Four-array-element double-frequency anti-interference system and method based on time division multiplexing
By using a time-division multiplexed four-element dual-frequency anti-interference system, hardware resources and sampling rate are dynamically adjusted, solving the problems of large hardware resource consumption and high static power consumption in dual-frequency signal processing, thereby reducing hardware costs and ensuring signal quality.
Patent Information
- Application Number
- CN202511179403.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-22
- Publication Date
- 2025-11-11
AI Technical Summary
Existing technologies consume large amounts of hardware resources and have high static power consumption when processing dual-frequency signals, making them difficult to adapt to miniaturized and low-power application scenarios.
A time-division multiplexed four-element dual-frequency anti-interference system is adopted. Through digital down-conversion, time-division multiplexing, anti-interference processing and digital up-conversion modules, combined with CIC decimation filter and finite state machine, the covariance matrix window length and interpolation method are dynamically adjusted to reduce the sampling rate and optimize the use of hardware resources.
It effectively reduces hardware resource consumption and static power consumption, reduces hardware costs, improves the accuracy and flexibility of anti-interference processing, adapts to different signal environments, and ensures signal quality.
Smart Images
Figure CN120928388A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of satellite navigation signal processing technology, and more specifically, to a four-element dual-frequency anti-interference system and method based on time-division multiplexing. Background Technology
[0002] In the field of satellite navigation signal reception and processing, simultaneous reception and anti-interference processing of dual-frequency signals (such as B1 and L1 bands) are key technologies for improving navigation accuracy and reliability. However, existing technologies have two significant problems when processing dual-frequency signals: On the one hand, the total bandwidth of dual-frequency signals is relatively large (the input signal bandwidth is at least 18MHz when dual-frequency signals are processed simultaneously in the existing technology), which means that the subsequent anti-interference processing module needs to process two high-frequency signals in parallel, resulting in a significant increase in the amount of hardware resources (such as the internal logic units and storage units of the FPGA), which not only increases the hardware cost of the device, but also limits the miniaturization design of the system.
[0003] On the other hand, according to the Nyquist sampling theorem, the sampling rate must be greater than twice the signal bandwidth to ensure that the signal is not distorted. For the high-frequency components in dual-frequency signals (such as the initial intermediate frequency of B1 of 39.098MHz and the initial intermediate frequency of L1 of 53.42MHz), existing technologies require a high sampling rate of 82.196MHz or higher to meet the requirements. This inevitably requires matching with a high-speed signal processing chip. However, a high sampling rate will directly lead to an increase in the system operating clock and a significant increase in static power consumption. At the same time, the selection of high-speed chips further increases the hardware cost, making it difficult to adapt to miniaturized and low-power application scenarios (such as vehicle navigation and portable terminals). In view of this, we propose a four-element dual-frequency anti-interference system and method based on time-division multiplexing. Summary of the Invention
[0004] The purpose of this invention is to provide a four-element dual-frequency anti-interference system and method based on time-division multiplexing, which aims to solve the problems of large hardware resource consumption, high static power consumption and high hardware cost in the existing technology.
[0005] To solve the above technical problems, the present invention provides the following technical solution: a four-element dual-frequency anti-interference system based on time division multiplexing, the system comprising a digital down-conversion module, a time division multiplexing module, an anti-interference processing module, a digital up-conversion module, an FIR filter, a CIC decimation filter, a finite state machine, and a direct digital frequency synthesizer; The digital downconversion module is used to downconvert the input B1 and L1 signals. It generates a digital local oscillator signal through a direct digital frequency synthesizer, multiplies the input signal with the digital local oscillator signal to obtain the downconverted signal and the mirror signal, filters out the mirror signal through an FIR filter, and then reduces the sampling rate of the input signal with the help of a CIC decimation filter. The time-division multiplexing module is used to perform time-division multiplexing processing on the down-converted B1 and L1 signals. By buffering the data after the B1 and L1 frequency conversion, the two intermediate frequency signals are divided on the time axis and each signal is allocated an independent processing time slot by the control of the finite state machine. The anti-interference processing module is used to perform anti-interference processing on the time-division multiplexed signal. It calculates the covariance matrix of the four-element signal by using the exponential weighting method, calculates the inverse matrix of the covariance matrix, calculates the weight vector according to the power inversion method, and multiplies the input signal with the corresponding weight vector and sums them to obtain the digital signal after anti-interference processing. The digital upconversion module is used to upconvert the signal after anti-interference processing. It generates a digital local oscillator signal through a direct digital frequency synthesizer, multiplies the input signal with the digital local oscillator signal to obtain the upconverted signal and the image signal, filters out the image signal through an FIR filter, and then uses interpolation to restore the sampling rate of the input signal.
