Adaptive pulse interference suppression method and device, computer equipment and storage medium

Abstract

The invention relates to a self-adaptive pulse interference suppression method and device, computer equipment and a storage medium. The method comprises the following steps: carrying out sliding window energy detection on a digital intermediate frequency signal output by the front end of a satellite navigation receiver to obtain a pulse interference duty ratio, carrying out FFT (Fast Fourier Transform) on an interference time period signal to extract an effective bandwidth, establishing a carrier-to-noise ratio loss estimation model of two strategies of time domain zero setting and frequency domain spectral line elimination, substituting parameters to calculate a loss value, and calculating the loss value according to the carrier-to-noise ratio loss estimation model. And preferentially executing interference suppression. According to the method, intelligent adaptation of an interference suppression strategy is realized, carrier-to-noise ratio loss is minimized, the robustness and availability of a receiver in a complex electromagnetic environment are improved, the algorithm compatibility is high, engineering integration is easy, and the method has the expansion potential of combining machine learning optimization.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of satellite navigation signal processing, and in particular to an adaptive impulse interference suppression method and device, a computer device and a storage medium. BACKGROUND

[0002] The navigation signal received by a global navigation satellite system receiver is extremely weak and is usually submerged in thermal noise. This characteristic makes it extremely sensitive to intentional or unintentional impulse radio frequency interference. With the increasingly complex radio electromagnetic environment, satellite navigation receivers are facing more and more man-made interference threats, among which impulse interference is a common and serious type of interference. Impulse interference usually appears as a short-time high-intensity signal that is periodic or aperiodic, and its energy is concentrated in certain time segments, which easily leads to receiver front-end saturation, correlator lock loss, positioning accuracy degradation, and even complete failure.

[0003] At present, the mainstream anti-impulse interference method in satellite navigation receivers is time-domain impulse detection and zeroing. This method continuously monitors the power or amplitude of the received signal in the time domain, and when the instantaneous power of the signal exceeds the dynamic threshold set according to the noise base, it is determined to be impulse interference, and the sampling data in this period is zeroed or greatly attenuated. This method is effective when the pulse duty cycle (the ratio of the interference duration to the period) is low (such as less than 10%).

[0004] However, when high-duty-cycle impulse interference is encountered (such as greater than 50%), the inherent defects of this method are exposed: since the navigation signal itself is continuously present, widely zeroing the time-domain sampling points will directly result in a serious loss of effective navigation signal energy. This loss is reflected as a significant decrease in receiver noise figure, which in turn leads to a series of serious consequences, including reduced acquisition sensitivity, unstable tracking loops, and deteriorated positioning accuracy.

[0005] In addition, the prior art generally uses a "one-size-fits-all" strategy, i.e., regardless of the characteristics of the interference, the same time-domain zeroing mechanism is used, and there is a lack of ability to make optimized decisions based on actual interference parameters. For some narrow-band but high-duty-cycle impulse interference (such as modulated periodic pulses), if an alternative method such as frequency-domain spectral line rejection is used, it may achieve less signal damage. SUMMARY

[0006] Therefore, it is necessary to provide an adaptive impulse interference suppression method, device, computer device and storage medium that can adaptively select the optimal suppression strategy according to the actual physical characteristics of the impulse interference.

[0007] An adaptive impulse interference suppression method, the method comprising:

[0008] acquiring a digital intermediate frequency signal, the digital intermediate frequency signal being output by a satellite navigation receiver front end and containing a navigation signal and impulse interference; performing sliding window energy detection on the digital intermediate frequency signal to identify an impulse interference time period, and counting a ratio of an interference duration to a total time length in a unit time to obtain a duty cycle of the impulse interference; performing fast Fourier transform on the digital intermediate frequency signal corresponding to the impulse interference time period to obtain a signal spectrum, and extracting an effective bandwidth of the impulse interference based on the signal spectrum; respectively establishing a carrier-to-noise ratio loss estimation model corresponding to the time domain zeroing method and the frequency domain spectral line rejection method, and bringing the duty cycle, the effective bandwidth, and a processing bandwidth of the navigation signal and a pseudo-random code rate into the carrier-to-noise ratio loss estimation model to calculate carrier-to-noise ratio loss estimation values under two kinds of suppression strategies; comparing the carrier-to-noise ratio loss estimation values corresponding to the two kinds of suppression strategies, and selecting a strategy with smaller carrier-to-noise ratio loss to perform interference suppression, thereby realizing adaptive impulse interference suppression.

