A narrowband interference mitigation system and method for Beidou navigation

Abstract

This invention addresses the problem that the direct zeroing method used in existing satellite navigation signal processing frequency domain FFT notch filtering easily leads to power loss near interference frequencies, affecting signal integrity. It proposes a narrowband interference suppression system and method for BeiDou navigation. The narrowband interference suppression system includes a BeiDou RF front-end module, a high-speed ADC sampling module, a digital down-conversion (DDC) module, a signal distributor and buffer module, an interference detection and parameter estimation unit, an interference suppression execution unit, a baseband correlation and demodulation module, and a navigation and positioning result output module. A cascaded array of IIR notch filters is constructed using a cascaded array module. A steep transition band is achieved through small-order serial units, and the stopband width of the notch filters can be flexibly adjusted via a convergence factor. This enables precise suppression of extremely narrow stopband interference at different bandwidths, filtering out signals only at interference frequencies, effectively avoiding impact on surrounding useful BeiDou signals and preventing spectrum leakage.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation signal processing technology, and in particular to a narrowband interference suppression system and method for BeiDou navigation. Background Technology

[0002] The BeiDou Navigation Satellite System plays an indispensable role in many fields such as transportation, land resources, and national defense. Its positioning accuracy and operational reliability directly affect the effectiveness of applications in various industries. During the transmission of BeiDou satellite navigation signals from an altitude of approximately 20,000 kilometers to the ground receiver, it is affected by various factors such as transmission distance and atmospheric attenuation, resulting in extremely weak signal power reaching the receiver antenna, typically only around -160 dBW. This makes the BeiDou navigation signal inherently weak in its anti-interference capability, making it highly susceptible to various narrowband interferences in the environment.

[0003] The sources of the aforementioned narrowband interference mainly include FM broadcast signals, harmonic signals generated by mobile communication base stations, radar detection signals, and illegally deployed jammers. This type of narrowband interference can cover or overwhelm the useful BeiDou signal, directly causing ground receivers to fail to acquire signals or lose tracking lock, leading to a significant decrease in positioning accuracy. In severe cases, it can even cause the receiver to malfunction completely, severely restricting the reliable application of the BeiDou navigation system in various key areas and failing to meet the needs of high-precision navigation, emergency rescue, and other scenarios.

[0004] Currently, most mainstream narrowband interference suppression technologies in the industry employ frequency domain FFT notch filtering technology. Its core principle is to transform the received mixed signal to the frequency domain and suppress narrowband interference by directly setting the interference frequency point to zero. For example, the narrowband interference suppression method disclosed in the invention patent application with publication number CN105911565A adopts this technical approach.

[0005] However, while existing frequency-domain FFT notch filtering techniques have the advantages of being easy to operate and having low implementation costs, they also have significant technical drawbacks. On the one hand, this method is prone to serious spectrum leakage problems, causing significant power loss of the useful BeiDou signal near the interference frequency point, thus destroying the integrity of the useful signal. On the other hand, in the process of transforming the processed frequency-domain signal back to the time domain, significant group delay jitter is introduced. This jitter will seriously affect the receiver's synchronization tracking accuracy, thereby leading to a decrease in the positioning accuracy of the BeiDou receiver. It cannot solve the core problem of the weak anti-narrowband interference capability of existing BeiDou navigation signals. Summary of the Invention

[0006] The purpose of this invention is to address the problems of the direct zeroing method in the frequency domain FFT notch filtering technique used in existing satellite navigation signal processing, which easily leads to power loss near the interference frequency point, affecting signal integrity. Furthermore, the process of transforming the frequency domain signal back to the time domain can easily introduce group delay jitter, affecting signal synchronization accuracy. This invention provides a narrowband interference suppression system for BeiDou navigation, which reduces useful signal loss and lowers group delay jitter.

[0007] To solve the above problems, the present invention adopts the following technical solution:

[0008] A narrowband interference suppression system for BeiDou navigation includes a BeiDou radio frequency front-end module, a high-speed ADC sampling module, a digital down-conversion (DDC) module, a signal distributor and buffer module, an interference detection and parameter estimation unit, an interference suppression execution unit, a baseband correlation and demodulation module, and a navigation and positioning result output module.

[0009] The Beidou RF front-end module, high-speed ADC sampling module, digital down-conversion (DDC) module, and signal distributor and buffer module are connected in sequence; the signal distributor and buffer module are also connected to the interference detection and parameter estimation unit and the interference suppression execution unit, respectively; the interference detection and parameter estimation unit and the interference suppression execution unit communicate bidirectionally; the interference suppression execution unit is connected to the baseband correlation and demodulation module; the baseband correlation and demodulation module is connected to the navigation and positioning result output module;

[0010] The Beidou radio frequency front-end module is used to receive multi-band radio frequency signals from Beidou satellites, process the signals, and down-convert them to intermediate frequency analog signals.

[0011] The high-speed ADC sampling module is used to perform analog-to-digital conversion on the intermediate frequency analog signal and output a digital intermediate frequency signal;

[0012] The digital downconversion (DDC) module is used to convert the digital intermediate frequency signal into a zero intermediate frequency baseband complex signal.

[0013] The signal distributor and buffer module are used to synchronously buffer the baseband complex signal, and at the same time divide the signal into two synchronous data streams and transmit them to the interference detection and parameter estimation unit and the interference suppression execution unit respectively.

[0014] The interference detection and parameter estimation unit includes a fast FFT and PSD calculation module, a dynamic threshold comparator, and an interference frequency point identification and bandwidth estimation module connected in sequence. The fast FFT and PSD calculation module performs FFT transformation on the baseband complex signal and calculates the real-time power spectral density. The dynamic threshold comparator generates an interference detection threshold that dynamically adjusts with background noise. The interference frequency point identification and bandwidth estimation module extracts the center frequency, -3dB bandwidth, and interference-to-signal ratio of the narrowband interference.

[0015] The interference suppression execution unit includes an IIR coefficient real-time generation engine and a cascaded IIR notch filter array module; wherein, the IIR coefficient real-time generation engine is used to calculate and generate the coefficient matrix of the second-order IIR notch filter based on the interference parameters; the cascaded IIR notch filter array module is used to receive the coefficient matrix and perform time-domain precise filtering on the baseband complex signal.

[0016] The baseband correlation and demodulation module is used to capture, track and demodulate the filtered and purified signal, and extract the navigation message and navigation measurement values ​​of the Beidou signal;

[0017] The navigation and positioning result output module is used to complete the positioning calculation and output the navigation and positioning result based on the navigation measurement value and navigation message.

[0018] Furthermore, the dynamic threshold comparator in the interference detection and parameter estimation unit uses a sliding window mid-range filtering algorithm to remove the broadband spectral components of the BeiDou useful signal, extract the background noise baseline, and calculate the adaptive threshold for interference detection in combination with the preset constant false alarm rate (CFAR).