[0006] Preferably, the formula for calculating the covariance matrix is: In the formula, for The four-element signal vector at time step i. The iteration window length, For dynamic weighting coefficients and ; The formula for calculating the inverse of the covariance matrix is: ; The formula for calculating the weight vector is: In the formula, It is a unit vector; The formula for multiplying the input signal and the corresponding weight vector and summing them is: ,in The weight vector of the first One element, For the first The signal of each array element.
[0007] Preferably, the direct digital frequency synthesizer generates digital local oscillator signals of corresponding frequency bands in the digital down-conversion module and the digital up-conversion module, respectively. The frequency of the local oscillator signal generated by the digital down-conversion module is matched with the frequency of the input B1 and L1 signals to achieve down-conversion of the B1 and L1 signals to the intermediate frequency. The frequency of the local oscillator signal generated by the digital up-conversion module is matched with the target output frequency to achieve up-conversion of the intermediate frequency signal to the original B1 and L1 signal frequencies.
[0008] Preferably, when calculating the covariance matrix, the iteration window length is dynamically adjusted according to the signal environment. When strong and rapidly changing interference is detected in the signal, the window length is reduced to improve the update speed of the covariance matrix. When the signal environment is relatively stable, the window length is increased to improve the calculation accuracy of the covariance matrix.
[0009] Preferably, the decimation factor of the CIC decimation filter is adjusted according to the bandwidth of the input signal. When the input signal bandwidth is small, the decimation factor is increased to further reduce the sampling rate and reduce the amount of data to be processed. When the input signal bandwidth is large, the decimation factor is decreased to avoid signal distortion.
[0010] Preferably, the digital up-conversion module uses a combination of zero-order hold interpolation and linear interpolation.
[0011] Preferably, the digital upconversion module uses zero-order hold interpolation for slowly changing signal components to simplify calculations, and uses linear interpolation for rapidly changing signal components to ensure signal recovery accuracy.
[0012] The present invention also provides a four-element dual-frequency anti-interference method based on time-division multiplexing, the method comprising the following steps; S1, digital down-conversion, receives B1 and L1 signals, uses a direct digital frequency synthesizer to generate a digital local oscillator signal, multiplies B1 and L1 signals with their corresponding digital local oscillator signals to obtain the down-converted signal and the image signal, filters out the image signal through an FIR filter, and then reduces the sampling rate through a CIC decimation filter. S2, Time Division Multiplexing, stores the down-converted B1 and L1 signals into buffers respectively, controlled by a finite state machine, and allocates alternating processing time slots for the B1 and L1 signals on the time axis, so that the two signals enter the anti-interference processing module in a time-division manner. S3. Anti-interference processing: For the signal entering the anti-interference processing module, the covariance matrix of the four-element signal is calculated using the exponential weighting method, and then the inverse matrix of the covariance matrix is calculated. The weight vector is calculated according to the power inversion method. The input signal is multiplied by the corresponding weight vector and summed to obtain the digital signal after anti-interference processing. S4. Digital up-conversion: A digital local oscillator signal is generated using a direct digital frequency synthesizer. The sampling rate is recovered by interpolation. The digital signal after anti-interference processing is then multiplied with the digital local oscillator signal to obtain the up-converted signal and the image signal. The image signal is filtered out by an FIR filter, and the processed B1 and L1 signals are output.
[0013] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention uses a time-division multiplexing module to perform time-division multiplexing processing on the down-converted B1 and L1 signals. A finite state machine controls the division of the two intermediate frequency signals on the time axis and allocates independent processing time slots. This allows the two signals to share core hardware resources such as the anti-interference processing module in a time-division manner, eliminating the need to configure separate anti-interference processing hardware for the B1 and L1 signals. This significantly reduces the duplication of hardware resources, thereby reducing the amount of hardware resources required. The reduction in hardware resources directly reduces the static power consumption of the circuit, while also reducing the number and complexity of the required hardware, effectively reducing hardware costs. This solves the problems of large hardware resource consumption, high static power consumption, and high hardware costs in the prior art.
[0014] 2. In the anti-interference processing module of this invention, the iteration window length of the covariance matrix is dynamically adjusted according to the signal environment. When the interference is strong and changes rapidly, reducing the window length can improve the update speed of the covariance matrix and ensure timely tracking of interference changes. When the signal environment is stable, increasing the window length can improve the calculation accuracy. This dynamic adjustment mechanism enables the system to adapt to different signal environments and improves the accuracy and flexibility of anti-interference processing.
