An adaptive GNSS interference mitigation method

Abstract

The application belongs to the technical field of satellite navigation, and relates to an adaptive GNSS interference suppression method, which comprises the following steps: acquiring a discrete sequence of a GNSS receiving signal, and setting multiple windows with different lengths; performing windowing processing and short-time Fourier transform on the discrete sequence according to the multiple windows, performing energy detection on frequency domain values of the transform results of each window, and judging the number of discrete points that meet a preset first condition; selecting the window with the maximum length from all the windows whose discrete point numbers meet a preset second condition as a normal window; setting a delay window according to the normal window, obtaining normal window transform results and delay window transform results, performing interference elimination and inverse transformation of short-time Fourier transform on the normal window transform results and the delay window transform results respectively, and obtaining time domain signals of a normal windowing channel and a delay windowing channel; superimposing the two time domain signals, and outputting anti-interference data to realize adaptive interference suppression. The application can realize adaptive GNSS interference suppression.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of satellite navigation technology, in particular to an adaptive GNSS interference suppression method. BACKGROUND

[0002] Global Navigation Satellite System (GNSS) is not only used for positioning and navigation, but also penetrates into various applications and markets, especially automatic driving vehicles, ships and aircrafts on land, in the air and at sea.

[0003] However, the application of GNSS always faces a major challenge: these satellite navigation signals are very weak and are extremely susceptible to interference. GNSS interference is a phenomenon in which other radio signals interfere with GNSS signals, which will cause the positioning accuracy of satellite navigation receiving terminals to decrease, or even completely obtain no position information. On the one hand, the GNSS signals received on the earth are extremely weak, about 100 times weaker than the thermal noise of satellite navigation receiving terminals. On the other hand, although various global satellite navigation systems (including GPS, GLONASS, Galileo and Beidou) transmit signals in dedicated frequency bands, there are still many radio signals emitted in the adjacent GNSS frequency band, including VHF, microwave, WIFI, Bluetooth, and 3G, 4G and 5G, etc. The appearance of these signals makes the spectrum very crowded, and some of these signals will overflow into the GNSS frequency band, causing interference to the reception of GNSS signals. In addition, sometimes people will intentionally interfere with GNSS signals for various purposes, and research has shown that various illegal but cheap vehicle-mounted GNSS jammers, handheld GNSS jammers and anti-drone interference devices are on an explosive upward trend.

[0004] Typical GNSS interference types include single-tone interference, impulse interference, narrowband interference and sweep interference, etc. Among them, sweep interference is an interference mode that periodically scans within a certain frequency band at a certain speed. Sweep interference concentrates the interference power on a single frequency point due to its instantaneous narrowband energy, significantly improves the suppression effect, avoids the power dispersion problem of traditional wideband interference, and becomes a common interference mode of GNSS signals.

[0005] In the prior art, the commonly used methods for suppressing GNSS interference include: time-frequency domain transformation method, STFT windowed Fourier transform (FT) method.

[0006] However, the prior art has the following disadvantages: firstly, the STFT window adopts a fixed window length without adaptability, which reduces the universality of signal analysis and makes it difficult to deal with interference signals with different sweep speeds; secondly, the detection threshold needs to be carefully set in the frequency domain to remove interference signals, and the threshold of different devices needs to be measured and set again, which increases the difficulty of deployment. SUMMARY

[0007] Therefore, it is necessary to provide an adaptive GNSS interference suppression method to solve the above technical problems.

[0008] An adaptive GNSS interference suppression method comprises the following steps:

[0009] obtaining a discrete sequence of a GNSS received signal, and setting a plurality of windows with different lengths;

[0010] performing windowing processing and short-time Fourier transform on the discrete sequence according to the plurality of windows to obtain a transform result corresponding to each window;

[0011] performing energy detection on the frequency domain values of the transform result of each window to obtain an energy detection result of each window, and determining the number of discrete points of each window whose energy detection result meets a preset first condition; selecting all windows whose discrete point number meets a preset second condition, and taking the window with the largest length as a normal window; and setting a delay window according to the normal window;

[0012] performing windowing processing and short-time Fourier transform on the discrete sequence according to the normal window and the delay window to obtain a normal window transform result and a delay window transform result;

[0013] performing interference removal on the normal window transform result and the delay window transform result respectively, and performing inverse short-time Fourier transform to obtain a time domain signal of a normal window channel and a time domain signal of a delay window channel;

[0014] superimposing the two time domain signals to output anti-interference data, so as to realize adaptive interference suppression.

