Radio astronomical radio frequency interference suppression method and system

Abstract

The invention discloses a radio astronomy radio frequency interference suppression method and system, and the method is realized based on adaptive digital filtering and spatial domain-frequency domain combined filtering, and comprises the following steps: S1, a feed source cabin receives an antenna surface reflection signal, divides the antenna surface reflection signal into two polarization signals in a vertical direction and a horizontal direction, carries out the filtering processing, and converts the polarization signals into optical signals; s2, optimizing the optical signal through an adaptive digital filtering suppression radio frequency interference algorithm in combination with the characteristics of an antenna array; s3, processing the signal through a spatial domain-frequency domain combined filtering algorithm, and suppressing interference and noise in other directions; s4, the processed astronomical signals are used for real-time observation on a display terminal of the man-machine interaction module or stored in a server for subsequent processing and analysis. According to the method and the system, ground communication signal interference is dynamically suppressed, and the directional gain of a target astronomical signal is improved, so that the problem of insufficient signal-to-noise ratio (SNR) caused by radio frequency interference (RFI) and noise in a traditional observation system is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of radio astronomy observation and radio frequency signal processing, and in particular to a radio frequency interference suppression method and system based on adaptive digital filtering and spatial-frequency domain joint filtering. Background Art

[0002] (1) Traditional RF interference suppression technology The commonly used RF interference suppression methods in the field of radio astronomy include: Static filters: Use bandpass or notch filters with fixed parameters to filter interference within a preset frequency band. For example, some systems use a primary filter module to perform initial signal processing but cannot dynamically adapt to changes in interference frequency.

[0003] Spatial beamforming: Use antenna arrays to form directional beams to enhance the directional gain of target signals.

[0004] Long integration time: reduces the impact of white noise by extending the observation time, but is ineffective for transient signals (such as fast radio bursts) and cannot solve the problem of structured interference.

[0005] (2) Representative solutions of existing technologies Fixed parameter filtering and spectrum shielding rely on predefined interference templates, lack real-time performance, and cannot cope with dynamic interference (such as 5G signal frequency hopping).

[0006] Single-dimensional processing, some systems only focus on frequency domain or spatial domain filtering.

[0007] Interferometer array technology relies on hardware shielding for its anti-interference capability and has poor adaptability to complex electromagnetic environments.

[0008] The existing technologies for radio astronomy observations mainly have the following defects: Insufficient dynamic adaptability: Traditional filter parameters are fixed and cannot respond to changes in interference frequency in real time (such as dynamic adjustment of satellite communication frequency bands), resulting in loss of effective signals or residual interference.

[0009] Lack of multi-dimensional collaboration: Existing methods mostly process frequency domain or spatial domain interference independently and lack joint optimization.

[0010] Strong dependence on reference signals: Some adaptive filtering technologies require independent reference signals (such as interference monitoring antennas). It is difficult to obtain pure references in complex electromagnetic environments, which affects the algorithm's convergence speed and accuracy.

[0011] High computational complexity: Joint spatial-frequency domain processing of large-scale antenna arrays requires real-time adjustment of tens of thousands of channel parameters. Existing systems struggle to meet millisecond-level response requirements, resulting in insufficient real-time performance. Summary of the Invention

[0012] To address the challenges of existing technologies, the present invention aims to provide a method and system for radio frequency interference (RFI) suppression based on adaptive digital filtering and joint spatial-frequency filtering. This method and system are suitable for high-sensitivity signal reception in radio telescope arrays operating in complex electromagnetic environments. This technology dynamically suppresses interference from ground-based communication signals and improves the directional gain of target astronomical signals, addressing the insufficient signal-to-noise ratio (SNR) in traditional observation systems caused by radio frequency interference (RFI) and noise.

