CN113472371A - Adaptive array antenna digital beam synthesis anti-interference processing method - Google Patents
Adaptive array antenna digital beam synthesis anti-interference processing method Download PDFInfo
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Abstract
The anti-interference processing method for the digital beam synthesis of the adaptive array antenna disclosed by the invention has the advantages of high calculation precision, low processing time delay and strong anti-interference capability. The invention is realized by the following technical scheme: the array multichannel digital intermediate frequency receiving signal output by the ADC module carries out digital down-conversion, digital filtering and time domain tapping through the data preprocessing module to obtain multichannel space-time two-dimensional receiving data, and the autocorrelation matrix calculating module calculates, multiplies and accumulates the space-time two-dimensional receiving data and the conjugate transpose data thereof to obtain an autocorrelation matrix; then, the autocorrelation matrix inversion module adopts the inversion operation of the autocorrelation matrix; the weight coefficient calculation module calculates the self-adaptive weight coefficient in real time by utilizing the self-correlation inverse matrix and the space-time two-dimensional guide vector; and the space-time beam synthesis module performs complex multiplication accumulation on the time-synchronized space-time two-dimensional baseband data and the self-adaptive weight coefficient to obtain a digital signal subjected to anti-interference processing, and the digital signal is subjected to digital-to-analog conversion and up-conversion by the DAC module to output an analog intermediate frequency signal.
Description
Technical Field
The invention relates to the technical field of array signal processing, in particular to a method for realizing self-adaptive array anti-interference.
Background
The adaptive array processing can obviously improve the adaptability of a modern information system in a complex signal environment, and is widely applied to the fields of radar, sonar, navigation and the like. With the increasing number of man-made interference and the increasingly severe electromagnetic environment, the interference resistance is becoming one of the necessary capabilities of the satellite navigation receiver. Because satellite navigation signals are extremely weak when arriving at the ground and are easily interfered intentionally or unintentionally, the traditional single-antenna multi-delay system only resists interference from a time domain, and the interference suppression capability is limited. The array antenna is used for increasing the degree of freedom of a space domain, and the anti-interference performance of the navigation signal receiver can be obviously enhanced through space domain-time domain combined processing. The multiple antennas are placed in different ways, i.e., different patterns, which may result in different spatial interference rejection performance for the navigation receiver. In the current anti-interference technology, the adaptive array antenna occupies a very important position, can dynamically track user signals, and automatically adjust the weighting coefficient of each array element according to the external signal environment, so that the main lobe of a beam directional diagram is aligned to the incoming direction of an expected signal, and the null or lower side lobe is aligned to the incoming direction of an interference signal, thereby achieving the effect of nulling the interference signal and effectively inhibiting the interference signal. The adaptive antenna array is a main branch of the communication anti-interference technology. For a wireless communication system, electronic interference firstly enters a receiving system from an antenna, and the self-adaptive antenna is that a checkpoint is arranged in the antenna, so that a signal of the own party passes through the checkpoint and an interference signal is suppressed under the condition that the interference is much stronger than the signal. However, when the number of interference sources is greater than the degree of freedom of the adaptive array antenna, the adaptive array antenna cannot suppress strong interference. In a coherent environment (such as urban multipath environment in a cellular mobile communication system), the existence of coherent interference can cause the desired signal in the array to be canceled, the adaptive array performance can be drastically degraded, and a common processing method is spatial smoothing. However, adaptive arrays employing conventional uniform spatial smoothing have poor coherent interference rejection and suffer from loss of array aperture. The square array, the rectangular array and the Y-shaped array are three common satellite navigation anti-interference array structures. Antenna factors influence the anti-interference performance of the array, and for the antennas, array cross coupling and unit inconsistency are main factors causing the anti-interference performance of the array to be reduced. In satellite navigation anti-interference, a traditional adaptive beam forming algorithm forms a null in an interference direction, so that interference is suppressed. However, when the signal source is adjacent to the interference source in time domain and space domain, the traditional adaptive beamforming algorithm may cause beam distortion, and the desired signal may be suppressed, resulting in poor detection. The estimation error of the array covariance matrix caused by limited sub-sampling adopted by the algorithm, the existence of coherent interference signals and the like can cause the performance degradation of the adaptive beam former, and the high calculation complexity of the existing algorithm also limits the application of the algorithm to a great extent.