[0015] In one embodiment, obtaining a discrete sequence of a GNSS received signal and setting a plurality of windows with different lengths comprises:

[0016] obtaining a discrete sequence of a GNSS received signal, and setting a window length , taking different integer values, the minimum value of , the maximum value of to obtain a plurality of windows with different lengths; wherein is rounded down, is the bottom of the logarithm, is the sampling rate of the receiver AD chip, is the frequency rate of change of the interference signal to be suppressed.

[0017] In one embodiment, the discrete sequence is windowed and short-time Fourier transformed according to a plurality of windows, to obtain a transform result corresponding to each window, including:

[0018] ;

[0019] wherein, is the transform result of the window, is an index of the short-time Fourier transform frame, is an index number of the spectrum obtained after the short-time Fourier transform, is a window function number, corresponding to the discrete signal number and the point number of the window, is the window length, is the discrete time domain signal, is a frame shift representing the point interval between adjacent windows, is a window function, is a natural constant, is an imaginary unit.

[0020] In one embodiment, the window is a Hamming window, and the window function is:

[0021] ;

[0022] wherein, is the window function, is a window function number, is the window length.

[0023] In one embodiment, the first condition is preset as:

[0024] ;

[0025] wherein, is the energy detection result of the window, is a frequency domain value of the transform result of the window.

[0026] In one embodiment, the second condition is preset as:

[0027] ;

[0028] wherein, is the number of discrete points of which the energy detection result of the window meets the preset first condition, is the window length.

[0029] In one embodiment, the delay window is set according to the normal window, including:

[0030] The delay is set according to the normal window , is the window length, and the delay window is obtained.

[0031] In one embodiment, the interference is removed from the normal window transform result and the delay window transform result, respectively, including:

[0032] ;

[0033] wherein,

[0034] ;

[0035] In the formula, is the frequency spectrum data after the interference is removed, is the frequency domain data after the short-time Fourier transform, is the interference removal threshold, is the signal mean value, is the weighting factor, is the standard deviation estimate.

[0036] In one embodiment, the inverse transform of the short-time Fourier transform is performed, including:

[0037] ;

[0038] In the formula, is the time domain signal, is the window length, is the index number of the frequency spectrum obtained after the short-time Fourier transform, is the frequency domain signal, is the natural constant, is the imaginary unit, is the window function sequence number, which corresponds to the discrete signal sequence number and also corresponds to the sequence number of the points of the window.

[0039] In one embodiment, the two time domain signals are superimposed to output the anti-interference data, including:

[0040] ;

[0041] In the formula, is the anti-interference data, is the normal windowed channel time domain data, is the delay channel time domain data, is half of the window length.

[0042] The adaptive GNSS interference suppression method increases the STFT transformation of different window lengths before the frequency domain transformation, selects the appropriate window length by detecting the energy concentration degree after the STFT transformation, the window has the adaptability, sets the interference elimination threshold by the statistical characteristics of the transformed data, eliminates the interference signal, and finally restores the signal by the inverse Fourier transformation, so as to achieve the adaptive interference suppression capability.

[0043] The application determines the window length adaptive to the interference speed of the current interference signal (such as the sweep interference) through the STFT calculation of multiple different window function lengths, further determines the length of the STFT calculation, and then determines the threshold of the post-interference signal in the time-frequency domain by the variance statistical method, realizes the interference elimination, and can improve the anti-interference capability of the satellite navigation receiving terminal variable-speed interference (such as sweep interference); at the same time, the threshold of the interference suppression is determined by the variance statistical method, and the adaptive anti-interference can be realized without relying on the prior information (the prior information is needed in the prior art to determine how much interference is collected and processed, and then the interference is suppressed); moreover, the interference type is not limited, and the application is suitable for the sweep interference, single-tone interference, narrowband interference and pulse interference of GNSS. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 It is a flowchart of an adaptive GNSS interference suppression method in one embodiment;

[0045] Figure 2 It is a schematic diagram of the overlapping windowing (with normal window and delay window) in one embodiment;

[0046] Figure 3 It is an application schematic diagram of an adaptive GNSS interference suppression method in one specific embodiment;

[0047] Figure 4 It is the frequency domain graph before and after the anti-interference in one specific embodiment;

[0048] Figure 5 It is the time domain graph before and after the anti-interference in one specific embodiment;