[0009] In one embodiment, the extracting the effective bandwidth of the impulse interference comprises: calculating an interval between two frequency points at which a main lobe of the signal spectrum drops from a peak value to -3dB, and determining the interval as the effective bandwidth of the impulse interference.

[0010] In one embodiment, the carrier-to-noise ratio loss estimation model corresponding to the time domain zeroing method is expressed as:

[0011] In the above formula, Duty cycle represents the duty cycle of the impulse interference.

[0012] In one embodiment, the carrier-to-noise ratio loss estimation model corresponding to the frequency domain spectral line rejection method is expressed as:

[0013] In the above formula, C / N0 represents a pseudo-random code rate of the navigation signal, Sinc represents a Sinc function, BW represents a processing bandwidth of the navigation signal, BW represents an effective bandwidth of the impulse interference, f represents a frequency.

[0014] In one embodiment, the comparing the carrier-to-noise ratio loss estimation values corresponding to the two kinds of suppression strategies and selecting a strategy with smaller carrier-to-noise ratio loss to perform interference suppression comprises: if the carrier-to-noise ratio loss estimation value corresponding to the time domain zeroing method is smaller, then the signal is processed by using a threshold-free time domain zeroing method; If the C / N loss estimation value corresponding to the frequency domain spectral line rejection method is smaller, the signal block is subjected to a fast Fourier transform and then a threshold-free frequency domain spectral line rejection operation is performed.

[0015] In one embodiment, when the frequency domain spectral line rejection method is used, the number of FFT points used for fast Fourier transform of the signal block is an exponential power of 2.

[0016] The application also provides an adaptive impulse interference suppression device, which comprises: A signal receiving module is configured to acquire a digital intermediate frequency signal, wherein the digital intermediate frequency signal is output by a satellite navigation receiver front end and contains a navigation signal and impulse interference. A duty cycle calculation module is configured to perform sliding window energy detection on the digital intermediate frequency signal, identify an impulse interference time period, and calculate a ratio of interference duration to total time in a unit of time to obtain a duty cycle of the impulse interference. An effective bandwidth obtaining module is configured to perform fast Fourier transform on the digital intermediate frequency signal corresponding to the impulse interference time period to obtain a signal spectrum, and extract an effective bandwidth of the impulse interference based on the signal spectrum. A C / N loss estimation value calculation module is configured to establish a corresponding C / N loss estimation model according to the time domain zeroing method and the frequency domain spectral line rejection method, and calculate C / N loss estimation values under two suppression strategies by inputting the duty cycle, the effective bandwidth, and a processing bandwidth of the navigation signal and a pseudo-random code rate into the C / N loss estimation model. A suppression strategy adaptation module is configured to compare the C / N loss estimation values corresponding to the two suppression strategies, select a strategy with smaller C / N loss to perform interference suppression, and realize adaptive impulse interference suppression.

[0017] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps in the adaptive impulse interference suppression method when executing the computer program.

[0018] A computer readable storage medium stores a computer program, and the computer program realizes the steps in the adaptive impulse interference suppression method when executed by a processor.

[0019] The adaptive impulse interference suppression method, device, computer device and storage medium described above, through sliding window energy detection on the digital intermediate frequency signal output by the satellite navigation receiver front end, identifies the impulse interference time period, counts the ratio of the interference duration to the total duration in a unit time, obtains the duty cycle of the impulse interference, then performs fast Fourier transform on the digital intermediate frequency signal corresponding to the impulse interference time period to obtain the signal spectrum, extracts the effective bandwidth of the impulse interference based on the signal spectrum, respectively establishes the carrier-to-noise ratio loss estimation model according to the time domain zeroing method and the frequency domain spectral line rejection method, and brings the duty cycle, the effective bandwidth and the processing bandwidth of the navigation signal and the pseudo-random code rate into the carrier-to-noise ratio loss estimation model to calculate the carrier-to-noise ratio loss estimation value under the two suppression strategies, compares the carrier-to-noise ratio loss estimation values corresponding to the two suppression strategies, selects the strategy with smaller carrier-to-noise ratio loss to perform interference suppression, and realizes adaptive impulse interference suppression.