In the array anti-interference technology, adaptive anti-interference algorithms evolve corresponding adaptive processing algorithms more and more according to different optimization targets, and the adaptive processing algorithms include a Power Inversion (PI) algorithm, a beam control (BS) algorithm, a Minimum Mean Square Error (MMSE) algorithm, a minimum variance distortion free (MVDR) algorithm, a Linear Constraint Minimum Variance (LCMV) algorithm and the like. The application conditions and the formed directional diagrams required by different adaptive anti-interference algorithms are different, and the adaptive anti-interference algorithms have advantages and disadvantages in performance and calculation amount and are different in anti-interference performance and difficulty in implementation. Therefore, when the adaptive anti-interference algorithm is applied to actual engineering, a proper adaptive anti-interference algorithm is selected according to the conditions and requirements of an application scene. The adaptive antenna system of the power inversion algorithm is particularly suitable for occasions with weak signals and strong interference, such as a satellite navigation system. However, when there is an interference signal, the power inversion array has a suppression effect only when the interference signal power is large to a certain extent. Since the power inversion array does not distinguish between a desired signal and an interfering signal, the output power of the array is minimized as much as possible. In a satellite navigation system, a useful signal is buried deeply under noise, and an interference signal is generally strong to have an interference effect. When the power of the interference signal is smaller, the power of the output interference signal is increased along with the increase of the input interference signal, and the power inversion array is in an inoperative state at the moment; when the interference signal power is higher than a certain threshold, the stronger the input interference signal is, the smaller the output interference signal power is, which is a characteristic of power inversion. In addition, the saturation distortion of the radio frequency front end under the condition of high power can also cause the reduction of cancellation performance. In a coherent environment, a beamforming algorithm based on the Linear Constrained Minimum Variance (LCMV) criterion will fail and array performance will drop dramatically. In addition, the direction-of-arrival estimation resolution is also poor when the spatial angle interval of the signal is small and the SNR is low.
At present, the implementation methods of adaptive array anti-interference mainly include a Least Mean Square (LMS) method, a Recursive Least Square (RLS) method, and a direct matrix inversion (SMI) method. The LMS method is a closed-loop algorithm, the operation amount of the method is small, the engineering is easy to realize, but the convergence rate of the LMS method is influenced by the dispersion of the characteristic values of the autocorrelation matrix, the convergence rate is low, the depth of the formed null is relatively shallow, and the anti-interference capability is weak. The convergence characteristic of the RLS method is much better than that of the LMS method, the convergence speed is higher, and the RLS method has better numerical stability, but the RLS method has obviously increased operation amount compared with the LMS method, so that the engineering realization difficulty is higher. The SMI method carries out covariance estimation on sampling snapshot data and matrix inversion operation, and has the advantages of deepest formed null and best anti-interference performance. In practical application, an interference signal environment is often complex, such as multipath effect or interference intentionally implemented in communication, and at this time, performance of a conventional adaptive beamforming method is seriously degraded, and a signal subspace and a noise subspace of a coherent signal source are mutually permeated, so that some super-resolution subspace algorithms, such as multiple signal classification (MUSIC) and signal parameter Estimation (ESPRIT) by using a rotation invariant technology, fail to effectively resolve or direction-finding a coherent signal.
In order to make the adaptive anti-interference algorithm exert the best performance, the rapid implementation of the complex matrix inversion operation in the SMI method needs to be broken through. Although the inversion operation of the matrix can be realized through the DSP or the ARM, the system has high power consumption and large processing time delay, and cannot meet the real-time requirement of engineering application. The traditional FPGA realizes matrix inversion operation, and has the disadvantages of long development period, low operation precision, high resource consumption and incapability of meeting the actual requirement.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the invention provides an adaptive array antenna digital beam synthesis anti-interference processing method which is high in calculation precision, low in processing time delay and strong in anti-interference capability.
