Method for interference rejection enhancement based on multi-element array antenna

Abstract

The application discloses an anti-interference improving method based on a multi-array element array antenna, and the method comprises the following steps: receiving spatial signals through M array elements respectively, the spatial signal received by each array element is sequentially subjected to amplification filtering through a radio frequency channel corresponding to the array element, frequency conversion processing through a down-conversion module, and quantization through an analog-to-digital converter (ADC), and M digital signals are output; the power value of each signal in the M digital signals is calculated in real time, the power value is compared with a preset saturation threshold, whether each channel is in a saturation state is judged, and dynamic selection of a main array element is performed; the digital signal corresponding to the main array element is taken as a reference signal, a preset adaptive algorithm is executed to output a corresponding weight vector, the M digital signals are subjected to weighted and combined processing, and an anti-interference signal is output. Therefore, the overall anti-interference performance of the system is improved.

Description

Technical Field

[0001] This invention relates to the field of navigation and communication equipment technology, and in particular to a method for improving anti-interference based on a multi-element array antenna. Background Technology

[0002] Multi-element array anti-jamming antennas are satellite navigation antennas based on adaptive nulling antenna technology. These antennas typically consist of an array of multiple elements, each connected to a complex weighter, and the signals are ultimately combined by an adder. The complex weighter dynamically adjusts the weighting coefficients of each element according to a preset algorithm (such as the minimum mean square error criterion), changing the element gain or phase, thereby creating nulls in the radiation pattern pointing towards the interference source to achieve anti-jamming functionality.

[0003] However, the existing technology has a significant drawback: when the interference signal is too strong, the output signal of the main receiving array element (usually array element 1) is prone to saturation, causing the A / D converter output data to reach the maximum value, the reference signal to fail, and thus the adaptive zeroing algorithm cannot work properly, and the system loses its anti-interference capability.

[0004] To address this, the present invention proposes a dynamic main array switching method to improve the robustness of the system under strong interference environments. Summary of the Invention

[0005] This application provides a method for improving anti-interference based on a multi-element array antenna. It provides a method for dynamically switching the main receiving array element by real-time monitoring of the signal strength of each array element, thereby avoiding channel saturation, improving the overall anti-interference performance of the system, solving the problem of reference signal failure caused by main receiving channel saturation, and ensuring the continuous and stable operation of the multi-element array anti-interference system in a strong interference environment.

[0006] This application provides a method for improving anti-interference based on a multi-element array antenna. The method is applied to an antenna system containing M elements, where M is an integer greater than or equal to 2. The method includes the following steps:

[0007] S101, spatial signals are received by the M array elements respectively. The spatial signal received by each array element is sequentially amplified and filtered by the RF channel corresponding to that array element, frequency converted by the down-conversion module, and quantized by the analog-to-digital converter (ADC), outputting M digital signals x. m (n), m = 1, 2, ..., M, where n represents the sampling time;

[0008] S102, calculate the power value P of each signal in the M digital signals in real time. m (n), and compare it with the preset saturation threshold P. sat The comparison is performed to determine whether each channel is saturated, and the main array element is dynamically selected.

[0009] S103, using the digital signal corresponding to the main array element as the reference signal, execute the preset adaptive algorithm to output the corresponding weight vector, and perform weighted merging processing on the M digital signals to output the anti-interference signal y(n).

[0010] Preferably, the dynamic selection of the main array elements specifically includes:

[0011] During initialization, a default main array element is set;

[0012] Continuously monitor whether the channels corresponding to the current main array element are saturated;

[0013] If the channel corresponding to the current main array element is detected to be saturated, then an array element is selected from all unsaturated channels as the new main array element.

[0014] Preferably, the saturation threshold is set based on the maximum unsaturated quantization level of the analog-to-digital converter (ADC);

[0015] The determination of whether each channel is in a saturated state includes:

[0016] If P m (n)≥P sat If the m-th channel is saturated at the current time n, then it is determined that the m-th channel is saturated.

[0017] If P m (n) < P sat If the m-th channel is in an unsaturated state at the current time n, then it is determined that the m-th channel is in an unsaturated state at the current time n.

[0018] Preferably, the step of selecting an array element as the new main array element from all unsaturated channels specifically means: selecting the array element with the largest power value among all unsaturated channels as the new main array element.

[0019] Preferably, S103 specifically includes:

[0020] The M digital signals are constructed into an input signal vector X(n);

[0021] The weight vector W(n) is calculated using a pre-defined adaptive algorithm.