[0020] The method realizes intelligent adaptation of interference suppression strategies, minimizes the carrier-to-noise ratio loss, improves the robustness and usability of the satellite navigation receiver in a complex electromagnetic environment, has strong algorithm compatibility and is easy to be integrated into engineering, and also has the extension potential of further optimization combined with machine learning. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 It is a flowchart of the adaptive impulse interference suppression method in an embodiment; Figure 2 It is a specific flowchart of the method executed in an embodiment; Figure 3 It is a comparison diagram of the predicted value and the measured value of the carrier-to-noise ratio loss of the time domain impulse zeroing processing obtained by using the method in an experiment; Figure 4 It is a comparison diagram of the predicted value and the measured value of the carrier-to-noise ratio loss of the frequency domain spectral line rejection processing obtained by using the method in an experiment; Figure 5 It is a measured result diagram of the carrier-to-noise ratio loss obtained by using the time domain impulse zeroing method and the method in an experiment; Figure 6 It is a structural block diagram of the adaptive impulse interference suppression device in an embodiment; Figure 7 It is an internal structure diagram of the computer device in an embodiment. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application is further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0023] In view of the problem that in the existing satellite navigation anti-pulse interference technology, the fixed time domain zero strategy leads to excessive noise ratio loss in high duty cycle interference scenarios, an adaptive pulse interference suppression method is proposed in the present application, which specifically includes the following steps: In step S100, a digital intermediate frequency signal is obtained, which is output by a satellite navigation receiver front end and contains a navigation signal and pulse interference.

[0024] In step S110, a sliding window energy detection is performed on the digital intermediate frequency signal to identify a pulse interference time period, and a ratio of interference duration to total time duration within a unit time is calculated to obtain a duty cycle of the pulse interference.

[0025] In step S120, a fast Fourier transform is performed on the digital intermediate frequency signal corresponding to the pulse interference time period to obtain a signal spectrum, and an effective bandwidth of the pulse interference is extracted based on the signal spectrum.

[0026] In step S130, a carrier-to-noise ratio loss estimation model is established based on the time domain zero method and the frequency domain spectral line rejection method, and the duty cycle, the effective bandwidth, and the processing bandwidth of the navigation signal and the pseudo-random code rate are input into the carrier-to-noise ratio loss estimation model to calculate the carrier-to-noise ratio loss estimation value under the two suppression strategies.

[0027] In step S140, the carrier-to-noise ratio loss estimation values corresponding to the two suppression strategies are compared, and the strategy with smaller carrier-to-noise ratio loss is selected to perform interference suppression, thereby realizing adaptive pulse interference suppression.

[0028] In the present method, by establishing a carrier-to-noise ratio loss estimation model combined with the characteristics of the navigation signal, the interference suppression strategy with the least impact on the navigation performance is dynamically selected, thereby effectively suppressing the interference while ensuring the accuracy of receiver acquisition, tracking and positioning.

[0029] In step S100, the digital intermediate frequency signal The radio frequency navigation signal received by the satellite navigation antenna is generated after being down-converted and analog-to-digital converted by the receiver radio frequency front end, and contains the expected satellite navigation signal and possible pulse interference. Among them, the satellite navigation signal can cover any frequency band signal of global navigation satellite systems such as GPS, BDS, GLONASS, Galileo, etc., and the signal characteristics meet the public interface control file specifications of the corresponding system, which is a low-power spread spectrum signal, usually submerged in thermal noise background. The pulse interference is a short-time high-intensity interference signal intruded in the external electromagnetic environment, and its frequency components can cover the intermediate frequency bandwidth of the receiver, which is easy to cause serious interference to subsequent signal acquisition and tracking.

[0030] In step S110, the digital intermediate frequency signal A sliding window energy detection is performed to identify the time period in which the pulse interference occurs. The ratio of the interference duration to the total time duration in a unit time is counted to obtain the duty cycle of the pulse interference , which is expressed as: (1) In formula (1), represents the single pulse duration, represents the pulse repetition period.

[0031] In step S120, based on the pulse interference time period identified in step S110, the signal data in the time period is intercepted from the digital intermediate frequency signal to form a signal block to be analyzed, and a fast Fourier transform (FFT) operation is performed on the signal block to convert the time domain signal to the frequency domain to obtain the corresponding signal spectrum .

[0032] Further, based on the signal spectrum , the effective bandwidth of the pulse interference is extracted, including: calculating the interval between the two frequency points at which the main lobe of the signal spectrum drops from the peak value to -3dB, and determining the difference between the two frequency points as the effective bandwidth of the pulse interference . The effective bandwidth can accurately represent the distribution range of the energy of the pulse interference in the frequency domain, providing a key frequency domain feature parameter for subsequent carrier-to-noise ratio loss modeling and suppression strategy selection.