[0019] Furthermore, the cascaded IIR notch filter array module is composed of 1 to 8 second-order IIR notch filter units cascaded in series, and the notch filter unit is a direct type II structure; the number of activated notch filter units matches the number of frequency points of narrowband interference; each stage of notch filter unit independently filters for a specific interference frequency point.

[0020] The IIR coefficient real-time generation engine in the interference suppression execution unit calculates the normalized interference frequency based on the interference center frequency, expressed as:

[0021]

[0022] in, The actual center frequency of narrowband interference. The sampling rate of the baseband complex signal;

[0023] Calculate the convergence factor r based on the interference bandwidth and the interference-to-signal ratio:

[0024]

[0025] in, JSR is the interference bandwidth and the signal-to-interference ratio. The value range is [0,π], and the value range of r is 0. <r<1。

[0026] A narrowband interference suppression method for BeiDou navigation, based on the aforementioned narrowband interference suppression system for BeiDou navigation, is characterized by comprising the following steps:

[0027] S101: Acquire BeiDou intermediate frequency digital signals and perform time-domain buffering: After the BeiDou satellite radio frequency signal is sequentially down-converted, analog-to-digital converted, and digitally down-converted, a zero intermediate frequency baseband complex signal is obtained and synchronously buffered;

[0028] S102: Perform N-point FFT to obtain real-time signal power spectral density. PSD: Apply a window function to the buffered baseband complex signal and then perform an N-point radix-2 FFT transform to calculate the power spectral density at each frequency point using the periodogram method.

[0029] S103: Calculate the adaptive noise baseline threshold based on median filtering: Extract the background noise baseline by performing sliding window median filtering on the power spectral density data, and calculate the dynamically adjusted adaptive threshold for interference detection based on constant false alarm probability.

[0030] S104: Determine if there are spectral spikes exceeding the threshold: Compare the power spectral density data with the adaptive threshold point by point. If S or more consecutive adjacent frequency points exceed the threshold, it is determined that narrowband interference has been detected, and S106 is executed; otherwise, S105 is executed.

[0031] S105: Maintain the filter in pass-through mode and output the original signal: Control the cascaded IIR notch filter array module to maintain the pass-through mode, and the baseband complex signal passes through without loss and is sent to the baseband correlation and demodulation module, then proceed to step S110.

[0032] S106: Extract the center frequency of the interference. Interference-to-signal ratio (JSR): Based on the improved successive elimination algorithm to lock the center frequency of the interference, the interference-to-signal ratio is obtained by calculating the ratio of the peak power of the interference to the average power of the BeiDou useful signal.

[0033] S107: Calculate the convergence factor r and pole positions of the IIR notch filter based on the interference bandwidth: Calculate the normalized interference frequency based on the interference center frequency, calculate the convergence factor based on the interference bandwidth and interference-to-signal ratio, and determine the pole positions in the z-plane.

[0034] S108: Update the coefficient matrix of the corresponding unit in the cascaded IIR notch filter array module: Generate the coefficient matrix of the second-order IIR notch filter based on the normalized interference frequency and convergence factor, and load and update it to the corresponding notch filter unit in parallel.

[0035] S109: Signal flows through cascaded notch filters for time-domain filtering and suppression: The baseband complex signal flows through the updated cascaded IIR notch filter array module, and each activated unit completes real-time filtering according to the time-domain recursive formula.

[0036] S110: The purified signal is sent to the baseband correlator for acquisition and tracking: the filtered purified signal is acquired, tracked and demodulated, the navigation measurement value and message are extracted and the positioning calculation is completed, and then it returns to S101 to realize closed-loop processing.

[0037] Furthermore, in step S102, N is set to 2048, and a Hamming window is used as the window function; the formula for calculating the power spectral density is:

[0038]

[0039] in, For frequency domain complex signals The modulus; The square of the amplitude of the in-phase component at the k-th frequency point; It is the square of the amplitude of the orthogonal component at the k-th frequency point.

[0040] Furthermore, in step S103, a 2n+1 sliding window is used to perform median filtering. The sliding window is formed by taking the power values ​​of n frequencies before and after the current frequency as the center, and the median value is obtained after sorting and selecting the median value to obtain the background noise baseline data. The calculation process for the adaptive threshold is shown in the following formula:

[0041]

[0042] in, This is background noise; The constant false alarm probability coefficient; This represents the standard deviation of the background noise baseline data.

[0043] Furthermore, the process of calculating the IIR notch filter convergence factor r and pole locations in step S107 includes the following steps:

[0044] S1071: Calculate the normalized interference frequency As shown in the following formula:

[0045]

[0046] in, The actual center frequency of narrowband interference. The sampling rate of the baseband complex signal; The value range is [0, π].

[0047] S1072: Calculate the convergence factor As shown in the following formula:

[0048]

[0049] in, The interference bandwidth is JSR, and the signal-to-interference ratio (SSR) is r; the value of r ranges from 0 to 1. <r<1;

[0050] S1073: Determine the location of the pole in the z-plane using the following formula:

[0051]

[0052] in, It is a natural constant. It is the imaginary unit.

[0053] Furthermore, the transfer function of the second-order IIR notch filter in step S108 is:

[0054]

[0055] in, The normalized interference frequency is r; the convergence factor is r. Delay operator for units; It is a second-order unit delay operator.

[0056] Furthermore, the time-domain recursive formula for the second-order IIR notch filter in step S109 is as follows:

[0057]

[0058] in, This is the input signal of the notch filter in the nth sampling period at the current moment; This represents the delay value of the input signal in the (n-1)th sampling period of the previous sampling period of the notch filter; This represents the delay value of the input signal in the (n-2)th sampling period of the first two sampling periods of the notch filter; This represents the delay value of the output signal in the (n-1)th sampling period of the previous sampling period of the notch filter; This represents the delay value of the output signal in the (n-2)th sampling period of the first two sampling periods of the notch filter; ; ; ; ; If multiple narrowband interferences are detected, the multi-stage notch filter units operate in series, with each stage independently filtering a specific interference frequency.

[0059] The beneficial effects of this invention are as follows:

[0060] A cascaded array of IIR notch filters is constructed using cascaded IIR notch filter modules. A steep transition band is achieved with a very small order, and the stopband width of the notch filter can be flexibly adjusted by the convergence factor. This enables precise suppression of narrowband interference of different bandwidths, filtering out signals at only the interference frequency points and effectively avoiding the impact on useful BeiDou signals in the surrounding area. Unlike the direct zeroing method of traditional frequency domain FFT notch filters, this method fundamentally solves the problem of spectrum leakage.

