A data processing method for a zero-IF receiving digital array channel

Abstract

The present invention discloses a data processing method for a zero-IF receiving digital array channel, comprising calibrating the data of the zero-IF receiving array channel and performing multi-beam synthesis on the data of the zero-IF receiving array channel. The calibrating the data of the zero-IF receiving array channel comprises: subjecting a single-frequency calibration signal received by each array element to pre-selection filtering, low-noise amplification, in-phase and quadrature mixing, low-pass filtering, and A / D acquisition in each channel of the zero-IF receiving array to obtain baseband digital complex signals of M receiving channels; using the baseband digital complex signals of the M receiving channels to estimate and compensate for IQ imbalance errors of each channel to obtain complex signals after IQ imbalance errors are compensated; and calculating a normalized channel error compensation value. The present invention has the advantages of improving the image suppression capability of the array channel, occupying little memory space, and being suitable for small-scale arrays.

Description

Technical Field

[0001] The present invention relates to the technical field of digital array channel calibration, and in particular to a data processing method for a zero intermediate frequency receiving digital array channel. Background Art

[0002] With the continuous advancement of digital signal processing technology and the corresponding increase in processing power, digital arrays, with their multiple scanning beams and high design flexibility, have gradually replaced analog array antennas and become a major research direction in electronic information technology fields such as communications, countermeasures, and radar. Digital arrays constructed with multi-channel zero-IF receivers offer low cost, low power consumption, and high integration, making them a key development direction for digital arrays. Data processing in zero-IF receiver digital array channels generally requires channel calibration to estimate and compensate for intra-channel IQ imbalance errors and inter-channel amplitude and phase errors, followed by multi-beam synthesis.

[0003] In practical applications, due to current device technology limitations, the image suppression capabilities of each zero-IF receive channel in the array are limited, inevitably leading to IQ imbalance errors. This error results in the presence of not only frequency-domain but also spatial-domain image components after beamforming in the zero-IF receive digital array. These image components can significantly impact the overall performance of the receive array.

[0004] Currently, there are numerous research papers on IQ imbalance estimation and compensation methods for single-channel zero-IF receivers, such as Chinese Patent Publication No. CN115833957A, which discloses a method for correcting IQ imbalance in zero-IF receivers. However, there is little discussion of calibration and synthesis methods for multi-channel zero-IF receivers in digital arrays. Unlike single-channel zero-IF receivers, the beamforming performance of zero-IF receiver digital arrays is affected by both intra-channel IQ imbalance errors and inter-channel amplitude and phase errors. For large-scale digital arrays, by rationally designing zero-IF receiver channels, the in-phase superposition characteristics of beamforming can be exploited to further suppress the image components caused by IQ imbalance errors within each channel. The image suppression ratio is approximately equal to the signal-to-noise ratio gain of array beamforming. Therefore, during array calibration, only the inter-channel amplitude and phase errors need to be estimated, eliminating the need to estimate intra-channel IQ imbalance errors. For small-scale digital arrays, beamforming has limited image suppression capabilities, and the image components carried by the beamforming output may not meet system requirements. Therefore, during array channel calibration, it is necessary to estimate both intra-channel IQ imbalance errors and inter-channel amplitude and phase errors separately. However, in actual calibration samples, both intra-channel IQ imbalance errors and inter-channel amplitude and phase errors are present, making it difficult to accurately separate these two errors.

[0005] Compared to inter-channel amplitude and phase error estimation, intra-channel IQ imbalance error estimation requires a large amount of calibration sample data to achieve satisfactory image suppression. If a similar inter-channel amplitude and phase error estimation method is used (first collecting calibration samples for all channels and storing them in computer memory, and then calculating the amplitude and phase error estimates between all channels), the estimation of IQ imbalance errors within each channel of the array requires a huge amount of storage space, which is not conducive to practical engineering applications. Therefore, to improve the image suppression capability of array channels, reduce the storage space occupied by calibration, and facilitate the simultaneous formation of multiple beams, it is necessary to find a zero-IF receive array channel calibration and multi-beam synthesis method that can estimate and compensate for IQ imbalance errors channel by channel, estimate and compensate for amplitude and phase errors between channels, occupy a small amount of memory space, and is suitable for small-scale arrays. Summary of the Invention

[0006] The technical problem to be solved by the present invention is how to provide a data processing method for zero intermediate frequency receiving array channels that can improve the image suppression capability of array channels, occupies little memory space, and is suitable for small-scale arrays.