The above object of the present invention can be achieved by the following technical solutions:
an anti-interference processing method for digital beam synthesis of an adaptive array antenna has the following technical characteristics: an FPGA software module for quickly realizing the anti-interference of the array is formed on the basis of the data preprocessing module, the anti-interference processing module and the system calibration processing module; the data preprocessing module firstly carries out digital down-conversion and digital filtering on a digital intermediate frequency signal received by multiple channels, obtains multi-channel space-time two-dimensional receiving data by utilizing a time domain tap, and calculates, multiplies and accumulates the space-time two-dimensional data and conjugate transpose data thereof to obtain an autocorrelation matrix; meanwhile, the system calibration processing module calculates a space-time two-dimensional guide vector of the incident direction of the received signal by using the channel calibration result and the antenna calibration result; then the anti-interference processing module adopts Vivado HLS technology to realize fast high-precision inverse operation of the autocorrelation matrix to obtain the inverse matrix of the autocorrelation matrix; obtaining an adaptive anti-interference algorithm of optimal beam forming by adopting a Lagrange multiplier method, calculating an adaptive weight coefficient in real time by utilizing an autocorrelation inverse matrix and a space-time two-dimensional steering vector according to the adaptive anti-interference algorithm, carrying out digital beam forming on a full array by utilizing the phase relation among the sub-arrays, calculating the cache time of space-time two-dimensional baseband data according to the array element number and the time-domain tap number, caching a self-adaptive data cache queue, caching the space-time two-dimensional baseband data, aligning the self-adaptive weight coefficient of digital beam forming with the space-time two-dimensional baseband data at the corresponding moment in time, outputting the baseband data which is time-synchronous with the adaptive weight coefficient, carrying out complex multiplication accumulation on the space-time two-dimensional baseband data which is time-synchronous with the self-adaptive weight coefficient, realizing the adaptive anti-interference in an FPGA, outputting the digital signal of the beam forming and converting the digital signal into an analog signal by DAC, and performing analog up-conversion processing, performing power matching setting, and outputting the analog intermediate-frequency signal subjected to anti-interference processing, thereby quickly realizing the anti-interference processing on the self-adaptive array signal.
Compared with the prior art, the invention has the following beneficial effects:
the invention is based on the data preprocessing module, the system calibration processing module, the anti-interference processing module and other constituent units. The data preprocessing module firstly carries out digital down-conversion and digital filtering on a digital intermediate frequency signal received by multiple channels, obtains multi-channel space-time two-dimensional receiving data by utilizing a time domain tap, and calculates, multiplies and accumulates the space-time two-dimensional data and conjugate transpose data thereof to obtain an autocorrelation matrix; transform preprocessing is adopted to avoid inhibiting the expected signals; meanwhile, incoherent interference and coherent interference are restrained, and self-adaptive null filtering in the interference direction is better realized. The development efficiency of matrix inversion operation is improved through a Vivado HLS technology, and meanwhile, the matrix inversion operation is realized by adopting an FPGA (field programmable gate array), so that the processing time delay is reduced, and the real-time performance is improved; and performing beam forming on the full array by utilizing the phase relation among the sub-arrays, and buffering the space-time two-dimensional baseband data by designing a self-adaptive data buffer queue so as to perform digital beam synthesis in time alignment on the self-adaptive weight coefficient and the space-time two-dimensional baseband data at the corresponding moment. The results show that: through self-adaptive processing, the antenna array can completely and automatically form a null in a strong interference direction to inhibit interference, so that a satisfactory output signal-to-noise ratio is obtained.
The adaptive anti-interference algorithm adopted by the invention utilizes an autocorrelation inverse matrix and a space-time two-dimensional guide vector to calculate an adaptive weight coefficient in real time, utilizes the phase relation among sub-arrays to form wave beams for the whole array, calculates the cache time of space-time two-dimensional baseband data according to the array element number and the time domain tap number, caches the space-time two-dimensional baseband data, time aligns the adaptive weight coefficient synthesized by digital wave beams with the space-time two-dimensional baseband data at the corresponding moment, outputs the baseband data in time synchronization with the adaptive weight coefficient, greatly improves the coherent interference suppression performance of the array, and avoids aperture loss generated by space smoothing. Theoretical analysis and simulation results show that: the adaptive array antenna array can adjust the direction of the antenna in real time, so that the main beam of the antenna is aligned to the direction of the expected signal, the null is aligned to the interference direction to suppress the interference signal,
the invention adopts the time synchronization space-time two-dimensional baseband data and the self-adaptive weight coefficient to carry out complex multiplication accumulation to obtain the self-adaptive anti-interference output beam-forming digital signal, thereby improving the output signal-to-interference-and-noise ratio and the robustness. Under the environment of interference and low signal-to-noise ratio, the error rate of the antenna can be greatly reduced, and the antenna has stronger anti-interference performance. Simulation results show that in a coherent interference environment, a directional diagram has an obvious main lobe which is favorable for receiving an expected signal in the direction of the expected signal, and a relatively high and relatively flat output signal-to-interference-and-noise ratio can be kept; the quick implementation method is not only suitable for a satellite navigation system and a satellite communication system, but also suitable for other array anti-interference processing systems.