[0013] To achieve the above objectives, the present invention provides a method for suppressing radio astronomy radio frequency interference, which is based on adaptive digital filtering and spatial-frequency domain joint filtering and includes the following steps: S1. The feed cabin receives the reflected signal from the antenna surface, splits it into two polarized signals, vertically and horizontally, filters them separately, and converts them into optical signals. S2. Optimize the optical signal using an adaptive digital filtering algorithm to suppress radio frequency interference, taking into account the characteristics of the antenna array. S3. Process the signal using a joint spatial-frequency filtering algorithm to suppress interference and noise from other directions. S4. The processed astronomical signals can be observed in real time on the human-computer interaction module display terminal or saved to a server for subsequent processing and analysis. The saved data conforms to astronomical data format standards and can be developed and studied using a variety of signal processing tools.

[0014] Furthermore, step S1 specifically includes: The S1.1 feed cabin receives the reflected signal from the antenna surface and divides it into two polarized signals, vertical and horizontal, for separate processing. S1.2 Filter 1 is a 1089-1536MHz bandpass filter, through which the signal is selected to be observed at a frequency of 1GHz-1.5GHz. Amplifier 1 is a precision active amplifier that amplifies weak signals. S1.3 Filter 2 is a 1050-1450MHz bandpass filter, and the bias voltage adds a DC component to the electrical signal; S1.4 filter 3 is a 1050-1450MHz bandpass filter, and amplifier 2 is a precision active amplifier; S1.5 filter 4 is a 1050-1450MHz bandpass filter, and amplifier 3 is a precision active amplifier; they are combined to amplify weak astronomical signals. The S1.6 electro-optical converter converts the electrical signal into an optical signal, which is then transmitted to the processing device via optical fiber for subsequent algorithm processing.

[0015] Further, step S2 specifically includes: S2.1, first divide the signal received by the radio telescope into three parts: the desired astronomical signal, the ground communication interference signal, and the system noise signal; S2.2 receives 1GHz-1.5GHz ground communication signals through an independent communication antenna to obtain reference signals ; S2.3 uses adaptive filtering to make the reference signal close to the ground communication interference signal.

[0016] Furthermore, the reference signal is not completely identical to the ground communication interference signal, but is correlated.

[0017] Furthermore, the stochastic gradient method is used for adaptive filtering, through a set of filter parameters of length N The reference signal is corrected so that the error between the corrected reference signal and the signal received by the radio telescope is minimized.

[0018] Furthermore, the ergodicity of random signals is utilized and the time-averaged error is used instead of the minimum mean square error to estimate the error.

[0019] Further, step S2.3 includes: S2.3.1 First, normalize the fixed step size and determine the fixed step size based on the signal characteristics; introduce a normalization factor; S2.3.2 Using reference signals from time n to time n-N+1, totaling N Composition vector , calculate the error between the corrected reference signal and the signal received by the radio telescope; further, the optimized filter parameters for the next moment can be obtained; S2.3.3 can obtain the optimal filter parameters under continuous operation. and Closest.

[0020] Furthermore, in step S3, the spatial-frequency domain joint filtering algorithm uses multiple antennas to obtain the correlation between signals, and through multi-antenna collaboration, uses beamforming technology to enhance signals in specific directions and suppress interference and noise in other directions.

[0021] Furthermore, in step S3, the spatial-frequency domain joint filtering algorithm specifically includes: S3.1 Treat the astronomical signal as a plane wave and point several antennas in the same direction to obtain the phase angle and pitch angle The different positions of the antennas will cause the signals received by different antennas to have different wavelengths. , the corresponding phase difference ; This constructs the steering vector elements of each antenna array ; All combinations can get the steering vector matrix ; S3.2 A total of N antennas are connected through the weight vector Merge into desired direction signal; required Satisfy the target direction The response of is 1, and the power output is minimized to obtain the beamforming signal of the mth subband; After obtaining the composite signals of all sub-bands, S3.3 uses inverse fast Fourier transform to reconstruct the time domain signals.

[0022] In another aspect, the present invention provides a radio astronomy radio frequency interference suppression system, wherein the system is used to implement the radio astronomy radio frequency interference suppression method according to the present invention.