[0007] The present invention solves the above technical problems by the following technical means: a data processing method for a zero intermediate frequency receiving digital array channel, comprising calibrating the data of the zero intermediate frequency receiving array channel and performing multi-beam synthesis on the data of the zero intermediate frequency receiving array channel; the calibrating the data of the zero intermediate frequency receiving array channel comprises:

[0008] Step 1: The digital array has a total of M array elements. The single-frequency calibration signal received by each array element undergoes pre-selection filtering, low-noise amplification, in-phase and quadrature mixing, low-pass filtering, and A / D acquisition in each channel of the zero-IF receiving array to obtain the baseband digital complex signal of the M receiving channels;

[0009] Step 2: Using the baseband digital complex signals of the M receiving channels, perform IQ imbalance error estimation and compensation for each channel to obtain a complex signal after IQ imbalance error compensation;

[0010] Step 3: Calculate a normalized channel error compensation value using the complex signal after IQ imbalance error compensation and the IQ imbalance weighting coefficient.

[0011] Furthermore, performing multi-beam combining on the data of the zero intermediate frequency receiving array channel includes:

[0012] Step 4: Calculate the beam weighting coefficients of the multi-beam according to the coordinates of the M array elements in the array rectangular coordinate system and the beam pointing angles;

[0013] Step 5: If the number of beams P = 1, combine the normalized channel error compensation value with the beam weight coefficient, correct the baseband digital complex signal, perform beamforming, and obtain a beamformed signal;

[0014] Step 6: If the number of beams P is greater than 1, the baseband digital complex signals of the M receiving channels are corrected using the normalized channel error compensation value and the multi-beam weighting coefficient, and P beams are formed simultaneously to obtain P beam-synthesized signals.

[0015] Furthermore, the step 1 includes:

[0016] The single-frequency calibration signal received by the mth array element is x m (t)=A0cos[(Ω c +Ω d )t+φ0], where φ0 is the initial phase, Ω c is the carrier analog angular frequency of the received signal, A0 is the amplitude of the single frequency signal, Ω d is the simulated angular frequency offset of the single frequency signal and Ω d >0;

[0017] The baseband digital complex signal of the mth receiving channel is Among them, * is the complex number conjugation operation, represents the baseband digital complex signal obtained by the mth receiving channel that is independent of the IQ imbalance error and A m , are respectively the frequency response of the mth RF front end at frequency Ω d The amplitude and phase values ​​at T s is the sampling frequency of A / D, λ 1,m and λ 2,m denote the first coefficient and the second coefficient respectively, and

[0018]

[0019]

[0020] Among them, g m It is composed of the zero intermediate frequency receiver in-phase local oscillator and quadrature local oscillators The amplitude error caused by the amplitude difference between m It is composed of the zero intermediate frequency receiver in-phase local oscillator and quadrature local oscillators Phase error caused by the phase difference between them; Complex low-pass filters The frequency response at frequency Ω d The amplitude and phase values ​​at Complex low-pass filters The frequency response at frequency-Ω d The amplitude and phase values ​​at ; Complex low-pass filters Relative to The frequency response at frequency Ω d The amplitude and phase values ​​at ; Complex low-pass filters Relative to The frequency response at frequency-Ω d The amplitude and phase values ​​at .

[0021] Furthermore, the step 2 includes:

[0022] Step 201: Baseband digital complex signal z m (n) is divided into two paths, one of which is to find the conjugate and obtain the conjugate signal The other channel is delayed by integer multiples to obtain the delayed signal z m (n)';

[0023] Step 202: Using the delayed signal z m (n)' and conjugate signal Perform complex multiplication and coherent accumulation to obtain the autocorrelation function value and complementary autocorrelation function values Where L is the accumulation length and LT s =δ·2π / Ω d , δ is a positive integer;

[0024] Step 203: First weighting coefficient for IQ imbalance compensation Calculate the second weighting coefficient for IQ imbalance compensation

[0025] Step 2-4: Using the first weighting coefficient and the second weighting coefficient Compensate for the IQ imbalance error and obtain a complex signal after IQ imbalance error compensation

[0026] Furthermore, the step 3 includes:

[0027] Step 301: Taking the first receiving channel as the reference channel, calculate the inter-channel amplitude and phase error compensation values ​​of other channels relative to the reference channel. Right now Where K is the number of calibration samples collected for estimating the inter-channel amplitude and phase error compensation values;

[0028] Step 302: By formula Calculate channel error compensation value;

[0029] Step 303: Obtain the amplitude of the error compensation value of each channel And select the maximum value EA max ;

[0030] Step 304: By formula Normalize the channel error compensation value to obtain the normalized channel error compensation value

[0031] Furthermore, the step 4 includes:

[0032] Step 401: Based on P beam pointing angles Calculate the direction cosine value corresponding to the pointing angle of each beam That is, for the pth beam, we have Among them, Azi p is the azimuth, Ele p is the pitch angle, u p is the direction cosine of the angle between the incident direction and the X-axis in the rectangular coordinate system, v p is the direction cosine of the angle between the incident direction and the Y axis in the rectangular coordinate system, w p is the direction cosine of the angle between the incident direction and the Z axis in the rectangular coordinate system;

[0033] Step 402: Based on the direction cosine values ​​of P beams and array coordinates (x m ,y m ,z m ),m=1,2,…,M, calculate the weighted coefficients of multi-beam

[0034]

[0035] Where c is the speed of light, α m is the amplitude weighting coefficient.

[0036] Furthermore, the step 5 includes:

[0037] Step 501: Normalize the channel error compensation value and beam weighting coefficients Combine to get the modified beam weight coefficient That is, for the mth array element, there is

[0038] Step 502: Modify the beam weighting coefficient Baseband digital complex signals for M receiving channels Perform correction to obtain M corrected complex signals

[0039] Step 503: M corrected complex signals Sum and get the beamformed signal Right now

[0040] Furthermore, the step 502 includes:

[0041] Step 5021: Baseband digital complex signal z m (n) is divided into two paths, one of which is to find the conjugate and obtain the conjugate signal The other channel is delayed by integer multiples to obtain the delayed signal z m (n)';

[0042] Step 5022: Use the modified beam weighting coefficient Baseband digital complex signal Correction is performed to obtain the corrected complex signal s m (n)', i.e.

[0043] Furthermore, the step 6 includes:

[0044] Step 601: Use the normalized channel error compensation value Baseband digital complex signals for M receiving channels Perform channel error compensation to obtain M complex signals after channel error compensation

[0045] Step 602: Use the multi-beam weighting coefficients of each channel to compensate the channel error and obtain the complex signal. Perform weighting to obtain the multi-beam weighted output signal Right now

[0046] Step 603: sum the weighted output signals of the multi-beams corresponding to the same beam to obtain P beam synthesis signals. Right now

[0047] Furthermore, step 601 includes:

[0048] Step 6011: Baseband digital complex signal z m (n) is divided into two paths, one of which is to find the conjugate and obtain the conjugate signal The other channel is delayed by integer multiples to obtain the delayed signal z m (n)';

[0049] Step 6012: Using channel error compensation value and Compensate the channel error and obtain the complex signal s after channel error compensation m (n)”, i.e.

[0050] The advantages of the present invention are:

[0051] (1) The present invention uses the baseband digital complex signals of M receiving channels to estimate and compensate for the IQ imbalance error of each channel, obtains the complex signal after the IQ imbalance error compensation, and calculates the normalized channel error compensation value, thereby facilitating the compensation of the channel error. Therefore, the entire scheme can estimate and compensate the IQ imbalance error channel by channel, and can also estimate and compensate the amplitude and phase errors between channels, thereby improving the image suppression capability of the array channel. The present invention does not need to first collect calibration samples of all channels and store them in the computer memory, and then calculate the IQ imbalance error estimation values ​​in all channels. The IQ imbalance error compensation value is directly calculated channel by channel in real time during calibration, which occupies a small memory space and is suitable for small-scale arrays.

[0052] (2) The zero-IF receiving channel calibration algorithm and the zero-IF receiving array multi-beam synthesis method of the present invention are simple in principle, small in computational complexity, and occupy little memory space, making them easy to implement in engineering.

[0053] (3) The calibration and synthesis method provided by the present invention is not only applicable to the case where the low-pass filter in the zero-IF receiver has a real impulse response, but is also applicable to the case where the low-pass filter has a complex impulse response.

[0054] (4) The method provided by the present invention is not limited by the array structure and is applicable to both planar digital arrays and conformal digital arrays. It is applicable not only to digital receiving arrays but also to digital transmitting arrays. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A block diagram of a zero intermediate frequency receiving array channel calibration method in a zero intermediate frequency receiving digital array channel data processing method disclosed in an embodiment of the present invention;

[0056] Figure 2 A block diagram of IQ imbalance error estimation and compensation in a data processing method for a zero-IF receiving digital array channel disclosed in an embodiment of the present invention;

[0057] Figure 3 A block diagram of a zero-IF receiving array multi-beam synthesis method in a data processing method for a zero-IF receiving digital array channel disclosed in an embodiment of the present invention;

[0058] Figure 4 A block diagram of channel error compensation and multi-beam weighting in a data processing method for a zero-IF receiving digital array channel disclosed in an embodiment of the present invention;