[0033] In step S130, the time domain zeroing method corresponds to a carrier-to-noise ratio loss estimation model, which is expressed as: (2) In formula (2), is expressed as the duty cycle of the pulse interference. is the estimated value of the carrier-to-noise ratio loss after adopting the time domain zeroing strategy (unit: decibel). The carrier-to-noise ratio loss estimation model shows that the greater the duty cycle, the lower the proportion of the signal retained, and the more obvious the carrier-to-noise ratio drop.

[0034] Further, the frequency domain spectral line rejection method corresponds to a carrier-to-noise ratio loss estimation model, which is expressed as: (3) In formula (3), represents the pseudo-random code rate of the navigation signal, represents the sinc function, represents the processing bandwidth of the navigation signal. Among them, is used to describe the power spectral density shape of the spread spectrum signal. The estimated value of the carrier-to-noise ratio loss (unit: decibel) after the frequency domain spectral line elimination strategy is adopted, and the model considers the actual spectral distribution of the navigation signal, avoiding the error caused by the simple assumption of uniform spectrum, represents the frequency.

[0035] In step S140, the estimated values of the carrier-to-noise ratio loss corresponding to the two suppression strategies are compared, and the strategy with smaller carrier-to-noise ratio loss is selected to perform interference suppression, including: if the estimated value of the carrier-to-noise ratio loss corresponding to the time domain zeroing method is smaller, the non-threshold time domain zeroing method is used to process the signal. If the estimated value of the carrier-to-noise ratio loss corresponding to the frequency domain spectral line elimination method is smaller, the non-threshold frequency domain spectral line elimination operation is performed after the fast Fourier transform of the signal block.

[0036] In this embodiment, by comparing the estimated values of the carrier-to-noise ratio loss corresponding to the two suppression strategies, the optimal interference suppression strategy is adaptively selected according to the comparison result, ensuring that the pulse interference is effectively suppressed while the energy damage to the navigation signal is minimized. When the estimated value of the carrier-to-noise ratio loss corresponding to the time domain zeroing method is smaller, it indicates that the carrier-to-noise ratio loss of the navigation signal by the time domain zeroing method is smaller, and the non-threshold time domain zeroing method is used to perform interference suppression. When the estimated value of the carrier-to-noise ratio loss corresponding to the frequency domain spectral line elimination method is smaller, it indicates that the carrier-to-noise ratio loss of the navigation signal by the frequency domain spectral line elimination method is smaller, and the non-threshold frequency domain spectral line elimination method is used to perform interference suppression.

[0037] Through the above adaptive decision mechanism based on the estimated value of the carrier-to-noise ratio loss, the optimal suppression strategy can be dynamically matched for different duty cycles and different bandwidths of pulse interference, completely abandoning the traditional fixed suppression mode of "one size fits all", and realizing intelligent and low-loss suppression of pulse interference.

[0038] Specifically, if , the non-threshold time domain zeroing method is used for interference suppression, and the signal after interference suppression can be represented as: (4) Specifically, if , the non-threshold frequency domain spectral line elimination method is used for interference suppression, and the signal block is first subjected to FFT to obtain , and then processed according to the following two formulas: (5) (6) In formulas (5) and (6), is the FFT transform of to obtain its frequency spectrum The FFT point number used at this time is generally an exponential power of 2, for example, 128, 256, etc.

[0039] In this embodiment, the inhibited signal is sent to the acquisition, tracking and demodulation module to recover navigation information such as pseudo-range and carrier phase.

[0040] At the same time, the current interference characteristics and decision results can be fed back to the historical database for long-term electromagnetic situation awareness and intelligent strategy learning.

[0041] The following is an example of a preferred embodiment of the method combined with Beidou B3I signals. In this preferred embodiment, the condition setting is as follows: (1) Received signal: Beidou B3I signal (center frequency 1268.52 MHz, code rate 10.23 Mcps), initial carrier-to-noise ratio 45 dBHz; (2) Receiver sampling rate: 20 MHz (quadrature sampling, zero intermediate frequency), processing bandwidth 20 MHz; (3) Interference type: impulse interference, jam-to-signal ratio of impulse interference 60 dB, pulse period 1 ms, duty cycle can be set (initial value set to 0.55), Gaussian noise interference within the pulse, bandwidth can be set (initial value set to 2 MHz), interference carrier frequency is located at the center of the receiver intermediate frequency.