[0023] The beneficial effects of the present invention are as follows: The present invention significantly improves the sensitivity, anti-interference ability and real-time performance of the radio astronomical observation system through the coordinated design of radio telescope antenna array hardware structure optimization, adaptive digital filtering to suppress radio frequency interference and spatial-frequency domain joint filtering technology.

[0024] 1. Technical Effects of Radio Telescope Antenna Array Hardware Structure High-sensitivity signal reception: Using low-noise filters and amplifiers, system noise is greatly reduced.

[0025] Independent reference antenna design: A small directional antenna is used to capture strong ground interference signals in real time, providing high-purity input for adaptive filtering.

[0026] Wideband adaptability: The antenna array elements cover the 1-1.5 GHz frequency band and support multiple scientific objectives such as the neutral hydrogen 21 cm line (1.42 GHz) and pulsar observations.

[0027] 2. Technical effectiveness of adaptive digital filtering in suppressing RF interference Dynamic interference suppression capability: The normalized least mean square (NLMS) algorithm based on the reference signal can track frequency-hopping communication signals (such as 5G and satellite signals) in real time, and the response time to burst pulse interference (such as radar) is <1 ms, ensuring the complete capture of transient signals (such as fast radio bursts).

[0028] Improved signal fidelity: The correlation between the astronomical signal and the reference signal is suppressed by adaptive filtering, and the spectral line characteristics (such as hydrogen line width and peak) are not distorted.

[0029] Supports multi-channel expansion, realizes independent sub-band filtering in the 1-1.5 GHz frequency band, and effectively suppresses broadband interference cross-modulation.

[0030] 3. Effect of Joint Spatial-Frequency Filtering Technology for Array Antennas Directivity gain is significantly improved: Spatial beamforming (MVDR algorithm) increases the gain in the target direction.

[0031] Multi-dimensional anti-interference optimization: The spatial-frequency domain joint processing architecture achieves full-band interference suppression. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of the flow of preliminary signal processing by the radio astronomy radio frequency interference suppression system of the present invention; Figure 2 This is the overall architecture diagram of the present invention; Figure 3 for The i-th parameter in Schematic diagram of adaptive change flow; Figure 4 This is the flow chart of the spatial-frequency domain joint filtering algorithm. DETAILED DESCRIPTION

[0033] The following will clearly and completely describe the technical solution of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0034] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0035] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0036] The following combination Figure 1-Figure 4The specific embodiments of the present invention are described in detail. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present invention and are not used to limit the present invention.

[0037] In view of the above-mentioned defects, the present invention proposes the following core innovations: Adaptive digital filtering and interference reference separation: Strong ground communication interference signals are captured in real time through independent antennas and used as reference input to dynamically adjust filtering parameters without relying on statistical prior models, significantly improving interference suppression accuracy.

[0038] Joint spatial-frequency filtering architecture: This architecture combines the beamforming capabilities of an array antenna with a frequency-domain adaptive filtering algorithm to achieve multi-dimensional interference suppression.

[0039] Low-complexity optimization algorithm: Uses block frequency domain processing and machine learning to assist parameter prediction, reducing the computational load of large-scale arrays and ensuring real-time requirements.

[0040] To meet the observation requirements of radio antenna arrays, the observation frequency band is 1 GHz to 1.5 GHz, which overlaps with the terrestrial communication band. The design of the present invention can eliminate some terrestrial communication interference and reduce background noise. To this end, the present invention provides a radio astronomy RF interference suppression system and method based on adaptive reference separation and joint spatial-frequency domain filtering.

[0041] The signals received by the feed cabin of each antenna include astronomical signals and strong communication interference signals. First, the received signals need to be preliminarily processed by hardware. The signal processing process is as follows: Figure 1 As shown, the radio astronomy radio frequency interference suppression method according to the present invention specifically includes the following steps: S1. The feed cabin receives the reflected signal from the antenna surface, splits it into two polarized signals, vertical and horizontal, and filters them separately before converting them into optical signals. This includes: The S1.1 feed cabin receives the reflected signal from the antenna surface and divides it into two polarized signals, vertical signal 1 and horizontal signal 2, which are processed separately.