[0059] Figure 5 A curve showing how the amplitude error estimation accuracy changes with the number of samples in a simulation experiment of a data processing method for a zero-IF receiving digital array channel disclosed in an embodiment of the present invention;

[0060] Figure 6 A curve showing the variation of phase error estimation accuracy with the number of samples in a simulation experiment of a data processing method for a zero-IF receiving digital array channel disclosed in an embodiment of the present invention;

[0061] Figure 7 This is a curve showing how the image rejection ratio changes with the number of sampling points when the signal-to-noise ratio is 20 dB in a simulation experiment of a data processing method for a zero-IF receiving digital array channel disclosed in an embodiment of the present invention;

[0062] Figure 8 The normal beam pattern corresponding to the target and the mirror signal in the simulation experiment of the data processing method of the zero-IF receiving digital array channel disclosed in the embodiment of the present invention is not compensated for the channel error;

[0063] Figure 9 The normal beam pattern corresponding to the target and the mirror signal after compensating for the channel error in a simulation experiment of a data processing method for a zero-IF receiving digital array channel disclosed in an embodiment of the present invention;

[0064] Figure 10 The beam pattern corresponding to the target and the image signal in the simulation experiment of the data processing method of the zero-IF receiving digital array channel disclosed in the embodiment of the present invention is not compensated for the channel error;

[0065] Figure 11 This is the beam pattern corresponding to the target and the image signal after compensating for the channel error in a simulation experiment of a data processing method for a zero-IF receiving digital array channel disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0066] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0067] like Figure 1 As shown, the present invention provides a data processing method for a zero-IF receiving digital array channel, comprising calibrating the data of the zero-IF receiving array channel and performing multi-beam synthesis on the data of the zero-IF receiving array channel; the calibrating the data of the zero-IF receiving array channel comprises:

[0068] Step 1: The digital array has a total of M array elements. The single-frequency calibration signal received by each array element undergoes pre-selection filtering, low-noise amplification, in-phase and quadrature mixing, low-pass filtering, and A / D acquisition in each channel of the zero-IF receiving array to obtain the baseband digital complex signal of the M receiving channels. The specific process of step 1 is as follows:

[0069] The digital array has a total of M array elements, so the single-frequency calibration signal received by the mth array element is

[0070] x m (t) = A0cosp(Ω c +Ω d )t+φ0]

[0071] Where φ0 is the initial phase, Ω c is the carrier analog angular frequency of the received signal, A0 is the amplitude of the single frequency signal, Ω d >0 is the analog angular frequency offset of the single-frequency signal. After pre-selection filtering, low-noise amplification, in-phase and orthogonal mixing, low-pass filtering and A / D acquisition of each channel of the zero-IF receiving array, the baseband digital complex signal of M receiving channels is obtained. have

[0072]

[0073] in, T s is the sampling frequency of A / D. 1,m and λ 2,m They are

[0074]

[0075]

[0076] Among them, g m It is composed of the zero intermediate frequency receiver in-phase local oscillator and quadrature local oscillators The amplitude error caused by the amplitude difference between m It is composed of the zero intermediate frequency receiver in-phase local oscillator and quadrature local oscillators The phase error caused by the phase difference between them. Complex low-pass filters The frequency response at frequency Ω d The amplitude and phase values ​​at Complex low-pass filters The frequency response at frequency-Ω d The amplitude and phase values ​​at . Complex low-pass filters Relative to The frequency response at frequency Ωd The amplitude and phase values ​​at . Complex low-pass filters Relative to The frequency response at frequency-Ω d The amplitude and phase values ​​at . The frequency response of the mth RF front end (including antenna, preselection filter, low noise amplifier) ​​at frequency Ω d The amplitude and phase values ​​at .

[0077] Step 2: Use the baseband digital complex signals of the M receiving channels to estimate and compensate the IQ imbalance error of each channel to obtain the complex signal after IQ imbalance error compensation; the IQ imbalance error estimation and compensation processing of each channel are the same. For the mth receiving channel, the processing block diagram is as follows: Figure 2 As shown, the specific process of step 2 is:

[0078] Step 201: Baseband digital complex signal z m (n) is divided into two paths, one of which is to find the conjugate and obtain the conjugate signal The other branch performs integer multiple delay to ensure that it is aligned with the conjugate branch in time, and obtains the delayed signal z m (n)'.

[0079] Step 202: Using the delayed signal z m (n)' and conjugate signal Perform complex multiplication and coherent accumulation to obtain the autocorrelation function value γ s and the complementary autocorrelation function value c s ,Right now

[0080]

[0081]

[0082] Where L is the accumulation length, which satisfies LT s =δ·2π / Ω d , δ is a positive integer.