[0049] Figure 6 It is the frequency domain graph of the GNSS signal capture Doppler signal before the anti-interference in one specific embodiment;

[0050] Figure 7 It is the frequency domain graph of the GNSS signal capture correlation value before the anti-interference in one specific embodiment;

[0051] Figure 8 It is the frequency domain graph of the GNSS signal capture Doppler signal after the anti-interference in one specific embodiment;

[0052] Figure 9 is a frequency domain diagram of the anti-interference GNSS signal acquisition correlation value in one embodiment;

[0053] Figure 10 is a structure block diagram of an adaptive GNSS interference suppression device in one embodiment;

[0054] Figure 11 is an internal structure diagram of a computer device in one embodiment. DETAILED DESCRIPTION

[0055] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application is further described in detail below in combination with 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. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of the present application.

[0056] In addition, the description such as "first", "second" and the like in the present application is only for the purpose of description and cannot be understood as indicating or implying the relative importance of the indicated technical features or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first" and "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "multiple groups" is at least two groups, such as two groups, three groups, etc., unless otherwise explicitly specified and limited.

[0057] In the present application, unless otherwise explicitly specified and limited, the terms "connection", "fixation" and the like should be understood broadly, for example, "fixation" can be fixed connection, or detachable connection, or integral; can be mechanical connection, or electrical connection, or physical connection, or wireless communication connection; can be directly connected, or indirectly connected through an intermediate medium, can be the internal communication of two elements or the interaction relationship between two elements, unless otherwise explicitly limited. For those of ordinary skill in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0058] In addition, the technical solutions of each embodiment of the present application can be combined with each other, but it must be based on the fact that those of ordinary skill in the art can realize it, when the combination of technical solutions appears contradictory or unachievable, it should be considered that the combination of technical solutions does not exist, nor within the scope of protection claimed by the present application.

[0059] The present application provides an adaptive GNSS interference suppression method, as shown in the flowchart, in one embodiment, comprising: Figure 1

[0060] ​Step 101, obtaining a discrete sequence of GNSS receiving signals, and setting a plurality of windows with different lengths.

[0061] Specifically,

[0062] The receiver AD chip (i.e. an analog-to-digital conversion chip, which converts an analog signal into a discrete digital signal) obtains a discrete sequence of GNSS receiving signals (ADC sampling data), and sets a window length as , Taking different integer values, The minimum value of , The maximum value of to obtain a plurality of windows with different lengths; wherein, is the floor function, is the logarithm with base 2, is the sampling rate of the receiver AD chip, with the unit of S / s representing the number of sampling data points per second, is the frequency variation rate of the interference signal to be suppressed, with the unit of Hz / s representing the frequency variation speed per second, and the value is greater than 0.

[0063] In this step, according to the sampling rate of the receiver AD chip and the frequency variation rate of the interference signal to be suppressed, the range of the window length is set to improve the accuracy and resource utilization of interference suppression, and to achieve full utilization of resources.

[0064] The number of specific windows can be set according to actual resources; preferably, the number of windows is 4, and the window lengths are , , , to simultaneously consider the interference accuracy and interference efficiency (for example: setting 4 windows to target different sweep frequency interference with different sweep speeds, respectively taking 7, 8, 9, and 10, and the window lengths are 128 points, 256 points, 512 points, and 1024 points, respectively).

[0065] Step 102, according to the plurality of windows, respectively performing windowing processing and short-time Fourier transform on the discrete sequence to obtain a transform result corresponding to each window.

[0066] Specifically,

[0067] According to the plurality of windows with different lengths, respectively performing windowing processing and short-time Fourier transform on the discrete sequence to obtain a transform result corresponding to each window:

[0068] ;

[0069] In the formula, the transform result of the window, an index of the short-time Fourier transform frame, an index number of the spectrum obtained after the short-time Fourier transform, a window function serial number, which is in one-to-one correspondence with the serial number of the discrete signal and also in one-to-one correspondence with the serial number of the points of the window, a window length, a discrete time-domain signal, a frame shift representing the number of point intervals between adjacent windows, a window function, a natural constant, an imaginary unit, a discrete normalized frequency,

[0070] wherein the window is a Hamming window (i.e., a hamming window), and the window function for the windowing processing is:

[0071] ;

[0072] in the formula, a window function of the Hamming window, a window function serial number, a window length.

[0073] In this step, the transform result is time-frequency two-dimensional spectrum data.