[0022] The array output signal is expressed by the formula y(n) = W H The expression (n)X(n) is calculated, where [·] H This indicates the conjugate transpose operation.

[0023] Preferably, the method is applicable to a frequency band of 800MHz to 3000MHz.

[0024] Preferably, the power value P m(n) is set to the instantaneous power at the corresponding sampling time.

[0025] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0026] A dynamic main array element switching mechanism based on real-time power monitoring is introduced, which changes the role of the main array element from fixed allocation to dynamic assignment based on the channel saturation state. When the main array element is saturated due to strong interference, this mechanism can quickly provide an undistorted and usable reference signal source to the adaptive algorithm, ensuring the necessary conditions for the continuous normal operation of the algorithm.

[0027] This approach fundamentally solves the vulnerability of traditional fixed main array systems to strong interference, significantly improving the system's survivability and reliability in complex electromagnetic environments, and achieving seamless maintenance of anti-interference capabilities. Without relying on hardware changes, a substantial performance improvement can be achieved through optimization of the signal processing flow, demonstrating high practical value and economic benefits. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating the method for improving anti-interference based on a multi-element array antenna according to an embodiment of the present invention.

[0029] Figure 2 This is a schematic diagram illustrating an example of an anti-interference enhancement method based on a multi-element array antenna according to the present invention. Detailed Implementation

[0030] To facilitate understanding of the present invention, a more complete description of this application will be given below with reference to the accompanying drawings, which illustrate preferred embodiments of the invention. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to enable a more thorough and complete understanding of the disclosure of the present invention.

[0031] It should be noted that the terms "vertical," "horizontal," "up," "down," "left," "right," and similar expressions used in this article are for illustrative purposes only and do not represent the only possible implementation.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains; the terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to limit the invention; the term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0033] Example 1: Figure 1This is a flowchart illustrating the method for improving anti-interference based on a multi-element array antenna according to an embodiment of the present invention.

[0034] like Figure 1 As shown, a method for improving anti-interference based on a multi-element array antenna is applied to an antenna system containing M elements, where M is an integer greater than or equal to 2. Each element is sequentially connected to an RF module, a down-conversion module, and an ADC (analog-to-digital converter). The method is applicable to satellite navigation signals (such as GPS L1 / L5, BeiDou B1 / B2 / B3, GLONASS L1, etc.) in the 800MHz to 3000MHz frequency band, and includes the following steps:

[0035] S101, the space signals (space electromagnetic signals, including B1 and B3 navigation signals and interference signals) are received by the M array elements respectively. The space signals received by each array element are sequentially amplified and filtered by the RF channel corresponding to that array element, frequency converted by the down-conversion module, and quantized by the analog-to-digital converter (ADC), outputting M digital signals x. m (n), where m represents the array element number, m = 1, 2, ..., M, and n represents the sampling time.

[0036] For example, refer to Figure 2 Step S101 includes:

[0037] A1. Space signal reception: M array elements simultaneously receive space signals, and each array element converts the electromagnetic signal into an analog electrical signal.

[0038] In this embodiment, M array elements together constitute an antenna array. The types of array elements can be microstrip patch antennas, helical antennas, or other antenna forms suitable for the target frequency band (e.g., 800MHz to 3000MHz). The spatial arrangement of the array elements (e.g., linear array, circular array, area array) and the spacing (preferably 0.3λ to 0.5λ, where λ is the center frequency wavelength) affect the array's radiation pattern performance and anti-interference capability, and are the physical basis for the implementation of this embodiment. In this embodiment of the invention, the distance between the unit antennas is defined as 0.45λ.

[0039] A2. RF Module Processing: The analog electrical signal of each array element is processed through its own RF channel; wherein, the RF channel includes at least a low noise amplifier (LNA) and a surface acoustic wave filter (SAW filter) for signal amplification and frequency band selection, and suppression of out-of-band interference.

[0040] Each array element is followed by an independent radio frequency (RF) channel. The core components of this channel are a low-noise amplifier (LNA) and a surface acoustic wave (SAW) filter. The LNA amplifies the weak received signal, and its noise figure directly affects the system sensitivity. The SAW filter filters out out-of-band interference, ensuring that only signals from the target frequency band (such as B1 and B3) enter the subsequent processing loop. The role of the RF channel is to initially improve signal quality and prepare for down-conversion.