[0015] 3. In this invention, the digital downconversion module adjusts the decimation factor according to the input signal bandwidth through the CIC decimation filter. When the bandwidth is small, the decimation factor is increased to reduce the amount of subsequent data, and when the bandwidth is large, the decimation factor is decreased to avoid signal distortion. The digital upconversion module adopts a combination of zero-order hold interpolation and linear interpolation to simplify the calculation for slowly changing signal components and ensure the recovery accuracy for rapidly changing components. Through dynamic adjustment of the sampling rate and accurate recovery, the signal quality is guaranteed while reducing the processing pressure. Attached Figure Description
[0016] Figure 1 This is a schematic diagram of the system architecture in this invention; Figure 2 This is a flowchart illustrating the method of the present invention. Detailed Implementation
[0017] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.
[0018] Example 1 like Figure 1 As shown, a four-element dual-frequency anti-interference system based on time-division multiplexing is disclosed. The system includes a digital down-conversion module, a time-division multiplexing module, an anti-interference processing module, a digital up-conversion module, an FIR filter, a CIC decimation filter, a finite state machine, and a direct digital frequency synthesizer. The digital downconversion module is used to downconvert the input B1 and L1 signals. It generates a digital local oscillator signal through a direct digital frequency synthesizer, multiplies the input signal with the digital local oscillator signal to obtain the downconverted signal and the image signal, filters out the image signal through an FIR filter, and then reduces the sampling rate of the input signal with a CIC decimation filter to convert the high-frequency B1 and L1 signals into intermediate frequency signals for subsequent processing. The FIR filter effectively removes image interference, and the CIC decimation filter reduces the sampling rate, reduces the amount of data, and improves the system processing efficiency. The time-division multiplexing module is used to perform time-division multiplexing processing on the down-converted B1 and L1 signals. By buffering the data after the B1 and L1 frequency conversion, the finite state machine controls the division of the two intermediate frequency signals on the time axis and allocates an independent processing time slot for each signal. This enables the time-division processing of the B1 and L1 signals in the same anti-interference processing module without the need for additional hardware, saving system resources. The finite state machine ensures that the time slot allocation is orderly and avoids signal conflicts. The anti-interference processing module is used to perform anti-interference processing on the time-division multiplexed signal. It calculates the covariance matrix of the four-element signal using the exponential weighting method, calculates the inverse matrix of the covariance matrix, calculates the weight vector according to the power inversion method, multiplies the input signal with the corresponding weight vector and sums them to obtain the anti-interference processed digital signal. This allows for the analysis of the characteristics of the signal and interference through the covariance matrix, the generation of optimal weights by combining the power inversion method, the suppression of interference signals, the enhancement of useful signals, and the improvement of the signal-to-noise ratio and reliability of the signal. The digital upconversion module is used to upconvert signals that have undergone anti-interference processing. It generates a digital local oscillator signal through a direct digital frequency synthesizer, multiplies the input signal with the digital local oscillator signal to obtain the upconverted signal and the image signal, filters out the image signal through an FIR filter, and restores the sampling rate of the input signal by interpolation to restore the processed intermediate frequency signal to the original B1 and L1 frequency band signals. The FIR filter removes image interference during the upconversion process, and the interpolation restores the sampling rate to ensure signal integrity and ensure that the output signal meets the application requirements.
[0019] The formula for calculating the covariance matrix is as follows: In the formula, for The four-element signal vector at time step i. The iteration window length, For dynamic weighting coefficients and ; The formula for calculating the inverse of the covariance matrix is: ; The formula for calculating the weight vector is: In the formula, It is a unit vector; The formula for multiplying the input signal and the corresponding weight vector and summing them is: ,in The weight vector of the first One element, For the first The signals of each array element are used to accurately characterize the statistical characteristics of the signal and interference through iterative calculation of the covariance matrix with dynamic weighting. The inverse matrix and weight vector calculations suppress the direction of interference and enhance the useful signal. The formula for multiplying and summing the input signal and weight vector is fused according to the optimal weights to maximize the anti-interference effect.
[0020] The direct digital frequency synthesizer generates digital local oscillator signals for corresponding frequency bands in the digital down-conversion module and the digital up-conversion module, respectively. The frequency of the local oscillator signal generated by the digital down-conversion module is matched with the input frequencies of B1 and L1 signals to down-convert the B1 and L1 signals to intermediate frequency. The frequency of the local oscillator signal generated by the digital up-conversion module is matched with the target output frequency to up-convert the intermediate frequency signal to the original frequencies of B1 and L1 signals. This ensures the accuracy of frequency conversion during down-conversion and up-conversion with a precise local oscillator signal, avoids signal distortion caused by frequency offset, and guarantees the frequency band consistency of the B1 and L1 signals before and after processing.