Drawings
Fig. 1 is a schematic block diagram of a software module circuit for anti-interference processing of adaptive array antenna digital beam synthesis of the present invention.
Fig. 2 is a schematic view of the interference rejection process of fig. 1.
FIG. 3 is a schematic diagram of a process flow for fast implementation of matrix inversion according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to specific embodiments.
See fig. 1. According to the invention, an array anti-interference fast-realization FPGA software module is formed based on a data preprocessing module, an anti-interference processing module and a system calibration processing module; the data preprocessing module firstly carries out digital down-conversion and digital filtering on a digital intermediate frequency signal received by multiple channels, obtains multi-channel space-time two-dimensional receiving data by utilizing a time domain tap, and calculates, multiplies and accumulates the space-time two-dimensional data and conjugate transpose data thereof to obtain an autocorrelation matrix; meanwhile, the system calibration processing module calculates a space-time two-dimensional guide vector of the incident direction of the received signal by using the channel calibration result and the antenna calibration result; then the anti-interference processing module adopts Vivado HLS technology to realize fast high-precision inverse operation of the autocorrelation matrix to obtain the inverse matrix of the autocorrelation matrix; obtaining an adaptive anti-interference algorithm of optimal beam forming by adopting a Lagrange multiplier method, calculating an adaptive weight coefficient in real time by utilizing an autocorrelation inverse matrix and a space-time two-dimensional steering vector according to the adaptive anti-interference algorithm, performing beam forming on a full array by utilizing a phase relation among subarrays, calculating the cache time of space-time two-dimensional baseband data according to the number of array elements and the number of time-domain taps, caching the space-time two-dimensional baseband data in a self-adaptive data cache queue, performing time alignment on the adaptive weight coefficient of digital beam forming and the space-time two-dimensional baseband data at the corresponding moment, outputting the baseband data in time synchronization with the adaptive weight coefficient, performing complex multiplication accumulation on the space-time two-dimensional baseband data in time synchronization and the adaptive weight coefficient, obtaining the adaptive anti-interference in an FPGA, outputting a digital signal of beam forming and converting the digital signal into an analog signal through DAC (digital-to analog conversion), and performing analog up-conversion processing, performing power matching setting, and outputting the analog intermediate-frequency signal subjected to anti-interference processing, thereby quickly realizing the anti-interference processing on the self-adaptive array signal.
The data preprocessing module comprises: the device comprises a DDC module, an autocorrelation matrix calculation module and an array multi-channel digital intermediate frequency receiving signal which are connected in parallel, wherein space-time two-dimensional receiving data are obtained through the DDC module, an autocorrelation matrix is calculated through the autocorrelation matrix calculation module, the product of N groups of continuous space-time two-dimensional sampling data and conjugate transpose data of the sampling data is solved for statistical averaging, and matrix inversion operation is achieved to obtain an autocorrelation inverse matrix.
The DDC module comprises a down-conversion module, a digital filtering module and a time domain tap module, wherein the down-conversion module configures the frequency of a direct digital frequency synthesizer (DDS) according to the frequency point of a digital intermediate frequency signal and generates sine and cosine signals, and then the sine and cosine signals are multiplied by the digital intermediate frequency signal respectively to realize digital down-conversion to obtain I-path and Q-path digital baseband signals; the digital filtering module designs a low-pass filter of finite length unit impulse response (FIR) according to the bandwidth of the received signal, and performs low-pass filtering processing on the I path and Q path digital baseband signals after digital down-conversion to obtain digital baseband signals after digital filtering; and the time domain tap module performs time delay on the digital baseband signal according to the time domain tap coefficient to obtain space-time two-dimensional baseband data.
In the calculation of the autocorrelation matrix, the autocorrelation matrix calculation module obtains the following autocorrelation matrix R of the space-time two-dimensional data according to the number N of sampling points of the multi-channel space-time two-dimensional data and the multi-channel space-time two-dimensional data matrix X with the number N of the sampling points:
wherein, XHAnd the conjugate transpose matrix represents a multi-channel space-time two-dimensional data matrix with N sampling points.