[0041] A3. Downconversion module processing: The signal after radio frequency processing is sent to the downconversion module, which downconverts it from radio frequency (RF) to intermediate frequency (IF) through a mixer, and after automatic gain control (AGC) and filtering, outputs an intermediate frequency analog signal with stable amplitude.

[0042] This module receives the signal output from the RF channel, mixes it with a local oscillator signal through a mixer, and downconverts the RF signal to a fixed intermediate frequency (IF). The module includes an automatic gain control (AGC) circuit to stabilize the amplitude of the output signal and prevent the subsequent ADC from saturating or having insufficient quantization accuracy due to the excessive dynamic range of the input signal.

[0043] A4. Analog-to-Digital Conversion Processing: The intermediate frequency analog signal of each channel is converted into a digital signal via an ADC, denoted as x. m (n), m=1,2,...,M, where n represents the sampling time.

[0044] The intermediate frequency analog signal of each channel is sampled and quantized by an independent ADC, and converted into a digital signal x. m (n). Where m is the element index (1 to M), and n is the discrete time index (sampling time). The number of bits of the ADC (e.g., 14 bits) and the sampling rate are key parameters that need to be selected according to system requirements.

[0045] S102, calculate the power value P of each signal in the M digital signals in real time. m (n), and compare it with the preset saturation threshold P. sat The comparison is performed to determine whether each channel is saturated, and the main array element is dynamically selected.

[0046] Specifically, the power value of the digital signal corresponding to each channel is set to either the instantaneous power or the average power of all sampling moments within a preset time window. Taking instantaneous power as an example, its calculation formula is:

[0047] P m (n)=|x m (n)| 2

[0048] Among them, P m (n) represents the power value of the m-th array element at sampling time n, xm (n) represents the digital signal of the m-th array element at sampling time n. For complex signals (I / Q channels), |x m (n)| 2 =I m (n) 2 +Q m (n) 2 This represents the magnitude of the complex signal; for a real signal, simply square the absolute value. To smooth out fluctuations, a short-time average power can also be used, such as: L is the preset time window length.

[0049] Specifically, the saturation threshold P sat The setting is based on the maximum unsaturated quantization level of the analog-to-digital converter (ADC), which is determined according to the ADC's range. It is typically set to 90% to 95% of the maximum quantization level of the ADC. For example, if the ADC is N-bit, the maximum positive voltage it can convert without distortion corresponds to a digital quantization value (maximum quantization value) of 2. N-1 -1. To avoid misjudging the critical state, P sat It should be set to a value slightly lower than the square of the maximum quantization value, for example, P. sat =(0.93×(2) N-1 -1)) 2 This threshold can be programmed during system initialization or configured via software; this invention will not elaborate on this aspect.

[0050] P sat The maximum unsaturated quantization level of the ADC is directly related to its accuracy and is crucial for ensuring accurate judgment and system consistency. The maximum unsaturated quantization level refers to the digital value of the largest input signal that the ADC can linearly convert without clipping distortion. As mentioned above, setting this value with a discount (e.g., 90%–95%) establishes a safety margin, ensuring judgment and switching occur before actual clipping distortion, thus improving system reliability. This threshold can be a fixed value or designed as a configurable parameter to accommodate different ADCs or different system safety margin requirements.

[0051] Specifically, determining whether each channel is saturated includes:

[0052] If P m (n)≥P sat If the m-th channel (for the m-th digital signal) is saturated at the current time n, then it is determined that the m-th channel is saturated.

[0053] If P m (n) < P sat If the m-th channel is in an unsaturated state at the current time n, then it is determined that the m-th channel is in an unsaturated state at the current time n.

[0054] In some embodiments, dynamic selection of the main array elements specifically includes:

[0055] B1. When the system starts up and initializes, a default main array element is set.

[0056] During system initialization, the first array element (m=1) is set as the main array element by default.

[0057] B2. Continuously monitor whether the channels corresponding to the current main array element are saturated.

[0058] B3. If the channel corresponding to the current main array element is detected to be saturated, then select an array element from all unsaturated channels as the new main array element.

[0059] Specifically, if the current main array element is not saturated, it remains the main array element; if the current main array element is saturated, a power value P is immediately selected from all M array elements. m (n) is the largest and less than the saturation threshold P sat The array element is used as the new main array element.