[0021] In calculating the covariance matrix, the iteration window length is dynamically adjusted according to the signal environment. When strong and rapidly changing interference is detected in the signal, the window length is reduced to improve the update speed of the covariance matrix. When the signal environment is relatively stable, the window length is increased to improve the calculation accuracy of the covariance matrix. This achieves the goal of dynamically adjusting the window length so that the covariance matrix can quickly adapt to changes in interference, while ensuring calculation accuracy in a stable environment, thus balancing the real-time performance and accuracy of anti-interference.
[0022] The decimation factor of the CIC decimation filter is adjusted according to the bandwidth of the input signal. When the input signal bandwidth is small, the decimation factor is increased to further reduce the sampling rate and reduce the amount of data to be processed. When the input signal bandwidth is large, the decimation factor is decreased to avoid signal distortion. This allows for flexible adjustment of the decimation factor, reducing the system processing pressure for narrowband signals and ensuring signal integrity for wideband signals, thus balancing processing efficiency and signal quality.
[0023] The digital upconversion module uses a combination of zero-order hold interpolation and linear interpolation to combine the advantages of both methods. Zero-order hold simplifies calculations, while linear interpolation ensures accuracy, balancing computational complexity and signal restoration quality when restoring the sampling rate.
[0024] The digital upconversion module uses zero-order hold interpolation for slowly changing signal components to simplify calculations, and linear interpolation for rapidly changing signal components to ensure signal recovery accuracy. This targeted selection of interpolation methods makes the processing of slowly changing signals more efficient and the recovery of rapidly changing signals more accurate, further optimizing the signal restoration effect.
[0025] A four-element dual-frequency anti-interference method based on time-division multiplexing, the method includes the following steps; S1, digital down-conversion, receives B1 and L1 signals, uses a direct digital frequency synthesizer to generate a digital local oscillator signal, multiplies B1 and L1 signals with their corresponding digital local oscillator signals to obtain the down-converted signal and the image signal, filters out the image signal through an FIR filter, and then reduces the sampling rate through a CIC decimation filter. S2, Time Division Multiplexing, stores the down-converted B1 and L1 signals into buffers respectively, controlled by a finite state machine, and allocates alternating processing time slots for the B1 and L1 signals on the time axis, so that the two signals enter the anti-interference processing module in a time-division manner. S3. Anti-interference processing: For the signal entering the anti-interference processing module, the covariance matrix of the four-element signal is calculated using the exponential weighting method, and then the inverse matrix of the covariance matrix is calculated. The weight vector is calculated according to the power inversion method. The input signal is multiplied by the corresponding weight vector and summed to obtain the digital signal after anti-interference processing. S4. Digital up-conversion: A digital local oscillator signal is generated using a direct digital frequency synthesizer. The sampling rate is recovered by interpolation. The digital signal after anti-interference processing is then multiplied with the digital local oscillator signal to obtain the up-converted signal and the image signal. The image signal is filtered out by an FIR filter, and the processed B1 and L1 signals are output.
[0026] The embodiments disclosed in this invention are preferred embodiments, but are not limited thereto. Those skilled in the art can easily understand the spirit of this invention based on the above embodiments and make different extensions and variations, but as long as they do not depart from the spirit of this invention, they are all within the protection scope of this invention.
Claims
1. A four-element dual-frequency anti-interference system based on time-division multiplexing, characterized in that, The system includes a digital downconversion module, a time-division multiplexing module, an anti-interference processing module, a digital upconversion module, an FIR filter, a CIC decimation filter, a finite state machine, and a direct digital frequency synthesizer; The digital downconversion module is used to downconvert the input B1 and L1 signals. It generates a digital local oscillator signal through a direct digital frequency synthesizer, multiplies the input signal with the digital local oscillator signal to obtain the downconverted signal and the mirror signal, filters out the mirror signal through an FIR filter, and then reduces the sampling rate of the input signal with the help of a CIC decimation filter. The time-division multiplexing module is used to perform time-division multiplexing processing on the down-converted B1 and L1 signals. By buffering the data after the B1 and L1 frequency conversion, the two intermediate frequency signals are divided on the time axis and each signal is allocated an independent processing time slot by the control of the finite state machine. The anti-interference processing module is used to perform anti-interference processing on the time-division multiplexed signal. It calculates the covariance matrix of the four-element signal by using the exponential weighting method, calculates the inverse matrix of the covariance matrix, calculates the weight vector according to the power inversion method, and multiplies the input signal with the corresponding weight vector and sums them to obtain the digital signal after anti-interference processing. The digital upconversion module is used to upconvert the signal after anti-interference processing. First, the sampling rate of the input signal is restored by interpolation. Then, a digital local oscillator signal is generated by a direct digital frequency synthesizer. The input signal and the digital local oscillator signal are multiplied to obtain the upconverted signal and the image signal. The image signal is filtered out by an FIR filter.