The anti-interference processing module includes: the self-correlation matrix inversion module firstly converts a self-correlation matrix R of a fixed point data type into a self-correlation matrix R of a floating point data typefloatThen, fast high-precision inversion operation of the autocorrelation matrix is realized by utilizing a matrix inversion FPGAIP core obtained by the VivadoHLS technology, and the autocorrelation inverse matrix of the floating point data type is output
Finally, the autocorrelation inverse matrix of the floating point data type
Autocorrelation inverse matrix R converted to fixed-point data type-1。
The autocorrelation matrix inversion module generates an FPGA IP core of matrix inversion by utilizing a Vivado HLS technology, wherein in the generation of the FPGA IP core of matrix inversion, C/C + + language is used for quickly modeling matrix inversion operation, then an optimization strategy is designed according to requirements such as processing delay, resource consumption and throughput, and finally the C/C + + model of matrix inversion is converted to an RTL model which can be realized on an FPGA to obtain the FPGA IP core of matrix inversion.
And the self-adaptive data caching module calculates the caching time and the self-adaptive weight coefficient of the space-time two-dimensional baseband data according to the array element number, the baseband data and the time domain tap number, aligns the self-adaptive weight coefficient with the output baseband data in time, outputs the baseband data with synchronous time, and realizes the time synchronous matching of the self-adaptive weight coefficient and the baseband data at the corresponding moment.
And the weight coefficient calculation module adaptively selects an array anti-interference algorithm according to the system requirements or whether the space-time two-dimensional guide vector is effective, and calculates an adaptive weight coefficient in real time according to the autocorrelation inverse matrix and the space-time two-dimensional guide vector.
When the system can not obtain the direction information of the received signal or the space-time two-dimensional guide vector is invalid, the weight coefficient calculation module selects a Power Inversion (PI) array anti-interference algorithm and utilizes an autocorrelation inverse matrix R-1Calculating an optimal weight coefficient:
wherein b is a constraint vector [1,0, …,0 ]]TAnd u is a constant.
When the system acquires the direction information of the received signal and the space-time two-dimensional guide vector is available, the weight coefficient calculation module selects a minimum variance distortion free response (MVDR) array anti-interference algorithm and an autocorrelation inverse matrix R-1The following optimal weight system is calculated:
wherein s is a space-time two-dimensional guide vector, and u is a constant.
The space-time beam synthesis module carries out complex multiplication accumulation on time-synchronous multi-channel space-time two-dimensional baseband data and space-time self-adaptive weight coefficientTime domain filtering and space domain filtering are realized, the digital signal of self-adaptive anti-interference output is obtained by utilizing the following calculation formula,
wherein, wHAnd (3) representing the conjugate of the space-time two-dimensional self-adaptive weight coefficient, wherein X is space-time two-dimensional baseband data, M is the number of array elements, and P is the number of time-domain taps.
Refer to fig. 2 and 3. The radio frequency signal which is received by an array antenna and contains a useful signal, an interference signal and a noise signal is converted into a digital intermediate frequency receiving signal through an array multi-channel, the digital intermediate frequency receiving signal is converted into a multi-channel analog intermediate frequency receiving signal through amplification, filtering and down-conversion processing, then the multi-channel analog intermediate frequency receiving signal is synchronously sampled by a multi-channel ADC (analog to digital converter) sampling module and is sent into an FPGA (field programmable gate array) software module, the synchronous sampling signal firstly enters a DDC (direct digital synthesizer) module through a data preprocessing module for processing, at least four paths of digital intermediate frequency signals input by the ADC sampling module are subjected to parallel digital down-conversion, digital filtering and time domain tap data preprocessing, the DDC module firstly configures the frequency of a direct digital frequency synthesizer (DDS) according to the frequency point of the digital intermediate frequency signal and generates sine and cosine signals, then the sine and cosine signals are respectively multiplied by the digital intermediate frequency signal to obtain I-path and Q-path digital baseband signals, and the time domain tap module performs time delay on the digital baseband signal according to the time domain tap coefficient to obtain space-time two-dimensional baseband data.