[0042] According to the data processing procedure in Figure 2 , the following is the procedure: First, obtain the digital intermediate frequency signal output by the satellite navigation receiver front end, which contains the expected navigation signal and impulse interference.

[0043] Envelope detection and moving average method are used to detect impulse interference, confirming that a high-intensity pulse of 0.55 ms appears once every 1 ms, and the pulse duty cycle is estimated using formula (1).

[0044] An 8192-point FFT is performed on the interference-containing segment, and the spectrum is observed to find that the interference energy is concentrated near the center frequency, and the -3 dB bandwidth is MHz.

[0045] The carrier-to-noise ratio loss using the time domain zeroing method is represented as:

[0046] The carrier-to-noise ratio loss using the frequency domain spectral line rejection method is represented as:

[0047] Here, the prediction accuracy of the carrier-to-noise ratio loss model is verified, and the verification method is as follows: (1) The bandwidth of the pulse interference is fixed at 2MHz, and the duty cycle of the pulse interference is changed to gradually increase from 0.1 to 0.8. First, the prediction value of the carrier-to-noise ratio loss is calculated by using the prediction model provided by the method, then the time domain pulse zeroing method is used to suppress the interference, the signal after interference suppression is sent to the subsequent acquisition and tracking module, the carrier-to-noise ratio of the navigation signal is estimated, and the carrier-to-noise ratio is compared with the initial carrier-to-noise ratio to obtain the carrier-to-noise ratio loss as the measured value. Figure 3 The comparison chart of the prediction value and the measured value of the carrier-to-noise ratio loss processed by the time domain pulse zeroing method is given.

[0048] (2) The duty cycle of the pulse interference is fixed at 0.2, and the bandwidth of the pulse interference is changed to gradually increase from 0.1 to 0.5. First, the prediction value of the carrier-to-noise ratio loss is calculated by using the prediction model provided by the method, then the frequency domain spectral line rejection method is used to suppress the interference, the signal after interference suppression is sent to the subsequent acquisition and tracking module, the carrier-to-noise ratio of the navigation signal is estimated, and the carrier-to-noise ratio is compared with the initial carrier-to-noise ratio to obtain the carrier-to-noise ratio loss as the measured value. Figure 4 The comparison chart of the prediction value and the measured value of the carrier-to-noise ratio loss processed by the frequency domain spectral line rejection method is given.

[0049] From Figure 3 and Figure 4 It can be seen that the prediction value and the measured value of the carrier-to-noise ratio loss are consistent and well matched, which verifies the effectiveness of the method.

[0050] Further, Therefore, the frequency domain spectral line rejection method is selected for anti-interference processing. The FFT result is normalized with respect to its own modulus, and then the time domain signal is restored through IFFT.

[0051] Further, the signal after interference suppression is sent to the acquisition module, the navigation signal is successfully detected, the tracking loop is stably operated, and the carrier-to-noise ratio measurement value is only decreased by about 1dB, which is much better than the 3.47dB loss of direct zeroing. Experiments show that the method effectively reduces the carrier-to-noise ratio loss by 2.42dB in this scenario, and significantly improves the performance of the satellite navigation receiver under pulse interference.

[0052] Further, the bandwidth of the pulse interference is fixed at 2MHz, and the duty cycle of the pulse interference is changed to gradually increase from 0.1 to 0.8. The time domain pulse zeroing method and the method are used for processing, Figure 5The measured results of the carrier-to-noise ratio loss obtained by the two methods are given. Figure 5 It can be seen from the results that the performances of the two methods are close when the pulse duty cycle is less than or equal to 0.2, but when the pulse duty cycle is greater than 0.2, the carrier-to-noise ratio loss after suppressing the pulse interference by the method is significantly smaller than that by the time-domain pulse zeroing method, fully highlighting the advantages of the method.