[0061] The cascaded IIR notch filter array module structure adopted, compared with the large-scale FFT processing of long order, does not require complex matrix operations and a large number of multipliers and register resources, which greatly reduces the computational complexity of the algorithm and the hardware resource occupancy rate. It can be directly integrated into the embedded SoC of the Beidou receiver, which meets the hardware design requirements of miniaturization and low power consumption of the Beidou receiver.

[0062] Real-time analysis of signal power spectral density is achieved through fast FFT and PSD calculation modules. Combined with the improved successive elimination algorithm, the identification of interference frequency points and parameter extraction can be completed in microseconds. The real-time IIR coefficient generation engine can quickly complete the calculation and update of the notch filter coefficient matrix, enabling the system to track the drift of interference frequency points and changes in bandwidth in real time. Even when facing frequency hopping interference and multi-point dynamic narrowband interference, it can achieve fast response and accurate suppression.

[0063] By combining the median filtering algorithm with constant false alarm rate (CFAR) probability, the adaptive noise baseline threshold is calculated, which can automatically distinguish between broadband BeiDou useful signals and narrowband interference signals without the need for manual setting of detection thresholds. Furthermore, the filtering units of the cascaded IIR notch filter array module are automatically activated according to the number of interference frequency points, achieving adaptive suppression of any number of multi-point narrowband interferences, thus solving the problem of poor flexibility of traditional fixed parameter filters. Attached Figure Description

[0064] Figure 1 This is a system architecture diagram of Embodiment 1 of the present invention;

[0065] Figure 2 This is a flowchart of the steps in Embodiment 1 of the present invention. Detailed Implementation

[0066] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0067] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the figures only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0068] Example 1:

[0069] like Figure 1 As shown, a narrowband interference suppression system for BeiDou navigation includes a BeiDou radio frequency front-end module, a high-speed ADC sampling module, a digital down-conversion (DDC) module, a signal distributor and buffer module, an interference detection and parameter estimation unit, an interference suppression execution unit, a baseband correlation and demodulation module, and a navigation and positioning result output module. The interference detection and parameter estimation unit includes a fast FFT and PSD calculation module, a dynamic threshold comparator, and an interference frequency point identification and bandwidth estimation module connected in sequence. The interference suppression execution unit includes an IIR coefficient real-time generation engine and a cascaded IIR notch filter array module.

[0070] Specifically,

[0071] The BeiDou RF front-end module receives RF signals from the L1, L2, and L5 frequency bands of BeiDou satellites. Its core consists of a low-noise amplifier (LNA), a mixer, a bandpass filter, and a local oscillator. The LNA amplifies the weak RF signal, with a gain controlled at 20-30dB to ensure a low noise figure (NF≤2dB). The local oscillator generates a fixed-frequency local oscillator signal, which, along with the amplified RF signal, is down-converted to a 70MHz intermediate frequency (IF) by the mixer, with an IF bandwidth of 20MHz. The bandpass filter removes spurious interference from the IF signal, with a passband ripple ≤0.5dB and stopband rejection ≥60dB, ultimately outputting a clean IF analog signal to provide the foundation for subsequent analog-to-digital conversion. Its design ensures low noise, high linearity, and avoids introducing additional signal distortion.

[0072] High-speed ADC sampling module: Connected to the intermediate frequency output of the Beidou RF front-end module, the sampling rate is selected according to the Nyquist sampling theorem. MSPS, with a quantization bit depth of 14 bits, of which The ADC sampling rate, measured in MSPS (megasamples per second), performs high-speed, high-precision analog-to-digital conversion on a 70MHz intermediate frequency analog signal, converting it into a digital intermediate frequency signal. A 14-bit quantization depth ensures accurate quantization of weak BeiDou signals, while a 200MSPS sampling rate meets the sampling requirements of a 20MHz intermediate frequency bandwidth, with a 10-fold sampling margin to prevent signal aliasing. The ADC's spurious-free dynamic range (SFDR) is ≥70dB, guaranteeing the purity of the sampled signal.

[0073] The digital downconverter (DDC) module is implemented using FPGA hardware logic and consists of a numerically controlled oscillator (NCO), a mixer, a multi-stage half-band low-pass filter, and a downsampler. The NCO generates a quadrature local oscillator signal with the same carrier frequency as the 70MHz digital intermediate frequency (IF) signal, including two paths, I and Q, where I is the in-phase component and Q is the quadrature component. The quadrature local oscillator signal is mixed with the IF signal to convert it into a complex baseband signal with zero IF. The multi-stage half-band low-pass filter removes the image frequency generated during mixing, achieving a total stopband rejection of ≥80dB. Finally, the signal is downsampled to... ,in, This represents the sampling rate of the baseband signal after downsampling, measured in MSPS. It reduces the rate of subsequent signal processing and hardware resource consumption, ultimately outputting a zero-IF baseband complex signal, including I and Q channels, with a data bit width of 16 bits.

[0074] Signal distributor and buffer module: A dual-port RAM is used as the core buffer. In this example, the buffer depth is set to 2048 points to match the number of points N=2048 in the subsequent FFT transformation, and the data bit width is 16 bits. The baseband complex signal output from the DDC module is synchronously buffered. Simultaneously, the buffered baseband complex signal is divided into two fully synchronized data streams by the signal distributor: one stream is sent to the interference detection and parameter estimation unit for interference frequency detection and parameter extraction; the other stream is sent to the cascaded IIR notch filter array module of the interference suppression execution unit, awaiting filtering processing. The dual-port RAM design enables parallel reading and writing of signals at a read / write rate of 20MSPS, ensuring the synchronization of interference detection and filtering suppression and avoiding time delay deviations in signal processing.

[0075] Interference detection and parameter estimation unit: This is the core of the system's perception. It consists of a fast FFT and PSD calculation module, a dynamic threshold comparator, and an interference frequency point identification and bandwidth estimation module, all cascaded together. All of these are implemented based on an FPGA pipeline architecture, with a processing latency of ≤5μs, ensuring a microsecond-level processing speed.

[0076] Fast FFT and PSD calculation module: Performs a 2048-point radix-2 FFT transform on the split baseband complex signal, where N=2048 is the number of FFT transform points; a Hamming window is applied to the signal before the transform, and the window function is:

[0077]

[0078] in, The value of the Hamming window function at the nth sampling point; This is the sampling point index, with a value range of [value range missing]. ; The number of FFT transform points; The value is pi, taken as 3.1416 in this example; this window function is used to suppress spectral leakage caused by the FFT transform; the FFT transform yields a 2048-point frequency domain complex signal, expressed as:

[0079]

[0080] in, The frequency domain complex signal is the k-th frequency point; This is the frequency index; in this example, the value range is... ; The amplitude of the in-phase component at the k-th frequency point; The amplitude of the orthogonal component at the k-th frequency point; The imaginary unit, Then, the real-time power spectral density (PSD) of the signal is calculated using the periodogram method. This involves summing the squares of the I and Q channels of the complex signal in the frequency domain to obtain the power value at each frequency point. The calculation formula is as follows:

[0081]

[0082] in, This represents the power spectral density value at the k-th frequency point, in dB. For frequency domain complex signals The modulus; The square of the amplitude of the in-phase component at the k-th frequency point; The square of the amplitude of the orthogonal component at the k-th frequency point; the final output is power spectral density data with a length of 2048 points and a frequency resolution of [missing value]. MSPS / 2048≈9.766kHz, where MSPS is the baseband sampling rate. The FFT point count represents the frequency interval between two adjacent frequency points, which is used to ensure the accuracy of frequency point identification for narrowband interference.