[0042] S1.2 Filter 1 is the first bandpass filter with a passband of 1089-1536MHz. The signal passes through it and selects the observation frequency of 1GHz-1.5GHz. Amplifier 1 is the first active amplifier, which amplifies weak signals. S1.3 filter 2 is a second bandpass filter with a passband of 1050-1450MHz. The bias voltage adds a DC component to the electrical signal, raising the signal above zero level. S1.4 filter 3 is the third bandpass filter with a passband of 1050-1450MHz, and amplifier 2 is the second active amplifier, which ensures low noise energy through step-by-step filtering and amplification; S1.5 filter 4 is the fourth bandpass filter with a passband of 1050-1450MHz, and amplifier 3 is the third active amplifier; they are used to amplify weak astronomical signals.

[0043] The S1.6 electro-optical converter converts the electrical signal into an optical signal, which is then transmitted to the processing device via optical fiber for subsequent algorithm processing.

[0044] Although a lot of filtering is done in hardware, interference caused by communications is still difficult to avoid. Combined with the characteristics of the antenna array, the signal is optimized using two technical methods through software algorithms.

[0045] like Figure 1 As shown in the figure, the collected signals are divided into vertical signal 1 and horizontal signal 2. After the two signals are amplified by the same multi-stage filtering, they are converted into optical signals and transmitted to the server room via optical fiber for subsequent processing and analysis.

[0046] like Figure 2 As shown, multiple independent radio telescopes obtain relatively pure astronomical signals through adaptive filtering. Then, spatial-frequency domain joint filtering is performed on each signal based on the geographical location relationship of the radio telescopes. The results are displayed, analyzed or stored for subsequent research.

[0047] S2. Based on the characteristics of the antenna array, the signal collected by the hardware is optimized through an adaptive digital filtering algorithm to suppress radio frequency interference. The signal is the signal collected in S1 and specifically includes: S2.1 first divides the radio telescope received signal into three parts: the desired astronomical signal, the ground communication interference signal, and the system noise signal. The specific expression is as follows: ; The radio telescope receives the signal (signal to be filtered), For the required astronomical signal, It is a ground communication interference signal. is the system noise signal.

[0048] S2.2 receives 1GHz-1.5GHz ground communication signals through an independent communication antenna to obtain reference signals Due to inconsistent acquisition methods, the reference signal Interference signal with ground communication Not exactly the same, but strongly correlated.

[0049] S2.3 uses adaptive filtering to make the reference signal Close to ground communication interference signal .

[0050] The reference signal at the current time and the previous N-1 time Arrange to form a reference signal vector The present invention uses the random gradient method to perform adaptive filtering, through a set of filter parameters with a length of N Correct the reference signal so that the error between it and the signal received by the radio telescope changes over time. The mean square value of reaches the minimum, where The filter performance is evaluated by the minimum mean square error (MMSE) method. By taking advantage of the ergodicity of random signals, the error is estimated by the time-averaged mean square error instead of the mean square error.

[0051] In order to make the mean square error Reaching the minimum, the filter parameters along The gradient direction of the change moves, that is:

[0052] in, is the Nth parameter of the filter. This formula obtains the parameter change gradient direction that can minimize the mean square error. The parameter changes along this direction can reach the minimum mean square error fastest.

[0053] ; in, is the error at time n. is the reference signal vector, which contains the reference signals of the current moment and N points in the past.

[0054] In order to make the filter parameters Move in the direction of error reduction and control its convergence rate, so that the filter parameters at the next moment are: ; in The fixed step size determines the convergence rate of the filter parameters. Using this implementation method can make the filter parameters Converge to the optimal value, so that the reference signal Interference signal with ground communication Closest.