[0053] In the above adaptive pulse interference suppression method, the core is to break through the technical shackles of the traditional satellite navigation anti-pulse interference fixed strategy and one-size-fits-all processing, and to build a new technical path of loss quantization prediction and strategy adaptive optimization. Specifically, the carrier-to-noise ratio loss quantization modeling mechanism is created, which is different from the traditional method that only focuses on the presence or absence of interference and ignores the degree of signal damage. The carrier-to-noise ratio loss estimation models of the time-domain zeroing method and the frequency-domain spectral line elimination method are established. The time-domain model directly relates to the pulse duty cycle, and the frequency-domain model introduces the navigation signal processing bandwidth, pseudo-random code rate and Sine function, which fits the power spectrum characteristics of spread spectrum signals, and solves the technical problem that the performance cost of the suppression strategy cannot be quantitatively evaluated, providing a quantitative basis for strategy selection. The adaptive decision logic driven by interference characteristics is proposed, which innovatively takes the time-domain characteristics (duty cycle) and frequency-domain characteristics (effective bandwidth) of pulse interference as decision inputs. By comparing the carrier-to-noise ratio loss prediction values of the two strategies, the suppression scheme with the least damage to the navigation signal is dynamically selected. This logic completely changes the traditional technology which relies on a single time-domain zeroing mode. In the low-duty-cycle interference scenario, the efficiency of the time-domain zeroing is retained, and in the high-duty-cycle, narrow-bandwidth interference scenario, the frequency-domain spectral line elimination is automatically switched to, effectively solving the technical pain points of the traditional method, such as excessive signal loss and rapid decline of carrier-to-noise ratio under high-duty-cycle interference. The anti-interference architecture of time-domain and frequency-domain cooperation is constructed, which is not simply a superposition of the two suppression methods, but an organic connection between them through the loss prediction model, forming a complementary and cooperative processing architecture. It not only avoids the limitations of the time-domain zeroing method in high-duty-cycle scenarios, but also overcomes the inefficiency of the frequency-domain spectral line elimination method in wideband interference scenarios, achieving global optimization of anti-interference performance in different interference scenarios, and providing core technical support for the development of high-reliability satellite navigation receivers in complex electromagnetic environments.

[0054] Furthermore, the method realizes intelligent selection of interference suppression strategies: instead of relying on fixed time-domain zeroing methods, it dynamically selects the optimal path according to the specific characteristics (duty cycle, bandwidth) of pulse interference, significantly improving the adaptability of the system. By quantitatively predicting the performance cost of different methods, it ensures that the method with the least damage to the useful signal is always used, especially suitable for high-duty-cycle, narrow-band pulse interference scenarios, which can effectively avoid excessive signal deletion caused by traditional methods.

[0055] The method has strong compatibility and is easy to integrate. The algorithms involved are standard digital signal processing operations (energy detection, FFT / IFFT, threshold judgment), which can be efficiently implemented on FPGA, DSP or software-defined radio platforms, have good real-time performance, and are easy to embed in existing GNSS receiver architectures.

[0056] The method improves the robustness and usability of the system, and can maintain high capture success rate and tracking stability in complex electromagnetic environments, which helps to shorten the time to first fix and reduce positioning interruption, and meets the demand for high reliability navigation in military, aviation, unmanned systems and other fields.

[0057] At the same time, it has expansion potential and supports the introduction of machine learning models to replace empirical formulas. In the future, it can realize automatic anti-jamming strategy evolution combined with deep reinforcement learning.

[0058] In summary, the method not only solves the problem of rapid performance degradation of traditional methods under high duty cycle pulse interference, but also provides key technical support for building an intelligent anti-jamming GNSS receiver.

[0059] It should be understood that, although Figure 1 The steps in the flowchart are displayed in sequence according to the direction of the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this article, the execution of these steps has no strict order restriction, and these steps can be executed in other order. Moreover, Figure 1 At least part of the steps in the flowchart can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily sequential, but can be executed with at least part of other steps or other steps. Sub-steps or stages are executed in rotation or alternation.

[0060] In one embodiment, as shown in Figure 6 An adaptive pulse interference suppression device is provided, comprising: a signal receiving module 200, a duty cycle calculation module 210, an effective bandwidth obtaining module 220, a carrier-to-noise ratio loss estimation value calculation module 230, and a suppression strategy adaptation module 240, wherein: The signal receiving module 200 is configured to obtain a digital intermediate frequency signal, wherein the digital intermediate frequency signal is output by a satellite navigation receiver front end and contains navigation signals and pulse interference; The duty cycle calculation module 210 is configured to perform sliding window energy detection on the digital intermediate frequency signal, identify the pulse interference time period, and calculate the ratio of the interference duration to the total time in a unit of time to obtain the duty cycle of the pulse interference; The effective bandwidth obtaining module 220 is configured to perform fast Fourier transform on the digital intermediate frequency signal corresponding to the pulse interference time period to obtain a signal spectrum, and extract an effective bandwidth of the pulse interference based on the signal spectrum. The carrier-to-noise ratio loss estimation value calculation module 230 is configured to respectively establish a carrier-to-noise ratio loss estimation model according to the time domain zeroing method and the frequency domain spectral line elimination method, and calculate carrier-to-noise ratio loss estimation values under two suppression strategies by inputting the duty cycle, the effective bandwidth, and the processing bandwidth of the navigation signal and the pseudo-random code rate into the carrier-to-noise ratio loss estimation model. The suppression strategy adaptation module 240 is configured to compare the carrier-to-noise ratio loss estimation values corresponding to the two suppression strategies, and select the strategy with smaller carrier-to-noise ratio loss to perform interference suppression, thereby realizing adaptive pulse interference suppression.

