channel to be equalized, is a serial number of the channel to be equalized, and N is a total number of the channels to be equalized Step 12, windowing the sampling signal of the to-be-equalized channel to cut off part of the signal to obtain a windowed signal; ； wherein is a windowed signal; is a time domain window; Step 13, performing FFT transform on the windowed signal of the to-be-equalized channel to obtain a frequency domain signal of the to-be-equalized channel where ω is frequency. Step 14, calculating the frequency-domain quotient of each channel to be equalized based on the frequency signal of the reference channel Step 15, calculating the frequency-domain quotient of each channel to be equalized based on the frequency signal of the given reference channel Step 16, calculating the frequency-domain quotient of each channel to be equalized based on the frequency signal of the given reference channel ； ； wherein, H is the frequency domain quotient of the i-th channel to be equalized; H ref (ω) is a frequency signal of the all-pass filter; L is the order of the all-pass filter, is a time domain form of the all-pass filter represented by the Euler formula.

3. The method of claim 2, wherein, The step 2 comprises: Step 21, designing a band-pass filter; A bandpass filter is constructed by a direct type FIR filter according to the bandwidth of the channel, the sampling rate and the carrier signal frequency ; Step 22, frequency domain quotient Through the band-pass filter, the ideal equalization filter frequency is obtained: ； wherein H m (ω) is the ideal equalization filter frequency; m is the ideal equalization filter channel number, ; Step 23, sampling the ideal equalization filter frequency to obtain M frequency sampling values of the ideal equalization filter : ； wherein is the discrete frequency sample point number, M is the total number of sample points; Step 24, determining a transmission function of the ideal equalization filter according to the ideal equalization filter frequency sample value: According to the sampling theorem, the transmission function of the ideal equalization filter is: ； wherein is the unit sample sequence obtained by performing an IDFT on a transfer function designed with the unit impulse response; Z is the complex number domain representation of the discrete Fourier transform, wherein ; is the rotation factor of the IDFT.

4. The method of claim 3, wherein, The step 3 iterates according to channel performance, and specifically: ； wherein, represents the performance of a channel, is an ideal equalizer filter frequency response sample for the i-th channel; is an ideal equalizer filter frequency response sample for the reference channel; is an amplitude mismatch; is a phase mismatch.

5. The method of claim 4, wherein, The step 3 comprises: According to the constraint condition of predefining channel performance according to design requirements, the amplitude mismatch and the phase mismatch of the equalized signal meet the threshold value requirements, the threshold value comprises an amplitude mismatch threshold and a phase mismatch threshold, and a designed ideal equalization filter is obtained; the specific constraint condition is: The absolute value of the difference between the amplitude mismatch mean value and 1 is less than 0.1V; The absolute value of the difference between the amplitude mismatch variance and 0 is less than 0.1V; The absolute value of the difference between the phase mismatch mean value and 0 is less than 0.1°; The absolute value of the difference between the phase mismatch variance and 0 is less than 0.1°.

6. The method of claim 5, wherein: The step 3 further comprises: Initializing an iteration counter C1, and the initial value of C1 is 1; and setting an iteration number C2; According to the designed ideal equalization filter, the amplitude mismatch value and the phase mismatch value of the equalized signal are calculated, and the values are compared with the constraint condition: If the variance and mean value of the signal amplitude and the variance and mean value of the phase are all less than the threshold value, it is indicated that the ideal equalization filter performance meets the requirements; otherwise, C1 is increased by 1, and step 2 is repeated until the design requirements are met or the maximum value of C1 exceeds C2-1.

7. The method of claim 6, wherein: The step 4 comprises: Performing IFFT transformation on the transmission function of the ideal equalization filter to obtain corresponding ideal equalization filter coefficients: ； wherein, are ideal equalization filter coefficients.

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