[0055] S2.3.1 First, if the step size is fixed If the step size is too small, the convergence speed is too slow and cannot meet the fast response requirements of radio telescopes. If the value is too large, the results may diverge and the optimal solution may not be obtained. Using a fixed step size will make it difficult to achieve the optimal effect when processing different signals. Therefore, the step size is normalized on this basis and the step size is determined according to the signal characteristics. The normalization factor is introduced. ,in is a small positive number to prevent the factor from returning to zero. We can get: ; The radio telescope receives signals at N times from n to n-N+1. Composition vector , and calculate , and Taking appropriate fixed values, we can get the coefficient .

[0056] in, ,when The convergence is slow but stable. The convergence speed is faster but may introduce overshoot or oscillation. The astronomical signal acquisition time is long and there is enough time to complete the convergence, so a lower convergence speed can be selected. , and then adjust according to the actual situation of the signal. This is to prevent the denominator from returning to zero during the calculation process. It has little impact on system performance and can be set to a fixed value. The coefficients used here are The signal is received by a radio telescope The calculated adaptive step size varies with the signal and can achieve a higher convergence speed while ensuring the convergence of the filter parameters.

[0057] S2.3.2 Using reference signals from time n to time n-N+1, totaling N Composition vector , the current filter parameters , the error can be calculated . We can further get the optimized filter parameters for the next moment . The i-th parameter in Adaptive change flow Figure 3 As shown, The meaning is a delay device with a delay of i.

[0058] according to , we know that the vector The i-th item in is the filter parameter , is the i-th parameter of the filter at time n. We can get: ; in, ,but: ; At time n, the filter's known parameters are the radio telescope's received signal x(n) and the reference signal c(n) before that time. All filter parameters at the current time are . The vectors can be formed by the known x(n) and c(n) and .according to and , x(n) can be calculated ,according to With the preset constant 、 The normalized step length can be obtained , both with Multiplying them gives , and then with the i-th filter parameter at this moment The optimized filter parameters at the next moment can be obtained by adding .

[0059] S2.3.3 The optimal filter parameters can be obtained under continuous operation , so that the reference signal passing through the filter The closest to the strongly correlated component in the radio telescope received signal x(n) is achieved, that is, and Closest. We can get: ;

[0060] The above calculations filter out the most interfering ground communication signal. The remaining system noise signal, n(n), is unavoidable but has been removed as much as possible by the hardware filtering in S1. The output signal of this adaptive filter can be used as an astronomical signal for subsequent processing and analysis.

[0061] S3. Further optimize the signal using a joint spatial-frequency filtering algorithm. After filtering out the ground interference in S2, the obtained signal can be regarded as a pure astronomical signal. When conducting astronomical observations, the radio telescope needs to obtain astronomical signals in a specified direction. However, a single antenna will receive signals in a larger angle range, and astronomical signals in other directions will become interference to the signal in the pointing direction. At this time, the astronomical signals of multiple antennas in the radio antenna array can be used to suppress interference and noise in other directions by using a joint spatial-frequency domain filtering algorithm. When multiple antennas point in the same direction, due to the different positions of the antennas, when the astronomical signals in the specified direction reach different antennas, a specific phase difference will be generated due to the different transmission distances. The interference signals from other directions will have obvious phase differences due to the different direction distances. By analyzing the spectrum of each antenna signal, the signal that meets this specific phase difference can be strengthened and other signals can be suppressed, thereby obtaining a clearer astronomical signal in the observation direction. Specifically including: Leveraging the advantages of radio antenna arrays, multiple antennas are used to obtain correlation between signals. Through multi-antenna collaboration, beamforming technology is used to enhance signals in specific directions and suppress interference and noise in other directions.

[0062] S3.1 approximates the astronomical signal (the signal processed by S2) as a plane wave, and points several antennas in the same direction to obtain the phase angle and pitch angle The different positions of the antennas will cause the signals received by different antennas to have different wavelengths. , the corresponding phase difference , f is the signal frequency. This is used to construct the steering vector elements of each antenna array All combinations can be used to obtain the steering vector matrix .