[0061] The specific limitations of the adaptive pulse interference suppression device can be referred to the limitations of the adaptive pulse interference suppression method described above, which will not be repeated here. Each module in the adaptive pulse interference suppression device described above can be realized by software, hardware, and combinations thereof, in whole or in part. Each module described above can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to each module.

[0062] In one embodiment, a computer device is provided, which can be a terminal, and its internal structure diagram can be as shown in Figure 7 The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The network interface of the computer device is configured to communicate with external terminals through network connection. The computer program is executed by the processor to implement an adaptive pulse interference suppression method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or can be a key, trackball, or touchpad arranged on the shell of the computer device. It can also be an external keyboard, touchpad, or mouse, etc.

[0063] Those skilled in the art can understand that Figure 7The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. A specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0064] In one embodiment, a computer device is provided, comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program: obtaining a digital intermediate frequency signal, the digital intermediate frequency signal being output by a satellite navigation receiver front end and containing a navigation signal and impulse interference; performing sliding window energy detection on the digital intermediate frequency signal to identify an impulse interference time period, and calculating a duty cycle of the impulse interference by counting a ratio of an interference duration to a total time duration within a unit time; performing fast Fourier transform on the digital intermediate frequency signal corresponding to the impulse interference time period to obtain a signal spectrum, and extracting an effective bandwidth of the impulse interference based on the signal spectrum; establishing a carrier-to-noise ratio loss estimation model corresponding to each of the time domain zeroing method and the frequency domain spectral line rejection method, and inputting the duty cycle, the effective bandwidth, a processing bandwidth of the navigation signal, and a pseudo-random code rate into the carrier-to-noise ratio loss estimation model to calculate carrier-to-noise ratio loss estimation values under the two suppression strategies; comparing the carrier-to-noise ratio loss estimation values corresponding to the two suppression strategies, and selecting the strategy with smaller carrier-to-noise ratio loss to perform interference suppression, thereby realizing adaptive impulse interference suppression.

[0065] In one embodiment, a computer readable storage medium is provided, having a computer program stored thereon, the computer program being executed by a processor to implement the following steps: obtaining a digital intermediate frequency signal, the digital intermediate frequency signal being output by a satellite navigation receiver front end and containing a navigation signal and impulse interference; performing sliding window energy detection on the digital intermediate frequency signal to identify an impulse interference time period, and calculating a duty cycle of the impulse interference by counting a ratio of an interference duration to a total time duration within a unit time; performing fast Fourier transform on the digital intermediate frequency signal corresponding to the impulse interference time period to obtain a signal spectrum, and extracting an effective bandwidth of the impulse interference based on the signal spectrum; establishing a carrier-to-noise ratio loss estimation model corresponding to each of the time domain zeroing method and the frequency domain spectral line rejection method, and inputting the duty cycle, the effective bandwidth, a processing bandwidth of the navigation signal, and a pseudo-random code rate into the carrier-to-noise ratio loss estimation model to calculate carrier-to-noise ratio loss estimation values under the two suppression strategies; The estimated values of the carrier-to-noise ratio loss corresponding to the two suppression strategies are compared, and the strategy with smaller carrier-to-noise ratio loss is selected to perform interference suppression, so as to realize adaptive pulse interference suppression.

[0066] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware, and the computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments of each method. In the embodiments provided in the present application, any reference to memory, storage, database or other medium can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0067] The technical features of the above embodiments can be combined in any way. To make the description concise, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not contradict, they should be considered as within the scope of the present application.

[0068] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, some modifications and improvements can be made, which are within the scope of the present application. Therefore, the scope of protection of the patent of the present application should be subject to the appended claims.