[0083] Dynamic threshold comparator: A 31-point sliding window median filter is used to process the power spectral density data of 2048 points. The sliding window is formed by taking the power values ​​of 15 points before and after the current frequency. By sorting the power values ​​in the sliding window in ascending order and taking the median, broadband spectral components of the useful BeiDou signal and isolated spectral noise are removed, and the baseline data of background noise is accurately extracted. ,in The power value of the background noise baseline, in dB; then based on the preset constant false alarm rate (CFAR= ), calculate the adaptive threshold for interference detection As shown in the following formula:

[0084]

[0085] in, The adaptive threshold for interference detection is expressed in dB. This represents the baseline power value for background noise. The constant false alarm rate coefficient corresponds to the following in this example: The constant false alarm probability; Baseline data for background noise The standard deviation, expressed in dB, is used to measure the degree of fluctuation in background noise. This formula enables the threshold to be dynamically adjusted according to the background noise, effectively avoiding missed or false detections.

[0086] Interference frequency point identification and bandwidth estimation module: Based on an improved successive elimination algorithm, it identifies interference frequencies exceeding an adaptive threshold. Spectral peaks are analyzed. First, all frequency points exceeding the threshold are marked. Then, the frequency range of narrowband interference is determined by neighborhood merging. ,in This is the starting index of the interference frequency point. The termination index of the interference frequency point is used; then the center frequency index of the interference is calculated using the centroid method. The calculation formula is:

[0087]

[0088] in, This is the index of the center frequency of the interference; The summation symbol represents summation from... arrive Sum the corresponding values ​​for all frequency points; Frequency index; Let be the power spectral density value at the k-th frequency point; based on the correspondence between the frequency point index and the actual frequency, the actual center frequency of the interference is calculated. The unit is Hz; the correspondence between the frequency index and the actual frequency is expressed as follows:

[0089]

[0090] in, This is the actual frequency corresponding to the frequency point; Frequency index; MSPS is the baseband sampling rate; The number of FFT points;

[0091] Simultaneously, based on the power attenuation characteristics of the interference frequency, the -3dB bandwidth of the interference is determined. The unit is Hz, which represents the frequency range width corresponding to a 3dB decrease in interference power. The ratio of the peak power at the interference frequency to the average power of the BeiDou useful signal is calculated to obtain the interference-to-signal ratio (JSR), in dB. The calculation formula is as follows:

[0092]

[0093] in, The interference-to-signal ratio (CNR) is a measure of the ratio of interference strength to the strength of the useful signal. Logarithmic operations to base 10; The peak power at the interference frequency is expressed in dBW. This represents the average power of the useful BeiDou signal, expressed in dBW.

[0094] Ultimately (Interference center frequency) The three sets of interference parameters (interference - 3dB bandwidth) and JSR (interference-to-signal ratio) are output in parallel to the IIR coefficient real-time generation engine of the interference suppression execution unit. If multiple narrowband interferences are detected, multiple sets of interference parameters are output.

[0095] Interference suppression execution unit: The core of the system, consisting of a real-time IIR coefficient generation engine and a cascaded IIR notch filter array module, is the key to achieving precise narrowband interference suppression, with an overall processing delay of ≤3μs.

[0096] Real-time IIR coefficient generation engine: Implemented using FPGA-based hardware multipliers and adders, it receives interference parameters from the interference frequency identification and bandwidth estimation module, including... , JSR; normalization of interference frequency is achieved through hardware logic circuits. Convergence factor The system performs real-time calculation of pole locations and generates the corresponding coefficient matrix based on the transfer function of the second-order IIR notch filter. The coefficient matrix is ​​output to the cascaded IIR notch filter array module in parallel, with the update delay controlled within 1μs. The hardware logic for coefficient calculation adopts a pipelined design to ensure that the calculation speed matches the signal processing speed.

[0097] Among them, normalized interference frequency The calculation formula is:

[0098]

[0099] in, The interference center frequency is expressed in Hz. MSPS is the baseband sampling rate; Pi; The range of values ​​is ;

[0100] Convergence factor The calculation formula is:

[0101]

[0102] in, Interference -3dB bandwidth, in Hz; This refers to the baseband sampling rate. The signal-to-dryness ratio is expressed in dB. The range of values ​​is ;

[0103] The location of the pole is:

[0104]

[0105] in, Let these be the coordinates of the pole in the z-plane; For the modulus of the pole, it is necessary to ensure The control poles are located inside the unit circle; This is a natural constant, and in this example, it is taken as 2.7183. The imaginary unit; The angle of the pole is used to ensure stable operation of the filter without self-oscillation.

[0106] Cascaded IIR Notch Filter Array Module: Composed of 1 to 8 second-order IIR notch filter units cascaded in series, supporting simultaneous suppression of up to 8 multi-point narrowband interferences. Each notch filter unit is a direct type II structure, consisting of 2 18-bit multipliers, 3 adders, and 2 delay units, balancing hardware resource consumption and filtering stability. Each notch filter unit can independently receive the coefficient matrix and update its internal parameters in real time. When no interference is detected, all notch filter units maintain a straight-through mode, allowing the signal to pass through without loss. When interference is detected, the corresponding number of notch filter units are activated. Each stage performs time-domain filtering for a specific interference frequency. The notch filter's stopband rejection is ≥40dB, and the passband ripple is ≤0.1dB. The core calculation formulas for each notch filter unit are the transfer function and the time-domain recursive formula; the transfer function is expressed as:

[0107]

[0108] in, The normalized interference frequency is r; the convergence factor is r. Delay operator for units; It is a second-order unit delay operator;

[0109] The time-domain recursive formula is expressed as:

[0110] .

[0111] in, This is the input signal of the notch filter in the nth sampling period at the current moment, which is the baseband complex signal to be filtered; This represents the delay value of the input signal in the (n-1)th sampling period of the previous sampling period of the notch filter; This represents the delay value of the input signal in the (n-2)th sampling period of the first two sampling periods of the notch filter; This is the output signal of the nth sampling period at the current moment of this unit, i.e., the signal after preliminary purification; This represents the delay value of the output signal in the (n-1)th sampling period of the previous sampling period of the notch filter; This represents the delay value of the output signal in the (n-2)th sampling period of the first two sampling periods of the notch filter; ; ; ; ; .