[0060] This approach aims to select a channel with sufficiently strong signal strength (beneficial for signal-to-noise ratio) but without distortion (unsaturated) as a reference. If multiple array elements meet the conditions, the one with the highest power is selected. If there are no unsaturated array elements, the array element with the lowest power can be selected to avoid the strongest interference, or the original state can be maintained and an alarm can be triggered.

[0061] In anti-interference applications, the main channel needs a certain signal strength to ensure the signal-to-noise ratio of the reference signal. Among the unsaturated channels, the channel with the highest power receives the strongest composite signal (navigation signal + residual interference), which usually means that it may be in a deeper interference null position relatively late, or that it receives a stronger navigation signal. Using it as a reference helps the adaptive algorithm converge faster and form a deeper null. Other selection strategies, such as random selection or fixed-order selection, cannot guarantee that the best reference signal will be obtained every time. Therefore, "selecting the one with the highest power" is a specific and important means to achieve the best effect of this invention.

[0062] S103, Adaptive zeroing processing based on the main array element: The digital signal corresponding to the main array element is used as the reference signal, the adaptive algorithm is executed to output the corresponding weight vector, and the M-channel digital signals are weighted and merged to output the anti-interference signal y(n).

[0063] It should be noted that, Figure 2 The adaptive anti-interference module is used to: execute steps S102 and S103 of the digital signal based on ADC digital-to-analog conversion processing, and output the anti-interference output signal.

[0064] In some embodiments, step S103 specifically includes:

[0065] S201, Constructing the signal vector: Organize the digital signals output by the M array elements at each sampling time n of the ADC into an input signal vector: X(n)=[x1(n),x2(n),...,x M (n)] T , where X(n) is an M×1 dimensional column vector, [·] T This indicates a transpose operation, and the vector contains snapshots of signals acquired from all array elements in the space.

[0066] S202, Determine the weight vector: Calculate a corresponding weight vector using a preset adaptive algorithm (such as the Least Mean Square Error (LMS) algorithm, the Linear Constraint Minimum Variance (LCMV) algorithm, etc.): W(n) = [w1(n), w2(n), ..., w M (n)] T Where W(n) is an M×1 dimensional weight column vector, w m (n) is the complex weight of the m-th array element at time n, used to adjust the amplitude and phase of the signal in that channel.

[0067] The adaptive algorithm uses the digital signal of the currently selected main array element as the desired signal or reference signal to calculate an M×1 dimensional complex weight vector.

[0068] S203, Array Signal Synthesis: The final output signal y(n) of the array is obtained by weighted summation of the signals of each array element. in,[·] H This represents the Hermitian transpose operation. It is w m The conjugate complex number of (n) is used to coherently cancel the signal in the direction of interference (forming a null), and coherently enhance the signal in the direction of the satellite signal.

[0069] S204, using the new array element as a reference: The core of the adaptive algorithm is to use the signal of the main array element as the desired signal or reference signal. After selecting a new main array element (assuming it is the k-th array element), the algorithm will use x k (n) is used as a reference to recalculate or update the weight vector W(n), ensuring that the null of the formed beam pattern is always aligned with the interference source, thereby maintaining effective anti-interference capability even if the original main array element fails.

[0070] As an example, taking an array containing 4 array elements (M=4) as an example, the steps of the embodiment of the present invention are described in detail:

[0071] Hardware platform: The array uses 4 microstrip patch antenna elements in a square layout, with the spacing between adjacent elements being 0.45 times the center frequency wavelength (e.g., for 1.5 GHz, the wavelength is 20 cm, and the spacing is about 9 cm). The RF section of each channel uses commercial GPS LNA and SAW filter chips, while the downconversion and ADC sections are implemented using integrated RF transceiver chips (such as AD9361).

[0072] Digital processing platform: FPGA or DSP is used as the digital processing core to realize ADC data acquisition, power calculation, saturation judgment, main array selection and adaptive weight calculation algorithm.

[0073] Parameter settings: ADC is 14-bit, with a maximum quantization value of 8191. Set the saturation threshold P. sat = (0.93 × 8191) 2 ≈(7617) 2 .