Claims

1. A method of adaptive impulsive interference mitigation, characterized by, The method comprises: acquiring a digital intermediate frequency signal, the digital intermediate frequency signal being output by a satellite navigation receiver front end and containing a navigation signal and impulse interference; performing sliding window energy detection on the digital intermediate frequency signal to identify an impulse interference time period, and counting a ratio of an interference duration to a total duration within a unit time to obtain a duty cycle of the impulse interference; performing fast Fourier transform on the digital intermediate frequency signal corresponding to the impulse interference time period to obtain a signal spectrum, and extracting an effective bandwidth of the impulse interference based on the signal spectrum; establishing a carrier-to-noise ratio loss estimation model corresponding to a time domain zeroing method and a frequency domain spectral line rejection method respectively, and inputting the duty cycle, the effective bandwidth, and a processing bandwidth of the navigation signal and a pseudo-random code rate into the carrier-to-noise ratio loss estimation model to calculate carrier-to-noise ratio loss estimation values under two kinds of suppression strategies; comparing the carrier-to-noise ratio loss estimation values corresponding to the two kinds of suppression strategies, and selecting a strategy with smaller carrier-to-noise ratio loss to perform interference suppression, thereby realizing adaptive impulse interference suppression.

2. The adaptive pulse interference mitigation method of claim 1, wherein, The extraction of the effective bandwidth of the impulse interference comprises: calculating an interval between two frequency points at which a main lobe of the signal spectrum drops from a peak value to -3dB, and determining the interval as the effective bandwidth of the impulse interference.

3. The adaptive pulse interference mitigation method of claim 1, wherein, The carrier-to-noise ratio loss estimation model corresponding to the time domain zeroing method is represented as: In the above formula, denotes the duty cycle of the pulse interference.

4. The adaptive pulse interference mitigation method of claim 1, wherein, The carrier-to-noise ratio loss estimation model corresponding to the frequency domain spectral line rejection method is represented as: In the above formulae, denotes the pseudo-random code rate of the navigation signal, denotes the sinc function, denotes the processing bandwidth of the navigation signal, denotes the effective bandwidth of the impulse interference, denotes the frequency.

5. The adaptive pulse interference mitigation method of claim 1, wherein, The comparison of the carrier-to-noise ratio loss estimation values corresponding to the two kinds of suppression strategies and the selection of a strategy with smaller carrier-to-noise ratio loss to perform interference suppression comprise: if the carrier-to-noise ratio loss estimation value corresponding to the time domain zeroing method is smaller, then a threshold-free time domain zeroing method is used to process the signal; if the carrier-to-noise ratio loss estimation value corresponding to the frequency domain spectral line rejection method is smaller, then a threshold-free frequency domain spectral line rejection operation is performed on the signal block after fast Fourier transform.

6. The adaptive impulsive interference mitigation method of claim 5, wherein, When the frequency domain spectral line rejection method is used, the number of FFT points used for fast Fourier transform on the signal block is an exponential power of 2.

7. An adaptive impulse interference rejection device, characterized by The device comprises: a signal receiving module configured to acquire a digital intermediate frequency signal, the digital intermediate frequency signal being output by a satellite navigation receiver front end and containing a navigation signal and impulse interference; a duty cycle calculation module configured to perform sliding window energy detection on the digital intermediate frequency signal to identify an impulse interference time period, and count a ratio of an interference duration to a total duration within a unit time to obtain a duty cycle of the impulse interference; an effective bandwidth obtaining module configured to perform fast Fourier transform on the digital intermediate frequency signal corresponding to the impulse interference time period to obtain a signal spectrum, and extract an effective bandwidth of the impulse interference based on the signal spectrum; a carrier-to-noise ratio loss estimation value calculation module configured to establish a carrier-to-noise ratio loss estimation model corresponding to a time domain zeroing method and a frequency domain spectral line rejection method respectively, and input the duty cycle, the effective bandwidth, and a processing bandwidth of the navigation signal and a pseudo-random code rate into the carrier-to-noise ratio loss estimation model to calculate carrier-to-noise ratio loss estimation values under two kinds of suppression strategies; a suppression strategy adaptation module configured to compare the carrier-to-noise ratio loss estimation values corresponding to the two kinds of suppression strategies, and select a strategy with smaller carrier-to-noise ratio loss to perform interference suppression, thereby realizing adaptive impulse interference suppression.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 6.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 6.

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