[0112] The baseband correlation and demodulation module, implemented using an FPGA, consists of an acquisition module, a tracking module, and a demodulation module. It processes the purified baseband complex signal after filtering by a cascaded IIR notch filter array module. The acquisition module achieves rapid acquisition of BeiDou satellite signals (≤1s) through parallel code phase search and carrier frequency search, combined with 1ms coherent integration and 16th incoherent integration to enhance acquisition gain. The tracking module uses a carrier tracking loop (Costas loop) and a code tracking loop (Delay-Locked Loop, DLL) to accurately track the satellite signal carrier and pseudocode. The bandwidth of the tracking loop is dynamically adjusted within the range of 1-10Hz based on the signal's carrier-to-noise ratio to ensure tracking accuracy and stability. The demodulation module extracts the navigation message from the tracked signal and calculates navigation measurements such as pseudorange and carrier phase. The measurement accuracy meets the positioning requirements of the BeiDou receiver, providing data for positioning calculations.

[0113] The navigation and positioning result output module is based on an embedded MCU, with a core 32-bit high-performance microprocessor. It receives navigation measurement values ​​and navigation messages from the baseband correlation and demodulation module, and completes the positioning calculation through the least squares method or Kalman filter algorithm at a calculation frequency of 10Hz. Finally, it outputs navigation and positioning results such as latitude, longitude, altitude, speed, and time through standard interfaces such as serial port and CAN bus. At the same time, it monitors information such as signal carrier-to-noise ratio and interference suppression status in real time, and feeds the status information back to the front-end module to realize closed-loop monitoring of the system's working status.

[0114] like Figure 2 As shown in the figure, this embodiment also provides a narrowband interference suppression method for BeiDou navigation, including the following steps:

[0115] S101: Acquires BeiDou intermediate frequency digital signals and performs time-domain buffering. Specifically:

[0116] The BeiDou RF front-end module down-converts the BeiDou satellite L1, L2, and L5 frequency band RF signals to a 70MHz intermediate frequency analog signal, and the high-speed ADC sampling module uses... The MSPS sampling rate and 14-bit quantization bits convert it into a digital intermediate frequency signal, where MSPS represents the ADC sampling rate, which is expressed in megasamples per second. The DDC module performs mixing, multi-stage half-band low-pass filtering, and downsampling on the digital intermediate frequency signal to convert it into... The MSPS zero-IF baseband complex signal includes two channels, I and Q. I is the in-phase component, and Q is the quadrature component. The data bit width is 16 bits. The baseband sampling rate is set to 2048 points. The baseband complex signal is then sent to the dual-port RAM of the signal distributor and buffer module for time-domain buffering. The buffer depth is set to match the number of points in the subsequent FFT transformation to ensure the integrity of the signal processing for each frame. The buffered signal is a continuous data stream, and it is read and written in a first-in-first-out (FIFO) manner. The read and write rate is synchronized with the signal processing rate at 20MSPS.

[0117] S102: Perform an N-point FFT to obtain the real-time signal power spectral density (PSD). Specifically:

[0118] The fast FFT and PSD calculation modules perform a radix-2 FFT transformation on the buffered 2048-point baseband complex signal, where N=2048 is the number of FFT points. Before the transformation, a Hamming window is applied to the signal, with the window function being...

[0119]

[0120] in, The value of the Hamming window at the nth sampling point; For sampling point index, ; The number of FFT points; This is the mathematical constant pi; the window function is used to suppress spectral leakage caused by the FFT transform.

[0121] The FFT transform yields a 2048-point frequency domain complex signal:

[0122]

[0123] in, The frequency domain complex signal is the k-th frequency point; For frequency point index, ; The amplitude of the in-phase component at the k-th frequency point; The amplitude of the orthogonal component at the k-th frequency point; The imaginary unit;

[0124] Then, the power spectral density at each frequency point is calculated using the periodogram method. The calculation formula is as follows:

[0125]

[0126] in, is the power spectral density value (dB) at the k-th frequency point; for The modulus; , These are the squares of the amplitudes of the in-phase and quadrature components, respectively;

[0127] The final power spectral density data for 2048 points was obtained, with a frequency resolution of:

[0128] MSPS / 2048≈9.766kHz

[0129] in, MSPS is the baseband sampling rate, which ensures the accuracy of frequency point identification for narrowband interference.

[0130] S103: Calculate the adaptive noise baseline threshold based on median filtering, specifically including the following steps:

[0131] S1031: The dynamic threshold comparator performs a 31-point sliding window mid-range filter on the 2048-point power spectral density data, first using the current frequency point... Centered on (frequency index), take to A sliding window is formed by power values ​​at 31 frequency points. The power values ​​within the window are sorted in ascending order, and the value at the middle position is taken as the median filtering result for that frequency point.

[0132] S1032: Traverse all 2048 frequency points to obtain filtered power spectral density data, remove broadband spectral components of useful BeiDou signals and isolated spectral noise, and accurately extract the baseline data of background noise. ; The power value of the background noise baseline, in dB;

[0133] S1033: Calculate background noise baseline data Standard deviation ; This is a quantitative indicator of the degree of background noise fluctuation, measured in dB.

[0134] S1034: Through formula Determine the adaptive threshold The unit is dB; in the formula This is the CFAR coefficient, corresponding to the preset constant false alarm probability (CFAR = ...). This threshold is dynamically adjusted according to the real-time changes in background noise to avoid missed or false detections caused by changes in environmental noise.

[0135] S104: Determine if there are spectral spikes exceeding the threshold, specifically:

[0136] The raw power spectral density data obtained in step S102 The adaptive threshold obtained in step S103 Frequency-by-frequency comparison, the judgment rule is set as follows: the power values ​​of three or more consecutive adjacent frequency points exceed the adaptive threshold. If only one or two frequency points exceed the threshold, it is determined that narrowband interference has been detected; if only one or two frequency points exceed the threshold, it is determined to be random noise and not considered narrowband interference, and S105 is executed. The original power spectral density data is included. This represents the power spectral density value at the k-th frequency point. This judgment rule can effectively avoid false detections caused by random noise, improve the reliability of interference detection, and ensure that no real narrowband interference signals are missed.