[0083] Step 203: Using the autocorrelation function value γ s and the complementary autocorrelation function value c s Calculate the weighting coefficients for IQ imbalance compensation and Right now

[0084] Step 204: Using weighted coefficients and Compensate for the IQ imbalance error and obtain the complex signal s after IQ imbalance error compensation m (n), i.e.

[0085] Step 3: Calculate the normalized channel error compensation value using the complex signal after IQ imbalance error compensation and the IQ imbalance weighting coefficient. The specific process of step 3 is as follows:

[0086] Step 301: Taking the first receiving channel as a reference, calculate the inter-channel amplitude and phase error compensation values ​​of other channels relative to the reference channel. Right now

[0087]

[0088] Where K is the number of calibration samples collected for estimating the inter-channel amplitude and phase error compensation values.

[0089] Step 302: Using the weighting coefficient of IQ imbalance and inter-channel amplitude and phase error compensation values Calculate channel error compensation value Right now

[0090]

[0091]

[0092] Step 303: Calculate the error compensation value of each channel The amplitude of all compensation values ​​is selected.

[0093]

[0094] Step 304: Using the maximum amplitude value as a reference, the channel error compensation value Normalize and get the normalized channel error compensation value Right now

[0095]

[0096] like Figure 3 As shown, performing multi-beam combining on the data of the zero intermediate frequency receiving array channel includes:

[0097] Step 4: Calculate the beam weighting coefficients of the multi-beam according to the coordinates of the M array elements in the array rectangular coordinate system and the beam pointing angles. The specific process of step 4 is as follows:

[0098] Step 401: Based on P beam pointing angles Calculate the direction cosine value corresponding to the pointing angle of each beam That is, for the pth beam, we have

[0099] u p =cos(Ele p )cos(Azip )

[0100] v p =cos(Ele p )sin(Azi p )

[0101] w p =sin(Ele p )

[0102] Step 402: Based on the direction cosine values ​​of P beams and array coordinates (x m ,y m ,z m ),m=1,2,…,M, calculate the multi-beam weighting coefficients:

[0103]

[0104] Where c is the speed of light, α m is the amplitude weighting coefficient.

[0105] Step 5: If the number of beams P = 1, combine the normalized channel error compensation value with the beam weighting coefficient, correct the baseband digital complex signal, perform beam synthesis, and obtain a beam synthesized signal. The specific process of step 5 is as follows:

[0106] Step 501: Normalize the channel error compensation value and beam weighting coefficients Combine to get the modified beam weight coefficient That is, for the mth array element, there is

[0107] Step 502: Modify the beam weighting coefficient Baseband digital complex signals for M receiving channels Perform correction to obtain M corrected complex signals The error compensation method for each channel is the same, including:

[0108] Step 5021: Baseband digital complex signal z m (n) is divided into two paths, one of which is to find the conjugate and obtain the conjugate signal The other branch performs integer multiple delay to ensure that it is aligned with the conjugate branch in time, and obtains the delayed signal z m (n)'.

[0109] Step 5022: Use the modified beam weighting coefficient Baseband digital complex signal Correction is performed to obtain the corrected complex signal s m (n)', i.e.

[0110] Step 503: M corrected complex signals Sum and get the beamformed signal Right now

[0111]

[0112] Step 6: If the number of beams P is greater than 1, the baseband digital complex signals of the M receiving channels are corrected using the normalized channel error compensation value and the multi-beam weighting coefficient, and P beams are formed simultaneously to obtain P beam-synthesized signals. The specific process of step 6 is as follows:

[0113] Step 601: Use the normalized channel error compensation value Baseband digital complex signals for M receiving channels Get the complex signal after M channel error compensation The error compensation method for each channel is the same. For the mth channel, the processing block diagram is as follows: Figure 4 The mid-channel error compensation module is shown, which specifically includes:

[0114] Step 6011: Baseband digital complex signal z m (n) is divided into two paths, one of which is to find the conjugate and obtain the conjugate signal The other branch performs integer multiple delay to ensure that it is aligned with the conjugate branch in time, and obtains the delayed signal z m (n)'.

[0115] Step 6012: Using channel error compensation value and Compensate the channel error and obtain the complex signal s after channel error compensation m (n)”, i.e.