[0063] Assume that the array receives the signal , k is the antenna number. And due to the phase difference Different frequencies bring different phase differences, so it is necessary to process the astronomical signal in frequency bands. Intercept a short period of time of the astronomical signal of each antenna, and divide the antenna receiving frequency range into several sub-bands through FFT (Fast Fourier Transform). The frequency center is , then the frequency domain of each sub-band (each antenna sub-band) is expressed as: , the respective vector matrices are .

[0064] S3.2 A total of N antennas are connected through the weight vector Combined into the desired direction signal. Satisfy the target direction The response is 1, that is At the same time, in order to minimize the power of noise and interference, it is equivalent to minimizing the power of the output signal, that is, the output power is ,in is the covariance matrix of the received signal. Arrange as a vector , the covariance matrix can be calculated .

[0065] is a vector The conjugate transpose of is the weight vector The conjugate transpose of are the azimuth and elevation angles of the antenna direction, respectively. For receiving The matrix composed of the phase differences of the antenna signals when receiving astronomical signals in different directions.

[0066] Using Lagrangian function to find the optimal weight vector . Introducing Lagrange multipliers , construct a constrained optimization problem: ; Due to the constraints , which is equivalent to the output signal power, but can be obtained through the intermediate variable Find the weight vector that minimizes power .

[0067] To minimize the power, find the extreme value of the function and take the derivative to get , This is the weight vector when the power is minimum Get the value.

[0068] This vector Bringing in constraints , that is, the specified direction response is 1: , . It can be obtained that under the constraints The value of .

[0069] It means the conjugate transpose of the matrix composed of the phase differences of the antenna signals.

[0070] according to We can get: .

[0071] For different sub-bands, use separate Get the covariance matrix , we can calculate: Different sub-bands have their own weight vectors .

[0072] According to the request The weights can be used to synthesize the beam signal of the mth subband into: ; in, is the center frequency The sub-band composite signal, for The weight coefficient of the kth antenna in the synthesis process can be maintained at 1 under the premise of the response multiplier in the specified direction. By superimposing each antenna, the signal power in other directions can be offset to the minimum. It means that within a short period of time after time t, the kth antenna is at the center frequency The spectrum of the sub-band.

[0073] After obtaining the composite signals of all sub-bands, S3.3 uses IFFT (Inverse Fast Fourier Transform) to reconstruct the time domain signals: ; Different center frequencies There is a corresponding Due to the different frequencies, each sub-band does not overlap, and each sub-band The complete spectrum can be obtained by combining and splicing. Then the complete spectrum is subjected to inverse fast Fourier transform to obtain the processed astronomical signal. After processing, this signal is reduced in all directions while maintaining the signal strength in the direction the antenna array is pointing. This method allows for targeted analysis of signal changes in celestial bodies in a specific direction.

[0074] Figure 4 This is the flow chart of the spatial-frequency domain joint filtering algorithm. Each radio telescope signal is intercepted for the same period of time and the FFT is performed to obtain the spectrum. Each spectrum is divided into several parts in the same way, using the mth frequency band of each antenna. Calculate its covariance matrix Using the covariance matrix and the steering vector matrix of the radio telescope Calculate the weight vector for each frequency band The weight vector and the spectrum of each frequency band are calculated and the frequency domain of each frequency band after weighted filtering , and perform IFFT to get its time domain signal y(t).

[0075] S4. The processed astronomical signals can be observed in real time on the human-computer interaction module display terminal or saved to a server for subsequent processing and analysis. The saved data conforms to the data format standard for astronomical data and can be developed and studied using a variety of signal processing tools.

[0076] On the other hand, the radio astronomy radio frequency interference suppression system according to the present invention includes a feed chamber, multiple filters, multiple amplifiers, an electro-optical converter, an independent reference antenna, and a signal processing device. The feed chamber, multiple filters, multiple amplifiers, and electro-optical converter construct a wideband antenna array element covering 1-1.5 GHz and a low-noise amplifier cascade structure, reducing system noise and improving weak signal reception sensitivity. The independent reference antenna obtains a pure interference reference signal, providing a high-purity interference reference signal input for adaptive filtering. The wideband antenna array element (1-1.5 GHz) supports multiple scientific objectives, such as the neutral hydrogen 21cm line and pulsar observations. The present invention combines beamforming technology with frequency-domain adaptive filtering to achieve joint optimization in the spatial and frequency domains through multi-antenna collaboration.