[0137] S105: Maintain filter pass-through mode, output original signal:

[0138] When no narrowband interference is detected or only random noise is detected, the interference suppression execution unit receives the interference-free command from the interference detection and parameter estimation unit and controls all notch filter units of the cascaded IIR notch filter array module to remain in pass-through mode. At this time, the baseband complex signal split by the signal distributor and buffer module to the interference suppression execution unit is sent directly to the baseband correlation and demodulation module without any filtering processing, passing through the cascaded IIR notch filter array module without loss, and proceeding to step S110. This ensures the integrity of the BeiDou useful signal and avoids signal power loss or phase distortion caused by unnecessary filtering. At the same time, the IIR coefficient real-time generation engine remains in standby mode and does not update the coefficient matrix, reducing the system hardware resource consumption.

[0139] S106: Extract the center frequency of the interference. And the dry letter ratio JSR, specifically:

[0140] Once narrowband interference is detected, the interference frequency identification and bandwidth estimation module initiates an improved successive elimination algorithm to accurately analyze and extract parameters from spectral peaks exceeding the threshold. The specific operation process is as follows:

[0141] First, mark all power values ​​that exceed the adaptive threshold. The frequency points are merged into a cluster of interference frequency points, and each cluster corresponds to a narrowband interference, so as to avoid misjudging consecutive frequency points of the same interference as multiple interferences.

[0142] Secondly, for each cluster of interfering frequency points, its frequency range is determined using a neighborhood merging algorithm. , For the cluster's starting frequency index, The cluster termination frequency index is used to remove isolated frequency points exceeding the threshold at the edge of the cluster, ensuring the accuracy of the interference frequency range.

[0143] Subsequently, the center frequency index of the interference was calculated using the centroid method. The calculation formula is:

[0144]

[0145] in, This is the index of the center frequency of the interference; The summation symbol represents summation from... arrive Sum the corresponding values ​​for all frequency points; Frequency index; Let be the power spectral density value at the k-th frequency point; this formula can accurately pinpoint the center location of interference, avoiding frequency point shifts caused by spectral fluctuations.

[0146] Finally, based on the correspondence between the frequency index and the actual frequency:

[0147]

[0148] in, MSPS is the baseband sampling rate; The number of FFT points; index the center frequency point. Converted to actual interference center frequency The unit is Hz;

[0149] Simultaneously, the peak power of the interference frequency cluster is extracted. The unit is dBW, which is the maximum power spectral density within the cluster;

[0150] Background noise baseline data extracted using sliding window mid-value filtering Based on the broadband spectral characteristics of the BeiDou useful signal, the average power of the BeiDou useful signal is calculated. The unit is dBW;

[0151] Then calculate the dry signal ratio (JSR) using the formula:

[0152]

[0153] The interference-to-signal ratio (JSR), measured in dB, is used to quantify the ratio of interference intensity to useful signal intensity and serves as a convergence factor. This provides a basis for the calculation.

[0154] If multiple narrowband interferences are detected, i.e., multiple independent clusters of interfering frequency points, the above parameter extraction process is executed independently for each cluster, outputting multiple sets of parameters. (Interference center frequency) (Interference -3dB bandwidth) and JSR (Interference-to-Signal Ratio) parameters ensure accurate identification of multi-point interference.

[0155] S107: Calculate the convergence factor of the IIR notch filter based on the interference bandwidth. And the location of the poles, specifically:

[0156] The IIR coefficient real-time generation engine receives interference parameters output by the interference frequency point identification and bandwidth estimation module, including... , JSR, in sequence, completes the normalization of interference frequencies. Convergence factor Real-time calculation of pole locations ensures the accuracy and real-time nature of coefficient calculation. The specific calculation process is as follows:

[0157] S1071: Calculate the normalized interference frequency The calculation formula is:

[0158]

[0159] in, The interference center frequency is expressed in Hz. MSPS is the sampling rate of the baseband complex signal, measured in Hz. Let π be the value of a circle, which is 3.1416 in this example; The range of values ​​is strictly controlled within To ensure that the frequency response characteristics of the notch filter are matched, and to avoid filter failure due to the normalized frequency being out of range;

[0160] S1072: Calculate the convergence factor The convergence factor is a core parameter controlling the stopband width of a notch filter. Its value directly determines the interference suppression accuracy and filter stability. The calculation formula is as follows:

[0161]

[0162] in, Interference -3dB bandwidth, in Hz. This refers to the baseband sampling rate. The signal-to-dryness ratio is expressed in dB. The range of values ​​is strictly controlled within This formula achieves adaptive adjustment of the convergence factor: when the interference bandwidth... When smaller, A smaller value narrows the stopband of the notch filter, improving interference suppression accuracy; when the interference bandwidth... When the JSR is relatively large or the interference-to-signal ratio is high, By appropriately increasing the value, the stopband width can be widened while improving the stability of the filter, thus avoiding self-oscillation of the filter due to excessive interference.

[0163] S1073: Determine the pole locations in the z-plane. The pole locations directly affect the stability of the filter. The calculation formula is as follows:

[0164]

[0165] in, Let these be the coordinates of the pole in the z-plane; The modulus of the pole, because This ensures that the poles lie within the unit circle in the z-plane; is a natural constant with a value of 2.7183; The imaginary unit, ; The angle of the pole corresponds to the normalized interference frequency, ensuring that the stopband center of the notch filter is precisely matched with the interference center frequency, thus achieving accurate filtering of interference.

[0166] S108: Update the coefficient matrix of the corresponding element in the cascaded notch array, specifically:

[0167] The IIR coefficient real-time generation engine calculates the normalized interference frequency based on step S107. and convergence factor The coefficient matrix of the second-order IIR notch filter is generated, and its generation strictly follows the transfer function of the notch filter to ensure the accuracy of the coefficients. Specifically, the numerator coefficients are generated based on the transfer function. , , and denominator coefficients , The transfer function is expressed as:

[0168]

[0169] The generated molecular coefficient , , and denominator coefficient , All coefficients are processed using 18-bit fixed-point quantization, balancing computational accuracy with hardware resource consumption, and avoiding a decrease in filtering performance due to quantization errors.

[0170] After the coefficient matrix is ​​generated, it is updated to the corresponding notch filter units of the cascaded IIR notch filter array module using a parallel loading method: if a single narrowband interference is detected, only one notch filter unit is activated and its coefficient matrix is ​​updated; if multiple narrowband interferences are detected, notch filter units matching the number of interference frequencies are activated, and each notch filter unit loads the coefficient matrix corresponding to the interference frequency, ensuring that each stage of the notch filter operates independently for a specific interference frequency. The time delay of the entire coefficient update process is strictly controlled to ≤1μs, ensuring that the filter can quickly respond to interference changes and adapt to dynamic frequency hopping interference scenarios. Unactivated notch filter units remain in pass-through mode and do not affect signal transmission.