[0116] Step 602: multi-beam weighting coefficients of each channel are calculated as Figure 4 As shown in the multi-beam weighted module, the complex signal after channel error compensation Perform weighting to obtain the multi-beam weighted output signal Right now

[0117] Step 603: sum the weighted output signals of the multi-beams corresponding to the same beam to obtain P beam synthesis signals. Right now

[0118] This paper validates the accuracy of the zero-IF receiver digital array channel calibration and synthesis method through four simulation scenarios. In the simulations, the system operates at an 8 GHz RF frequency, a 30 MHz sampling rate, and a uniform linear array with 16 elements and 11 mm element spacing. The uniform linear array uses uniform weighting.

[0119] Scenario 1: Channel Amplitude and Phase Error Estimation Accuracy

[0120] For a zero-IF receiving array, the channel amplitude error A m The channel phase error is uniformly distributed within 0dB to 1dB. The signal is evenly distributed within ±40 degrees. The carrier frequency of the single-frequency calibration signal is 1 MHz.

[0121] During channel calibration, samples of the baseband digital complex signal of each receiving channel of the array are collected, and the signal-to-noise ratio of the sample is taken as 20dB. The number of samples collected is 10 0 to 10 6 After 1000 simulation experiments, the estimation accuracy of channel amplitude and phase error under different numbers of samples is as follows: Figure 5 and Figure 6 shown.

[0122] As shown in the figure, when the number of sampling points is 100, the mean + 3 times the standard deviation of the channel amplitude error estimate is 0.3452 dB, and the mean + 3 times the standard deviation of the channel phase error estimate is 1.557 degrees. When the signal-to-noise ratio of the channel samples is 20 dB, the number of samples collected for channel amplitude and phase error correction, K = 100, can be selected. The proposed zero-IF receive channel calibration algorithm has high amplitude and phase error estimation accuracy.

[0123] Scenario 2: Image Rejection Ratio for Channel IQ Imbalance

[0124] For the zero-IF receiving array, the carrier frequency of the single-frequency calibration signal is 1 MHz, the signal-to-noise ratio is 20 dB, the amplitude imbalance error is 1 dB, and the phase imbalance error is 5 degrees. Therefore, the image rejection ratio caused by the IQ imbalance error is 22.8 dB.

[0125] The number of sampling points is 3×10 2 to 3×10 6 After 1000 repeated experiments, the image suppression ratio change curve corresponding to different sampling points is as follows: Figure 7 As shown in Figure 2. Before channel IQ imbalance error compensation, the image rejection ratio (IRR) is 22.8dB. When the number of sampling points is 3×10 6When the estimated compensation value is used to compensate for the channel IQ imbalance error, the mean-3 times standard deviation of the image suppression ratio is 70.93dB. When the number of sampling points is small (for example, the number of sampling points is 3000), the mean-3 times standard deviation of the image suppression ratio is approximately 36dB. It can be seen that in order to obtain an accurate compensation value for the channel IQ imbalance error, a large amount of sample data needs to be collected, which makes the IQ imbalance error estimation require a larger storage space than the inter-channel amplitude and phase error estimation. The method proposed in the present invention does not need to store calibration samples for IQ imbalance error estimation, and occupies less storage space.

[0126] Scenario 3: Array normal beam pattern before and after array channel calibration

[0127] For a zero-IF receiving array, the channel amplitude error A m The channel phase error is uniformly distributed within 0dB to 1dB. The IQ imbalance amplitude error g is uniformly distributed within ±15 degrees. m The phase error θ is uniformly distributed between 0.5dB and 1.5dB. m The IQ imbalance amplitude and phase error are uniformly distributed between 0 and 10 degrees, so the image rejection ratio brought by the average value of the IQ imbalance amplitude and phase error is 22.8 dB.

[0128] In order to obtain the normal beam pattern before and after the digital array calibration, the calibration signal uses a single-frequency signal with a radio frequency of 8.001 GHz and an accumulation length of 3×10 6 , ensuring that there are an integer number of single-frequency cycles within the sampling duration. The number of sampling points for inter-channel amplitude and phase error estimation is 100.

[0129] When the channel error is not compensated, the array normal beam pattern corresponding to the target and the mirror signal is as follows: Figure 8 As shown in the figure, compared with the IQ imbalance image suppression level of a single channel, beamforming has no ability to suppress the image components caused by IQ imbalance. The image suppression ratio after beamforming is approximately equal to the average image suppression ratio of a single channel.

[0130] After channel error compensation, the array normal beam pattern corresponding to the target and the mirror signal is as follows: Figure 9 As shown in the figure, channel error compensation improves the image rejection ratio from approximately 22.4dB before compensation to over 68dB. The proposed channel calibration method can further improve the image rejection ratio of the beamforming output.