[0077] Block frequency domain processing and machine learning-assisted parameter prediction are used to reduce the real-time computational complexity of large-scale antenna arrays.

[0078] Based on the MVDR (minimum variance distortionless response) algorithm, the sub-band covariance matrix is ​​used to dynamically adjust the weights to improve the gain in the target direction.

[0079] This invention significantly improves the sensitivity, anti-interference capability, and real-time performance of radio astronomy observation systems through the coordinated design of radio telescope antenna array hardware structure optimization, adaptive digital filtering to suppress radio frequency interference, and spatial-frequency domain joint filtering technology. Specific technical effects are as follows: 1. Technical Effects of Radio Telescope Antenna Array Hardware Structure High-sensitivity signal reception: Using low-noise filters and amplifiers, system noise is greatly reduced.

[0080] Independent reference antenna design: A small directional antenna is used to capture strong ground interference signals in real time, providing high-purity input for adaptive filtering.

[0081] Wideband adaptability: The antenna array elements cover the 1-1.5 GHz frequency band and support multiple scientific objectives such as the neutral hydrogen 21 cm line (1.42 GHz) and pulsar observations.

[0082] 2. Technical effectiveness of adaptive digital filtering in suppressing RF interference Dynamic interference suppression capability: The normalized least mean square (NLMS) algorithm based on the reference signal can track frequency-hopping communication signals (such as 5G and satellite signals) in real time, and the response time to burst pulse interference (such as radar) is <1 ms, ensuring the complete capture of transient signals (such as fast radio bursts).

[0083] Improved signal fidelity: The correlation between the astronomical signal and the reference signal is suppressed by adaptive filtering, and the spectral line characteristics (such as hydrogen line width and peak) are not distorted.

[0084] Supports multi-channel expansion, realizes independent sub-band filtering in the 1-1.5 GHz frequency band, and effectively suppresses broadband interference cross-modulation.

[0085] 3. Effect of Joint Spatial-Frequency Filtering Technology for Array Antennas Directivity gain is significantly improved: Spatial beamforming (MVDR algorithm) increases the gain in the target direction.

[0086] Multi-dimensional anti-interference optimization: The spatial-frequency domain joint processing architecture achieves full-band interference suppression.

[0087] Any process or method described in the flowchart of the present invention or in other ways herein can be understood as representing a module, segment or portion of code including one or more executable instructions for implementing specific logical functions or process steps, which can be implemented in any computer-readable medium for use by an instruction execution system, device or apparatus. The computer-readable medium can be any medium that stores, communicates, propagates or transmits a program for use by an execution system, device or apparatus, including read-only memory, magnetic disk or optical disk, etc.

[0088] Throughout this specification, reference to terms such as "embodiment" and "example" indicates that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, those skilled in the art may combine or integrate different embodiments or examples described in this specification, as well as features therein, without creating any inconsistency.

[0089] Although the above content has shown and described the embodiments of the present invention, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present invention. Ordinary technicians in this field can perform update operations such as changes, modifications, replacements and variations on the above embodiments within the scope of the present invention.

Claims

1. A method for suppressing radio astronomy radio frequency interference, characterized in that: The method is based on adaptive digital filtering and spatial-frequency domain joint filtering, and includes the following steps: S1. The feed cabin receives the reflected signal from the antenna surface, splits it into two polarized signals, vertically and horizontally, filters them separately, and converts them into optical signals. S2. Optimize the optical signal using an adaptive digital filtering algorithm to suppress radio frequency interference, taking into account the characteristics of the antenna array. S3. Process the signal using a joint spatial-frequency filtering algorithm to suppress interference and noise from other directions. S4. The processed astronomical signals are used for real-time observation on the display terminal of the human-computer interaction module, or saved to the server for subsequent processing and analysis.