The DDS sends the obtained I path and Q path digital baseband signals to a finite impulse response FIR low pass filter of finite length unit impulse response for filtering, a digital signal processing system based on FPGA calculates a fixed number of sampling values, each output value realized in parallel is subjected to digital down-conversion through a digital down-converter, the I path and Q path digital baseband signals after the digital down-conversion are subjected to low pass filtering processing to obtain spatial domain digital baseband signals after the digital filtering, and a time domain tap module carries out time domain tap processing on the digital spatial domain baseband signals according to a time domain tap coefficient to obtain space-time two-dimensional baseband data sent to an adaptive data cache module and a self-correlation matrix calculation module. Adaptive data cache module rootAnd calculating the cache time of the space-time two-dimensional baseband data by the data array element number and the time domain tap number, and outputting the baseband data which is time-synchronous with the self-adaptive weight coefficient. And the autocorrelation matrix output by the autocorrelation matrix calculation module is divided into two paths and respectively sent to a system calibration processing module and an anti-interference processing module, the system calibration processing module utilizes the 1 st column correlation value of the autocorrelation matrix of the channel calibration module to carry out standardization processing to obtain the amplitude-phase error coefficient among multiple channels, the amplitude-phase error coefficient is output to a space-time steering vector calculation module as a channel calibration result, the channel calibration result is sent to the space-time steering vector calculation module, and the antenna calibration module inquires array antenna response data stored locally according to the direction information of the received signal to obtain the array antenna response in the current direction. The space-time guide vector calculation module calculates a space-time two-dimensional guide vector in the current signal receiving direction in real time according to an antenna calibration result, a channel calibration result and a time domain guide vector which are input by the antenna calibration module, and sends the space-time two-dimensional guide vector in the incident direction of the array antenna receiving signal to the weight coefficient calculation module in the anti-interference processing module, and the weight coefficient calculation module converts an autocorrelation matrix R of a fixed point data type into an autocorrelation matrix R of a floating point data type by using the autocorrelation matrix inversion modulefloatThe optimization strategy of the Vivado HLS technology and the C/C + + model of matrix inversion are adopted, the C/C + + model is converted into an RTL hardware model, the fast floating point inversion operation of the autocorrelation matrix is realized through the FPGA IP core of matrix inversion, and the inverse matrix of the autocorrelation matrix of the floating point data type is obtained
The matrix inversion FPGA IP core inverts the autocorrelation matrix of the floating point data type according to the data type
Converting the floating point into the fixed point to the floating point, and converting the floating point into the fixed point to obtain the autocorrelation inverse matrix R through data type conversion-1. The weight coefficient calculation module adaptively selects an array anti-interference algorithm according to system requirements or whether the space-time two-dimensional steering vector is effective or not, and according to the autocorrelation inverse matrix and the space-time two-dimensional steering vectorThe guide vector calculates the self-adaptive weight coefficient of the self-correlation inverse matrix and the space-time two-dimensional guide vector in real time, and sends the self-adaptive weight coefficient to the space-time beam synthesis module, extracts the space-time two-dimensional baseband data and the weight coefficient after the self-adaptive data caching module caches the self-adaptive data, and performs complex multiplication accumulation on the multi-channel space-time two-dimensional baseband data and the self-adaptive weight coefficient to realize time domain filtering and space domain filtering and obtain a self-adaptive anti-interference output digital signal. The digital signal after the self-adaptive anti-interference processing is converted into an analog signal through DAC digital-to-analog conversion, then the analog signal is subjected to analog up-conversion processing and power matching setting, and an analog intermediate-frequency signal after the anti-interference processing is output, so that the anti-interference processing of the self-adaptive array signal is quickly realized.
The adaptive anti-interference algorithm adopted by the weight coefficient calculation module includes, but is not limited to, a power inversion algorithm (PI), a minimum variance distortionless response algorithm (MVDR), and other adaptive array anti-interference algorithms.
The array antenna can be a four-element passive antenna, and the number of the elements includes but is not limited to a four-element array antenna, and also includes array antennas with other element numbers; the array element arrangement form includes, but is not limited to, a uniform linear array, a uniform circular array, and other arrangement forms.
While there has been described and illustrated what are considered to be example embodiments of the present invention, those skilled in the art will recognize that many variations are possible in light of the above description, and thus the present embodiment is intended to be illustrative only of one or more specific embodiments. It will be apparent to those skilled in the art that various modifications can be made without departing from the spirit of the invention. In addition, many modifications may be made to adapt a particular situation to the teachings of the present invention without departing from the central concept described herein. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed, but that the invention will include all embodiments and equivalents falling within the scope of the invention.