[0171] S109: The signal flows through a cascaded notch filter for time-domain filtering and suppression. Specifically:

[0172] The baseband complex signal, which is branched from the signal distributor and buffer module to the interference suppression execution unit, flows through the updated cascaded IIR notch filter array module in a pipeline manner to achieve real-time time-domain filtering and suppression of narrowband interference. The working process is as follows:

[0173] The baseband complex signal, including I and Q channels, is first input to the first-stage activated notch filter unit. This unit performs real-time filtering according to a time-domain recursive formula, filtering out narrowband interference at the corresponding frequency point. The time-domain recursive formula is expressed as:

[0174]

[0175] in, This is the input signal of the notch filter in the nth sampling period at the current moment, which is the baseband complex signal to be filtered; This represents the delay value of the input signal in the (n-1)th sampling period of the previous sampling period of the notch filter; This represents the delay value of the input signal in the (n-2)th sampling period of the first two sampling periods of the notch filter; This is the output signal of the unit at the current moment, i.e., the signal after preliminary purification; This represents the delay value of the output signal in the (n-1)th sampling period of the previous sampling period of the notch filter; This represents the delay value of the output signal in the (n-2)th sampling period of the first two sampling periods of the notch filter; ; ; ; ; .

[0176] If multiple narrowband interferences exist, the initial purified signal output from the first-stage notch filter unit is input to the second-stage activated notch filter unit. This unit performs the same time-domain recursive filtering operation for the second interference frequency, and so on, until the signal flows through all activated notch filter units, completing the synchronous filtering of all narrowband interferences. Each activated notch filter unit has a stopband rejection ≥40dB, ensuring deep filtering of interference signals; passband ripple ≤0.1dB, group delay fluctuation ≤1μs, minimizing damage to useful BeiDou signals and ensuring signal phase and amplitude integrity. The filtering process uses pipelined processing, synchronized with the signal sampling rate of 20MSPS, without adding additional signal processing delay.

[0177] S110: The purified signal is sent to the baseband correlator for acquisition and tracking, and then returns to S101. Specifically:

[0178] The purified baseband complex signal output from the cascaded IIR notch filter array module is buffered and then sent to the baseband correlation and demodulation module. This module sequentially completes signal acquisition, tracking, and demodulation, as follows:

[0179] The acquisition module adopts parallel code phase search and carrier frequency search algorithms, combined with 1ms coherent integration and 16 times incoherent integration to improve the acquisition gain, quickly acquire Beidou satellite signals, and the acquisition time is ≤1s, ensuring that useful signals can be quickly locked after interference suppression;

[0180] The tracking module accurately tracks the carrier and pseudocode of the satellite signal through a carrier tracking loop (Costas loop) and a code tracking loop (Delay Locked Loop DLL). The bandwidth of the tracking loop is dynamically adjusted (1-10Hz) according to the carrier-to-noise ratio of the signal. When the carrier-to-noise ratio is low, the loop bandwidth is reduced to improve tracking stability. When the carrier-to-noise ratio is stable, the loop bandwidth is increased to improve the tracking response speed.

[0181] The demodulation module extracts the BeiDou navigation message from the tracked signal and calculates navigation measurement values ​​such as pseudorange and carrier phase. The measurement accuracy meets the positioning requirements of the BeiDou receiver.

[0182] The system returns to step S101 to continue collecting the next set of baseband complex signals, realizing continuous closed-loop processing of interference detection and suppression, and ensuring that the Beidou receiver can work continuously and stably in complex electromagnetic environments.

[0183] It should be noted that the navigation and positioning result output module receives navigation measurements and navigation messages from the baseband correlation and demodulation module, and performs positioning calculations using the least squares method or Kalman filter algorithm at a frequency of 10Hz. It outputs navigation and positioning results such as latitude, longitude, altitude, speed, and time, and also outputs them externally through standard interfaces such as serial port and CAN bus. Furthermore, the navigation and positioning result output module monitors signal carrier-to-noise ratio and interference suppression status in real time, feeding this status information back to the interference detection and parameter estimation unit. This enables dynamic adjustment of the detection threshold, forming a complete closed loop of interference detection, parameter estimation, interference suppression, and navigation and positioning.

[0184] The above description is merely a specific example of the present invention and does not constitute any limitation on the present invention. Obviously, those skilled in the art, after understanding the content and principles of the present invention, may make various modifications and changes in form and detail without departing from the principles and structure of the present invention; however, these modifications and changes based on the spirit of the present invention are still within the scope of protection of the claims of the present invention.

Claims

1. A narrowband interference suppression system for BeiDou navigation, characterized in that, It includes a Beidou radio frequency front-end module, a high-speed ADC sampling module, a digital down-conversion (DDC) module, a signal distributor and buffer module, an interference detection and parameter estimation unit, an interference suppression execution unit, a baseband correlation and demodulation module, and a navigation and positioning result output module; The Beidou RF front-end module, high-speed ADC sampling module, digital down-conversion (DDC) module, and signal distributor and buffer module are connected in sequence; the signal distributor and buffer module are also connected to the interference detection and parameter estimation unit and the interference suppression execution unit, respectively; the interference detection and parameter estimation unit and the interference suppression execution unit communicate bidirectionally; the interference suppression execution unit is connected to the baseband correlation and demodulation module; The baseband correlation and demodulation module is connected to the navigation and positioning result output module; The Beidou radio frequency front-end module is used to receive multi-band radio frequency signals from Beidou satellites, process the signals, and down-convert them to intermediate frequency analog signals. The high-speed ADC sampling module is used to perform analog-to-digital conversion on the intermediate frequency analog signal and output a digital intermediate frequency signal; The digital downconversion (DDC) module is used to convert the digital intermediate frequency signal into a zero intermediate frequency baseband complex signal. The signal distributor and buffer module are used to synchronously buffer the baseband complex signal, and at the same time divide the signal into two synchronous data streams and transmit them to the interference detection and parameter estimation unit and the interference suppression execution unit respectively. The interference detection and parameter estimation unit includes a fast FFT and PSD calculation module, a dynamic threshold comparator, and an interference frequency point identification and bandwidth estimation module connected in sequence. The fast FFT and PSD calculation module performs FFT transformation on the baseband complex signal and calculates the real-time power spectral density. The dynamic threshold comparator generates an interference detection threshold that dynamically adjusts with background noise. The interference frequency point identification and bandwidth estimation module extracts the center frequency, -3dB bandwidth, and interference-to-signal ratio of the narrowband interference. The interference suppression execution unit includes an IIR coefficient real-time generation engine and a cascaded IIR notch filter array module; wherein, the IIR coefficient real-time generation engine is used to calculate and generate the coefficient matrix of the second-order IIR notch filter based on the interference parameters; the cascaded IIR notch filter array module is used to receive the coefficient matrix and perform time-domain precise filtering on the baseband complex signal. The baseband correlation and demodulation module is used to capture, track and demodulate the filtered and purified signal, and extract the navigation message and navigation measurement values ​​of the Beidou signal; The navigation and positioning result output module is used to complete the positioning calculation and output the navigation and positioning result based on the navigation measurement value and navigation message.