[0074] Workflow:

[0075] When the system is powered on, the default main array element is array element 1;

[0076] The FPGA continuously calculates the P of 4 channels. m (n);

[0077] When strong interference is incident from a certain direction, causing the power P1(n) of array element 1 to continuously exceed P... sat ;

[0078] After detecting saturation of array element 1, the main array identifier immediately checks the power of array elements 2, 3, and 4, assuming that P2(n) is at this time. <P sat ,、P3(n) <P sat And P3(n)>P2(n), select array element 3 as the new main array element, and send a control signal to the adaptive processing unit;

[0079] The adaptive algorithm then uses x3(n) as the new reference signal to update the weight vector calculation process. The algorithm quickly adjusts the weights and forms nulls aligned with the interference source on the new radiation pattern, thus restoring and maintaining the system's anti-interference capability.

[0080] The technical solutions described in the embodiments of this application have at least the following technical effects or advantages:

[0081] Through real-time monitoring and dynamic switching, the system effectively avoids the paralysis of the entire system's anti-interference function caused by the saturation of a single main channel. In non-uniform, strong interference fields, the system can automatically select the optimal reference channel to maintain a higher output signal-to-interference-plus-noise ratio (SINR). It can be embedded as an enhancement module into existing adaptive nulling antenna systems without changing the main hardware structure.

[0082] A dynamic main array element switching mechanism based on real-time power monitoring is introduced, which changes the role of the main array element from fixed allocation to dynamic assignment based on the channel saturation state. When the main array element is saturated due to strong interference, this mechanism can quickly provide an undistorted and usable reference signal source to the adaptive algorithm, ensuring the necessary conditions for the continuous normal operation of the algorithm.

[0083] This approach fundamentally solves the vulnerability of traditional fixed main array systems to strong interference, significantly improving the system's survivability and reliability in complex electromagnetic environments, and achieving seamless maintenance of anti-interference capabilities. Without relying on hardware changes, a substantial performance improvement can be achieved through optimization of the signal processing flow, demonstrating high practical value and economic benefits.

[0084] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for improving anti-interference based on multi-element array antennas, characterized in that, The method is applied to an antenna system containing M array elements, where M is an integer greater than or equal to 2; the method includes the following steps: S101, spatial signals are received by the M array elements respectively. The spatial signal received by each array element is sequentially amplified and filtered by the RF channel corresponding to that array element, frequency converted by the down-conversion module, and quantized by the analog-to-digital converter (ADC), outputting M digital signals x. m (n), m = 1, 2, ..., M, where n represents the sampling time; S102, calculate the power value P of each signal in the M digital signals in real time. m (n), and compare it with the preset saturation threshold P. sat The comparison is performed to determine whether each channel is saturated, and the main array element is dynamically selected. S103, using the digital signal corresponding to the main array element as the reference signal, execute the preset adaptive algorithm to output the corresponding weight vector, and perform weighted merging processing on the M digital signals to output the anti-interference signal y(n).

2. The method for improving anti-interference based on a multi-element array antenna as described in claim 1, characterized in that, The dynamic selection of the main array elements specifically includes: During initialization, a default main array element is set; Continuously monitor whether the channels corresponding to the current main array element are saturated; If the channel corresponding to the current main array element is detected to be saturated, then an array element is selected from all unsaturated channels as the new main array element.

3. The method for improving anti-interference based on a multi-element array antenna as described in claim 2, characterized in that, The saturation threshold is set based on the maximum unsaturated quantization level of the analog-to-digital converter (ADC). The determination of whether each channel is in a saturated state includes: If P m (n)≥P sat If the m-th channel is saturated at the current time n, then it is determined that the m-th channel is saturated. If P m (n) < P sat If the m-th channel is in an unsaturated state at the current time n, then it is determined that the m-th channel is in an unsaturated state at the current time n.

4. The method for improving anti-interference based on a multi-element array antenna as described in claim 3, characterized in that, The step of selecting an array element as the new main array element from all unsaturated channels specifically involves selecting the array element with the largest power value among all unsaturated channels as the new main array element.

5. The method for improving anti-interference based on a multi-element array antenna as described in claim 4, characterized in that, S103 specifically includes: The M digital signals are constructed into an input signal vector X(n); The weight vector W(n) is calculated using a pre-defined adaptive algorithm. The array output signal is expressed by the formula y(n) = W H The expression (n)X(n) is calculated, where [·] H This indicates the conjugate transpose operation.

6. The method for improving anti-interference based on a multi-element array antenna as described in claim 4, characterized in that, The method is applicable to the frequency band from 800MHz to 3000MHz.

7. The method for improving anti-interference based on a multi-element array antenna as described in claim 5, characterized in that, The power value P m (n) is set to the instantaneous power at the corresponding sampling time.

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