Claims (10)
1. An anti-interference processing method for digital beam synthesis of an adaptive array antenna has the following technical characteristics: an FPGA software module for quickly realizing the anti-interference of the array is formed on the basis of the data preprocessing module, the anti-interference processing module and the system calibration processing module; the data preprocessing module firstly carries out digital down-conversion and digital filtering on a digital intermediate frequency signal received by multiple channels, obtains multi-channel space-time two-dimensional receiving data by utilizing a time domain tap, and calculates, multiplies and accumulates the space-time two-dimensional data and conjugate transpose data thereof to obtain an autocorrelation matrix; meanwhile, the system calibration processing module calculates a space-time two-dimensional guide vector of the incident direction of the received signal by using the channel calibration result and the antenna calibration result; then the anti-interference processing module adopts Vivado HLS technology to realize fast high-precision inverse operation of the autocorrelation matrix to obtain the inverse matrix of the autocorrelation matrix; obtaining an adaptive anti-interference algorithm of optimal beam forming by adopting a Lagrange multiplier method, calculating an adaptive weight coefficient in real time by utilizing an autocorrelation inverse matrix and a space-time two-dimensional steering vector according to the adaptive anti-interference algorithm, carrying out digital beam forming on a full array by utilizing the phase relation among the sub-arrays, calculating the cache time of space-time two-dimensional baseband data according to the array element number and the time-domain tap number, caching a self-adaptive data cache queue, caching the space-time two-dimensional baseband data, aligning the self-adaptive weight coefficient of digital beam forming with the space-time two-dimensional baseband data at the corresponding moment in time, outputting the baseband data which is time-synchronous with the adaptive weight coefficient, carrying out complex multiplication accumulation on the space-time two-dimensional baseband data which is time-synchronous with the self-adaptive weight coefficient, realizing the adaptive anti-interference in an FPGA, outputting the digital signal of the beam forming and converting the digital signal into an analog signal by DAC, and performing analog up-conversion processing, performing power matching setting, and outputting the analog intermediate-frequency signal subjected to anti-interference processing, thereby quickly realizing the anti-interference processing on the self-adaptive array signal.
2. The adaptive array antenna digital beam forming interference rejection processing method of claim 1, wherein: the data preprocessing module comprises: the device comprises a DDC module, an autocorrelation matrix calculation module and an array multi-channel digital intermediate frequency receiving signal which are connected in parallel, wherein space-time two-dimensional receiving data are obtained through the DDC module, an autocorrelation matrix is calculated through the autocorrelation matrix calculation module, the product of N groups of continuous space-time two-dimensional sampling data and conjugate transpose data of the sampling data is solved for statistical averaging, and matrix inversion operation is achieved to obtain an autocorrelation inverse matrix.
3. The adaptive array antenna digital beam forming interference rejection processing method of claim 2, wherein: the DDC module comprises a down-conversion module, a digital filtering module and a time domain tap module, wherein the down-conversion module configures the frequency of a direct digital frequency synthesizer (DDS) according to the frequency point of a digital intermediate frequency signal and generates sine and cosine signals, and then the sine and cosine signals are multiplied by the digital intermediate frequency signal respectively to realize digital down-conversion to obtain I-path and Q-path digital baseband signals.
4. The adaptive array antenna digital beam forming interference rejection process of claim 3, wherein: the digital filtering module designs a low-pass filter of finite length unit impulse response (FIR) according to the bandwidth of the received signal, and performs low-pass filtering processing on the I path and Q path digital baseband signals after digital down-conversion to obtain digital baseband signals after digital filtering; and the time domain tap module performs time delay on the digital baseband signal according to the time domain tap coefficient to obtain space-time two-dimensional baseband data.
5. The adaptive array antenna digital beam forming interference rejection processing method of claim 2, wherein: in the calculation of the autocorrelation matrix, the autocorrelation matrix calculation module obtains the following autocorrelation matrix R of the space-time two-dimensional data according to the number N of sampling points of the multi-channel space-time two-dimensional data and the multi-channel space-time two-dimensional data matrix X with the number N of the sampling points:
wherein, XHAnd the conjugate transpose matrix represents a multi-channel space-time two-dimensional data matrix with N sampling points.