2. The narrowband interference suppression system for BeiDou navigation according to claim 1, characterized in that, The dynamic threshold comparator in the interference detection and parameter estimation unit uses a sliding window mid-range filtering algorithm to remove the broadband spectral components of the BeiDou useful signal, extract the background noise baseline, and calculate the adaptive threshold for interference detection in combination with the preset constant false alarm rate (CFAR).

3. A narrowband interference suppression system for BeiDou navigation according to claim 1, characterized in that, The cascaded IIR notch filter array module consists of 1 to 8 second-order IIR notch filter units cascaded in series. The notch filter unit is a direct type II structure. The number of activated notch filter units matches the number of frequency points of narrowband interference. Each notch filter unit independently filters for a specific interference frequency point.

4. A narrowband interference suppression system for BeiDou navigation according to claim 1, characterized in that, The IIR coefficient real-time generation engine in the interference suppression execution unit calculates the normalized interference frequency based on the interference center frequency, expressed as: ， in, The actual center frequency of narrowband interference. The sampling rate of the baseband complex signal; Calculate the convergence factor r based on the interference bandwidth and the interference-to-signal ratio: ， in, JSR is the interference bandwidth and the signal-to-interference ratio. The value range is [0,π], and the value range of r is 0. <r<1。 5. A narrowband interference suppression method for BeiDou navigation, implemented based on the narrowband interference suppression system for BeiDou navigation as described in any one of claims 1 to 4, characterized in that, Includes the following steps: S101: Acquire BeiDou intermediate frequency digital signals and perform time-domain buffering: After the BeiDou satellite radio frequency signal is sequentially down-converted, analog-to-digital converted, and digitally down-converted, a zero intermediate frequency baseband complex signal is obtained and synchronously buffered; S102: Perform N-point FFT to obtain real-time signal power spectral density. PSD: Apply a window function to the buffered baseband complex signal and then perform an N-point radix-2 FFT transform to calculate the power spectral density at each frequency point using the periodogram method. S103: Calculate the adaptive noise baseline threshold based on median filtering: Extract the background noise baseline by performing sliding window median filtering on the power spectral density data, and calculate the dynamically adjusted adaptive threshold for interference detection based on constant false alarm probability. S104: Determine if there are spectral spikes exceeding the threshold: Compare the power spectral density data with the adaptive threshold point by point. If S or more consecutive adjacent frequency points exceed the threshold, it is determined that narrowband interference has been detected, and S106 is executed; otherwise, S105 is executed. S105: Maintain the filter in pass-through mode and output the original signal: Control the cascaded IIR notch filter array module to maintain the pass-through mode, the baseband complex signal passes through without loss and is sent to the baseband correlation and demodulation module, and proceed to step S110. S106: Extract the center frequency of the interference. Interference-to-signal ratio (JSR): Based on the improved successive elimination algorithm to lock the center frequency of the interference, the interference-to-signal ratio is obtained by calculating the ratio of the peak power of the interference to the average power of the BeiDou useful signal. S107: Calculate the IIR notch filter convergence factor r and pole positions based on the interference bandwidth: Calculate the normalized interference frequency based on the interference center frequency, calculate the convergence factor based on the interference bandwidth and interference-to-signal ratio, and determine the pole positions in the z-plane. S108: Update the coefficient matrix of the corresponding unit in the cascaded IIR notch filter array module: Generate the coefficient matrix of the second-order IIR notch filter based on the normalized interference frequency and convergence factor, and load and update it to the corresponding notch filter unit in parallel. S109: Signal flows through cascaded notch filters for time-domain filtering and suppression: The baseband complex signal flows through the updated cascaded IIR notch filter array module, and each activated unit completes real-time filtering according to the time-domain recursive formula. S110: The purified signal is sent to the baseband correlator for acquisition and tracking: the filtered purified signal is acquired, tracked and demodulated, navigation measurement values ​​and messages are extracted and the positioning calculation is completed, and then it returns to S101 to realize closed-loop processing.

6. A narrowband interference suppression method for BeiDou navigation according to claim 5, characterized in that, In step S102, N is set to 2048, and a Hamming window is used as the window function; the formula for calculating the power spectral density is: ， in, For frequency domain complex signals The modulus; The square of the amplitude of the in-phase component at the k-th frequency point; It is the square of the amplitude of the orthogonal component at the k-th frequency point.

7. A narrowband interference suppression method for BeiDou navigation according to claim 5, characterized in that, In step S103, a 2n+1 sliding window is used to perform median filtering. The sliding window is formed by taking the power values ​​of n frequencies before and after the current frequency as the center, and the median value is obtained after sorting and selecting the median value to obtain the background noise baseline data. The calculation process for the adaptive threshold is shown in the following formula: ， in, This represents the baseline power value for background noise. The constant false alarm probability coefficient; This represents the standard deviation of the background noise baseline data.

8. A narrowband interference suppression method for BeiDou navigation according to claim 5, characterized in that, The process of calculating the convergence factor r and pole locations of the IIR notch filter in step S107 includes the following steps: S1071: Calculate the normalized interference frequency As shown in the following formula: ， in, The actual center frequency of narrowband interference. The sampling rate of the baseband complex signal; The value range is [0, π]. S1072: Calculate the convergence factor As shown in the following formula: ； in, The interference bandwidth is JSR, and the signal-to-interference ratio (SSR) is r; the value of r ranges from 0 to 1. <r<1; S1073: Determine the location of the pole in the z-plane using the following formula: ， in, It is a natural constant. It is the imaginary unit.

9. A narrowband interference suppression method for BeiDou navigation according to claim 5, characterized in that, The transfer function of the second-order IIR notch filter in step S108 is: ， in, The normalized interference frequency is r; the convergence factor is r. Delay operator for units; It is a second-order unit delay operator.

10. A narrowband interference suppression method for BeiDou navigation according to claim 5, characterized in that, The time-domain recursive formula for the second-order IIR notch filter in step S109 is as follows: ， in, This is the input signal of the notch filter in the nth sampling period at the current moment; This represents the delay value of the input signal in the (n-1)th sampling period of the previous sampling period of the notch filter; This represents the delay value of the input signal in the (n-2)th sampling period of the first two sampling periods of the notch filter; This represents the delay value of the output signal in the (n-1)th sampling period of the previous sampling period of the notch filter; This represents the delay value of the output signal in the (n-2)th sampling period of the first two sampling periods of the notch filter; ; ; ; ; If multiple narrowband interferences are detected, the multi-stage notch filter units operate in series, with each stage independently filtering a specific interference frequency.

Images