[0074] In step 103, the frequency domain values of the transform result of each window are subjected to energy detection to obtain the energy detection result of each window, and the number of discrete points of each window whose energy detection result satisfies a preset first condition is determined; all windows whose number of discrete points satisfy a preset second condition are selected, and the window with the largest length among them is selected as a normal window; and the delay window is set according to the normal window.

[0075] Specifically:

[0076] The frequency domain values of the transform result of each window are subjected to energy detection to obtain the energy detection result of each window, and the number of discrete points of each window whose energy detection result satisfies a preset first condition is determined;

[0077] The preset first condition is:

[0078] ;

[0079] in the formula, an energy detection result of the window, a frequency domain value of the transform result of the window;

[0080] All windows whose number of discrete points satisfy a preset second condition are selected, and the window with the largest length among them is selected as the best window, and as the normal window (for example: MThe values of 128 points and 256 points meet the calculation N ≤ M / 3 condition, and the value of M is taken as the length of the normal window, and subsequent calculations are performed.

[0081] The preset second condition is:

[0082] ;

[0083] In the formula, is the number of discrete points whose energy detection results meet the preset first condition, is the window length.

[0084] According to the normal window (i.e., the maximum window length of all windows whose number of discrete points meets the preset second condition) , the delay point number is set to , is the window length, and the delay window is obtained; that is, the input signal sequence is delayed by 1 / 2 of the window length (the ADC sampling data sequence is delayed by sampling points), and then the windowing processing is performed, as shown in Figure 2 .

[0085] In this step, the delay window is set to form a delay windowing channel, so as to reduce the signal-to-noise ratio loss caused by windowing through overlapping windowing, and compensate for the signal energy loss after windowing.

[0086] Step 104: According to the normal window and the delay window, the discrete sequence is respectively subjected to windowing processing and short-time Fourier transform, and the normal window transform result and the delay window transform result are obtained.

[0087] In this step, the normal window transform result and the delay window transform result are time-frequency two-dimensional spectrum data.

[0088] It should be noted that how to perform windowing processing and short-time Fourier transform belongs to the prior art, and will not be described here.

[0089] Step 105: The normal window transform result and the delay window transform result are respectively subjected to interference elimination and inverse transformation of short-time Fourier transform, and the time-domain signal of the normal windowing channel and the time-domain signal of the delay windowing channel are obtained.

[0090] Specifically:

[0091] The normal window transform result and the delay window transform result are respectively subjected to interference elimination:

[0092] ;

[0093] In the formula,

[0094] ;

[0095] wherein, is the frequency spectrum data after interference rejection, is the frequency domain data after short-time Fourier transform, is the interference rejection threshold, is the signal mean value, is the weighting factor, which can be actually taken as 0.3, is the standard deviation estimation;

[0096] The interference rejection results of the normal window transform result and the delay window transform result are respectively subjected to inverse short-time Fourier transform, and the two-way time-frequency signals after interference rejection are transformed from the frequency domain to the time domain to obtain the time domain signal of the normal window channel and the time domain signal of the delay window channel:

[0097] ;

[0098] wherein, is the time domain signal, is the window length, which is equal to the inverse FFT point number, is the index number of the frequency spectrum obtained after short-time Fourier transform, is the frequency domain signal, is the natural constant, is the imaginary unit, is the window function serial number, which corresponds to the discrete signal serial number and the window point serial number.

[0099] In this step, the same interference rejection method is adopted for the STFT calculation of the two-way parallel normal window channel and delay window channel, and the threshold value of interference rejection is estimated by a statistical method, without prior information, which is a self-adaptive interference rejection method.

[0100] Step 106, superimposing the two-way time domain signals to output the anti-interference data, so as to realize adaptive interference suppression.

[0101] Specifically:

[0102] The two-way time domain signals are superimposed (i.e. overlap addition) to output the anti-interference data:

[0103] ;

[0104] wherein, is the anti-interference data, is the normal window channel time domain data (i.e. normal channel time domain data), is the delay window channel time domain data (i.e. delay channel time domain data), half of the window length, i.e. .

[0105] In this step, how to superimpose the two signals belongs to the prior art, and will not be repeated here.

[0106] The adaptive GNSS interference suppression method increases the STFT transformation of different window lengths before the frequency domain transformation, selects the appropriate window length by detecting the energy concentration degree after the STFT transformation, the window has adaptability, sets the interference rejection threshold through the statistical characteristics of the transformed data, to reject the interference signal, and finally restores the signal through the inverse Fourier transformation, so as to achieve the ability of adaptive interference suppression.