[0131] Scenario 4: Array channel calibration and simultaneous multi-beam synthesis

[0132] For a zero-IF receiving array, the channel amplitude error A mThe channel phase error is uniformly distributed within 0dB to 1dB. The IQ imbalance amplitude error g is uniformly distributed within ±20 degrees. m The phase error θ is uniformly distributed between 0.5dB and 1.5dB. m The image rejection ratio (IRR) achieved by the average IQ imbalance amplitude and phase error is 22.8 dB, as the distribution is uniform between 0 and 10 degrees. The array simultaneously forms seven beams, uniformly covering a ±30-degree observation area.

[0133] In order to obtain the beam pattern of simultaneous multi-beam after digital array calibration, the calibration signal uses a single-frequency signal with a radio frequency of 8.001 GHz and an accumulation length of 3×10 6 , ensuring that there are an integer number of single-frequency cycles within the sampling duration. The number of sampling points for inter-channel amplitude and phase error estimation is 100.

[0134] When the channel error is not compensated, the multi-beam array beam pattern corresponding to the target and the mirror signal is as follows: Figure 10 As shown in the figure, compared with the IQ imbalance image suppression level of a single channel, beamforming has no ability to suppress the image components caused by IQ imbalance. The image suppression ratio after beamforming is approximately equal to the average image suppression ratio of a single channel.

[0135] After channel error compensation, the multi-beam array beam pattern corresponding to the target and the mirror signal is as follows: Figure 11 As shown in the figure, channel error compensation improves the image rejection ratio from approximately 22.4dB before compensation to over 68dB. The proposed channel calibration method can further improve the image rejection ratio of the beamforming output.

[0136] In summary, the zero-IF receive array channel calibration and synthesis method is simple in principle, requires minimal memory, and is easily implemented. Its performance has been verified through simulation experiments. Therefore, the proposed method can estimate and compensate for both IQ imbalance errors on a channel-by-channel basis and for amplitude and phase errors between channels. It requires minimal memory and is particularly suitable for small-scale digital arrays.

[0137] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A data processing method for a zero-IF receiving digital array channel, characterized in that: The method includes calibrating the data of the zero intermediate frequency receiving array channel and performing multi-beam synthesis on the data of the zero intermediate frequency receiving array channel; the calibrating the data of the zero intermediate frequency receiving array channel includes: Step 1: The digital array has a total of M array elements. The single-frequency calibration signal received by each array element undergoes pre-selection filtering, low-noise amplification, in-phase and quadrature mixing, low-pass filtering, and A / D acquisition in each channel of the zero-IF receiving array to obtain the baseband digital complex signal of the M receiving channels; Step 2: Using the baseband digital complex signals of the M receiving channels, perform IQ imbalance error estimation and compensation for each channel to obtain a complex signal after IQ imbalance error compensation; Step 3: Calculate a normalized channel error compensation value using the complex signal after IQ imbalance error compensation and the IQ imbalance weighting coefficient; The performing multi-beam combining on the data of the zero intermediate frequency receiving array channel includes: Step 4: Calculate the beam weighting coefficients of the multi-beam according to the coordinates of the M array elements in the array rectangular coordinate system and the beam pointing angles; Step 5: If the number of beams P = 1, combine the normalized channel error compensation value with the beam weight coefficient, correct the baseband digital complex signal, perform beamforming, and obtain a beamformed signal; Step 6: If the number of beams P is greater than 1, the baseband digital complex signals of the M receiving channels are corrected using the normalized channel error compensation value and the multi-beam weighting coefficient, and P beams are formed simultaneously to obtain P beam-synthesized signals.

2. The data processing method for a zero-IF receiving digital array channel according to claim 1, characterized in that: The step 1 comprises: The single-frequency calibration signal received by the mth array element is x m (t)=A0cos[(Ω c +Ω d )t+φ0], where φ0 is the initial phase, Ω c is the carrier analog angular frequency of the received signal, A0 is the amplitude of the single frequency signal, Ω d is the simulated angular frequency offset of the single frequency signal and Ω d >0; The baseband digital complex signal of the mth receiving channel is Among them, * is the complex number conjugation operation, represents the baseband digital complex signal obtained by the mth receiving channel that is independent of the IQ imbalance error and A m , are respectively the frequency response of the mth RF front end at frequency Ω d The amplitude and phase values ​​at T s is the sampling frequency of A / D, λ 1,m and λ 2,m denote the first coefficient and the second coefficient respectively, and Among them, g m It is composed of the zero intermediate frequency receiver in-phase local oscillator and quadrature local oscillators The amplitude error caused by the amplitude difference between m It is composed of the zero intermediate frequency receiver in-phase local oscillator and quadrature local oscillators Phase error caused by the phase difference between them; Complex low-pass filters The frequency response at frequency Ω d The amplitude and phase values ​​at Complex low-pass filters The frequency response at frequency-Ω d The amplitude and phase values ​​at ; Complex low-pass filters Relative to The frequency response at frequency Ω d The amplitude and phase values ​​at ; Complex low-pass filters Relative to The frequency response at frequency-Ω d The amplitude and phase values ​​at .