6. The adaptive array antenna digital beam forming interference rejection processing method of claim 1, wherein: the anti-interference processing module includes: the self-correlation matrix inversion module firstly converts a self-correlation matrix R of a fixed point data type into a self-correlation matrix R of a floating point data typefloatThen, fast high-precision inversion operation of the autocorrelation matrix is realized by utilizing a matrix inversion FPGAIP core obtained by the VivadoHLS technology, and the autocorrelation inverse matrix of the floating point data type is output
Finally, the autocorrelation inverse matrix of the floating point data type
Autocorrelation inverse matrix R converted to fixed-point data type-1。
7. The adaptive array antenna digital beam forming interference rejection processing method of claim 6, wherein: the autocorrelation matrix inversion module generates an FPGA IP core of matrix inversion by utilizing a Vivado HLS technology, wherein in the generation of the FPGA IP core of matrix inversion, C/C + + language is used for quickly modeling matrix inversion operation, then an optimization strategy is designed according to requirements such as processing delay, resource consumption and throughput, and finally the C/C + + model of matrix inversion is converted to an RTL model which can be realized on an FPGA to obtain the FPGA IP core of matrix inversion.
8. The adaptive array antenna digital beam forming interference rejection processing method of claim 6, wherein: the self-adaptive data caching module calculates the caching time and the self-adaptive weight coefficient of the space-time two-dimensional baseband data according to the array element number, the baseband data and the time domain tap number, aligns the self-adaptive weight coefficient with the output baseband data in time, outputs the baseband data with synchronous time, and realizes the time of the self-adaptive weight coefficient and the baseband data at the corresponding momentSynchronously matching; the weight coefficient calculation module adaptively selects an array anti-interference algorithm according to system requirements or whether the space-time two-dimensional guide vector is effective or not, and calculates an adaptive weight coefficient in real time according to the autocorrelation inverse matrix and the space-time two-dimensional guide vector; when the system can not obtain the direction information of the received signal or the space-time two-dimensional guide vector is invalid, the weight coefficient calculation module selects the power inversion PI array anti-interference algorithm and utilizes the autocorrelation inverse matrix R-1Calculating an optimal weight coefficient:
when the system acquires the direction information of the received signal and the space-time two-dimensional guide vector is available, the weight coefficient calculation module selects the minimum variance distortionless response MVDR array anti-interference algorithm and the autocorrelation inverse matrix R-1The following optimal weight system is calculated:
wherein b is a constraint vector [1,0, …,0 ]]TU is a constant and s is a space-time two-dimensional director.
9. The adaptive array antenna digital beam forming interference rejection processing method of claim 5, wherein: the space-time beam synthesis module performs complex multiplication accumulation on the time-synchronized multi-channel space-time two-dimensional baseband data and the space-time adaptive weight coefficient to realize time domain filtering and space domain filtering, and obtains a digital signal of adaptive anti-interference output by utilizing the following calculation formula,
wherein, wHRepresents the conjugate of the self-adaptive weight coefficient of the space-time two-dimension, X is space-time two-dimension baseband data,m is the number of array elements and P is the number of time-domain taps.
10. The adaptive array antenna digital beam forming interference rejection processing method of claim 1, wherein: the radio frequency signal which is received by an array antenna and contains a useful signal, an interference signal and a noise signal is converted into a digital intermediate frequency receiving signal through an array multi-channel, the digital intermediate frequency receiving signal is converted into a multi-channel analog intermediate frequency receiving signal through amplification, filtering and down-conversion processing, then the multi-channel analog intermediate frequency receiving signal is synchronously sampled by a multi-channel ADC (analog to digital converter) sampling module and is sent into an FPGA (field programmable gate array) software module, the synchronous sampling signal firstly enters a DDC (direct digital synthesizer) module through a data preprocessing module for processing, at least four paths of digital intermediate frequency signals input by the ADC sampling module are subjected to parallel digital down-conversion, digital filtering and time domain tap data preprocessing, the DDC module firstly configures the frequency of a direct digital frequency synthesizer (DDS) according to the frequency point of the digital intermediate frequency signal and generates sine and cosine signals, then the sine and cosine signals are respectively multiplied by the digital intermediate frequency signal to obtain I-path and Q-path digital baseband signals, and the time domain tap module performs time delay on the digital baseband signal according to the time domain tap coefficient to obtain space-time two-dimensional baseband data.
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