2. The four-element dual-frequency anti-interference system based on time-division multiplexing according to claim 1, characterized in that, The formula for calculating the covariance matrix is: In the formula, for The four-element signal vector at time step i. The iteration window length, For dynamic weighting coefficients and ; The formula for calculating the inverse of the covariance matrix is: ; The formula for calculating the weight vector is: In the formula, It is a unit vector; The formula for multiplying the input signal and the corresponding weight vector and summing them is: ,in The weight vector of the first One element, For the first The signal of each array element.
3. The four-element dual-frequency anti-interference system based on time-division multiplexing according to claim 1, characterized in that, The direct digital frequency synthesizer generates digital local oscillator signals for corresponding frequency bands in the digital down-conversion module and the digital up-conversion module, respectively. The frequency of the local oscillator signal generated by the digital down-conversion module is matched with the frequency of the input B1 and L1 signals to achieve down-conversion of the B1 and L1 signals to intermediate frequency. The frequency of the local oscillator signal generated by the digital up-conversion module is matched with the target output frequency to achieve up-conversion of the intermediate frequency signal to the original B1 and L1 signal frequencies.
4. A four-element dual-frequency anti-interference system based on time-division multiplexing according to claim 2, characterized in that, When calculating the covariance matrix, the iteration window length is dynamically adjusted according to the signal environment. When strong and rapidly changing interference is detected in the signal, the window length is reduced to improve the update speed of the covariance matrix. When the signal environment is relatively stable, the window length is increased to improve the calculation accuracy of the covariance matrix.
5. A four-element dual-frequency anti-interference system based on time-division multiplexing according to claim 1, characterized in that, The decimation factor of the CIC decimation filter is adjusted according to the bandwidth of the input signal. When the input signal bandwidth is small, the decimation factor is increased to further reduce the sampling rate and reduce the amount of data to be processed. When the input signal bandwidth is large, the decimation factor is decreased to avoid signal distortion.
6. A four-element dual-frequency anti-interference system based on time-division multiplexing according to claim 1, characterized in that, The digital upconversion module uses a combination of zero-order hold interpolation and linear interpolation.
7. A four-element dual-frequency anti-interference system based on time-division multiplexing according to claim 6, characterized in that, The digital upconversion module uses zero-order hold interpolation for slowly changing signal components to simplify calculations, and uses linear interpolation for rapidly changing signal components to ensure signal recovery accuracy.
8. A four-element dual-frequency anti-interference method based on time-division multiplexing, applicable to the four-element dual-frequency anti-interference system based on time-division multiplexing as described in any one of claims 1-7, characterized in that, The method includes the following steps; S1, digital down-conversion, receives B1 and L1 signals, uses a direct digital frequency synthesizer to generate a digital local oscillator signal, multiplies B1 and L1 signals with their corresponding digital local oscillator signals to obtain the down-converted signal and the image signal, filters out the image signal through an FIR filter, and then reduces the sampling rate through a CIC decimation filter. S2, Time Division Multiplexing, stores the down-converted B1 and L1 signals into buffers respectively, controlled by a finite state machine, and allocates alternating processing time slots for the B1 and L1 signals on the time axis, so that the two signals enter the anti-interference processing module in a time-division manner. S3. Anti-interference processing: For the signal entering the anti-interference processing module, the covariance matrix of the four-element signal is calculated using the exponential weighting method, and then the inverse matrix of the covariance matrix is calculated. The weight vector is calculated according to the power inversion method. The input signal is multiplied by the corresponding weight vector and summed to obtain the digital signal after anti-interference processing. S4. Digital up-conversion: A digital local oscillator signal is generated using a direct digital frequency synthesizer. The sampling rate is recovered by interpolation. The digital signal after anti-interference processing is then multiplied with the digital local oscillator signal to obtain the up-converted signal and the image signal. The image signal is filtered out by an FIR filter, and the processed B1 and L1 signals are output.