2. The radio astronomy radio frequency interference suppression method according to claim 1, characterized in that: Step S1 specifically includes: The S1.1 feed cabin receives the reflected signal from the antenna surface and divides it into two polarized signals, vertical and horizontal, for separate processing. S1.2 Filter 1 is the first bandpass filter of 1089-1536MHz, through which the signal selects the observation frequency of 1GHz-1.5GHz. Amplifier 1 is the first active amplifier, which amplifies weak signals. S1.3 filter 2 is a second bandpass filter with a frequency range of 1050-1450 MHz. The bias voltage adds a DC component to the electrical signal. S1.4 Filter 3 is the third bandpass filter of 1050-1450MHz, and Amplifier 2 is the second active amplifier; S1.5 filter 4 is the fourth bandpass filter of 1050-1450MHz, and amplifier 3 is the third active amplifier; they are combined to amplify weak astronomical signals; The S1.6 electro-optical converter converts the electrical signal into an optical signal, which is then transmitted to the processing device via optical fiber for subsequent algorithm processing.

3. The radio astronomy radio frequency interference suppression method according to claim 1, characterized in that: Step S2 specifically includes: S2.1, first divide the signal received by the radio telescope into three parts: the desired astronomical signal, the ground communication interference signal, and the system noise signal; S2.2 receives 1GHz-1.5GHz ground communication signals through an independent communication antenna to obtain reference signals ; S2.3 uses adaptive filtering to make the reference signal close to the ground communication interference signal.

4. The radio astronomy radio frequency interference suppression method according to claim 3, characterized in that: The reference signal is not completely identical to the ground communication interference signal, but is correlated.

5. The radio astronomy radio frequency interference suppression method according to claim 3, characterized in that: Adaptive filtering is performed using the stochastic gradient method, with a set of filter parameters of length N. The reference signal is corrected so that the error between the corrected reference signal and the signal received by the radio telescope is minimized.

6. The radio astronomy radio frequency interference suppression method according to claim 5, characterized in that: By utilizing the ergodicity of random signals, the time-averaged error is used to replace the minimum mean square error for error estimation.

7. The radio astronomy radio frequency interference suppression method according to claim 3, characterized in that: Step S2.3 includes: S2.3.1 First, normalize the fixed step size and determine the fixed step size based on the signal characteristics; introduce a normalization factor; S2.3.2 Using the reference signal from time n to time n-N+1 Composition vector , calculate the error between the corrected reference signal and the signal received by the radio telescope; obtain the optimized filter parameters for the next moment; S2.3.3 can obtain the optimal filter parameters under continuous operation. and Closest.

8. The radio astronomy radio frequency interference suppression method according to claim 1, characterized in that: In step S3, the spatial-frequency domain joint filtering algorithm uses multiple antennas to obtain the correlation between signals, and through multi-antenna collaboration, uses beamforming technology to enhance signals in specific directions and suppress interference and noise in other directions.

9. The radio astronomy radio frequency interference suppression method according to claim 8, characterized in that: In step S3, the spatial-frequency domain joint filtering algorithm specifically includes: S3.1 Treat the astronomical signal as a plane wave and point several antennas in the same direction to obtain the phase angle and pitch angle The different positions of the antennas will cause the signals received by different antennas to have different wavelengths. , the corresponding phase difference ; This constructs the steering vector elements of each antenna array ; All combinations give the steering vector matrix ; S3.2 A total of N antennas are connected through the weight vector Merge into desired direction signal; required Satisfy the target direction The response of is 1, and the power output is minimized to obtain the beamforming signal of the mth subband; After obtaining the composite signals of all sub-bands, S3.3 uses inverse fast Fourier transform to reconstruct the time domain signals.

10. A radio astronomy radio frequency interference suppression system, characterized in that: The system is used to implement the radio astronomy radio frequency interference suppression method according to any one of claims 1-9.

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