3. The data processing method for a zero-IF receiving digital array channel according to claim 2, characterized in that: The step 2 includes: Step 201: Baseband digital complex signal z m (n) is divided into two paths, one of which is to find the conjugate and obtain the conjugate signal The other channel is delayed by integer multiples to obtain the delayed signal z m (n)'; Step 202: Using the delayed signal z m (n)' and conjugate signal Perform complex multiplication and coherent accumulation to obtain the autocorrelation function value and complementary autocorrelation function values Where L is the accumulation length and LT s =δ·2π / Ω d , δ is a positive integer; Step 203: First weighting coefficient for IQ imbalance compensation Calculate the second weighting coefficient for IQ imbalance compensation Step 2-4: Using the first weighting coefficient and the second weighting coefficient Compensate for the IQ imbalance error and obtain a complex signal after IQ imbalance error compensation 4. The data processing method for a zero-IF receiving digital array channel according to claim 3, characterized in that: The step 3 comprises: Step 301: Taking the first receiving channel as the reference channel, calculate the inter-channel amplitude and phase error compensation values ​​of other channels relative to the reference channel. Right now Where K is the number of calibration samples collected for estimating the inter-channel amplitude and phase error compensation values; Step 302: By formula Calculate channel error compensation value; Step 303: Obtain the amplitude of the error compensation value of each channel And select the maximum value EA max ; Step 304: By formula Normalize the channel error compensation value to obtain the normalized channel error compensation value 5. The data processing method for a zero-IF receiving digital array channel according to claim 1, characterized in that: The step 4 comprises: Step 401: Based on P beam pointing angles Calculate the direction cosine value corresponding to the pointing angle of each beam That is, for the pth beam, we have Among them, Azi p is the azimuth, Ele p is the pitch angle, u p is the direction cosine of the angle between the incident direction and the X-axis in the rectangular coordinate system, v p is the direction cosine of the angle between the incident direction and the Y axis in the rectangular coordinate system, w p is the direction cosine of the angle between the incident direction and the Z axis in the rectangular coordinate system; Step 402: Based on the direction cosine values ​​of P beams and array coordinates (x m ,y m ,z m ),m=1,2,…,M, calculate the weighted coefficients of multi-beam Where c is the speed of light, α m is the amplitude weighting coefficient.

6. The data processing method for a zero intermediate frequency receiving digital array channel according to claim 5, characterized in that: The step 5 comprises: Step 501: Normalize the channel error compensation value and beam weighting coefficients Combine to get the modified beam weight coefficient That is, for the mth array element, there is Step 502: Modify the beam weighting coefficient Baseband digital complex signals for M receiving channels Perform correction to obtain M corrected complex signals Step 503: M corrected complex signals Sum and get the beamformed signal Right now 7. The data processing method for a zero intermediate frequency receiving digital array channel according to claim 6, characterized in that: The step 502 includes: Step 5021: Baseband digital complex signal z m (n) is divided into two paths, one of which is to find the conjugate and obtain the conjugate signal The other channel is delayed by integer multiples to obtain the delayed signal z m (n)'; Step 5022: Use the modified beam weighting coefficient Baseband digital complex signal Correction is performed to obtain the corrected complex signal s m (n)', i.e. .

8. The data processing method for a zero intermediate frequency receiving digital array channel according to claim 6, characterized in that: The step 6 comprises: Step 601: Use the normalized channel error compensation value Baseband digital complex signals for M receiving channels Perform channel error compensation to obtain M complex signals after channel error compensation Step 602: Use the multi-beam weighting coefficients of each channel to compensate the channel error and obtain the complex signal. Perform weighting to obtain the multi-beam weighted output signal Right now Step 603: sum the weighted output signals of the multi-beams corresponding to the same beam to obtain P beam synthesis signals. Right now 9. The data processing method for a zero-IF receiving digital array channel according to claim 8, characterized in that: Step 601 includes: Step 6011: Baseband digital complex signal z m (n) is divided into two paths, one of which is to find the conjugate and obtain the conjugate signal The other channel is delayed by integer multiples to obtain the delayed signal z m (n)'; Step 6012: Using channel error compensation value and Compensate the channel error and obtain the complex signal s after channel error compensation m (n)”, i.e.

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