[0107] The present application determines the window length adaptive to the interference speed of the current interference signal (such as sweep interference) through the STFT calculation of multiple different window function lengths, and then determines the length of the STFT calculation, and then determines the threshold of the post-interference signal in the time-frequency domain by using the variance statistical method, realizes interference rejection, and can improve the anti-interference ability of the satellite navigation receiving terminal variable interference (such as sweep interference); at the same time, the threshold of interference suppression is determined by using the variance statistical method, which can realize adaptive anti-interference without relying on prior information (the prior art needs a large amount of collection and processing to determine how much interference is, and then suppresses, that is, needs prior information); and, without limiting the type of interference, it is suitable for GNSS sweep interference, single-tone interference, narrowband interference and pulse interference.

[0108] It should be understood that, although Figure 1 The steps in the flowchart of the present application are displayed in sequence according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps in the present application 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 sub-steps or stages of other steps.

[0109] As Figure 3As shown, in a specific embodiment, the method of this application is located after the ADC and before the GNSS signal processing in the satellite navigation receiver terminal. The ADC-sampled data is divided into segments (four window lengths are set: 128 points, 256 points, 512 points, and 1024 points) using a short-time Fourier transform to determine the optimal segment length. The sampled data is divided into delayed and non-delayed channels. The data in the delayed channel is delayed by 1 / 2 window length points compared to the data in the non-delayed channel. Short-time Fourier transforms and frequency domain interference removal are performed on both the delayed and non-delayed channels, followed by inverse Fourier transforms. Finally, the data from the two channels are added together to obtain the anti-interference data, which is then sent to the GNSS signal processing module for reception and positioning.

[0110] like Figure 4 The frequency domain diagrams before and after anti-interference are shown below. Figure 5 The time-domain plots before and after anti-interference are shown. It can be seen from the plots that the interference signal was eliminated after the method was applied. The interference signal intensity decreased by about 60dB after the anti-interference, leaving only the background noise signal.

[0111] Figure 6 and Figure 7 The GNSS signal acquisition before anti-interference is shown. It can be seen that without anti-interference, the signal cannot be acquired, and the navigation signal cannot be received normally.

[0112] Figure 8 and Figure 9 The image shows the GNSS signal acquisition after interference suppression using this method. It can be seen that the relevant peak navigation signal can be captured and received normally.

[0113] This application also provides an adaptive GNSS interference suppression device, such as Figure 10 As shown, in one embodiment, it includes: a first module 1001, a second module 1002, a third module 1003, a fourth module 1004, a fifth module 1005, and a sixth module 1006, wherein:

[0114] The first module 1001 is used to acquire the discrete sequence of the GNSS received signal and set multiple windows of different lengths;

[0115] The second module 1002 is used to perform windowing processing and short-time Fourier transform on the discrete sequence according to multiple windows, and obtain the transformation result corresponding to each window.

[0116] The third module 1003 is used to perform energy detection on the frequency domain value of the transformation result of each window, obtain the energy detection result of each window, and determine the number of discrete points of the energy detection result of each window that meet the preset first condition; select all windows whose number of discrete points meets the preset second condition, and take the window with the largest length as the normal window; set the delay window according to the normal window;

[0117] the fourth module 1004 is configured to perform windowing processing and short-time Fourier transform on the discrete sequence according to the normal window and the delay window respectively, to obtain a normal window transform result and a delay window transform result;

[0118] the fifth module 1005 is configured to perform interference elimination on the normal window transform result and the delay window transform result respectively, and perform inverse short-time Fourier transform on the normal window transform result and the delay window transform result respectively, to obtain a time domain signal of a normal window channel and a time domain signal of a delay window channel;

[0119] the sixth module 1006 is configured to superimpose the two time domain signals to output anti-interference data, to implement adaptive interference suppression.

[0120] The specific limitation of the adaptive GNSS interference suppression device can refer to the limitation of the adaptive GNSS interference suppression method in the foregoing, and will not be described herein. Each module in the device can be realized by software, hardware and a combination thereof in whole or in part. Each module 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 operation corresponding to each module.

[0121] In an embodiment, a computer device is provided, which can be a terminal, and an internal structure diagram thereof can be as shown in FIG. 10. Figure 11 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 an external terminal through a network connection. The computer program is executed by the processor to implement an adaptive GNSS 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 a key, trackball or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad or mouse, etc.

[0122] Those skilled in the art can understand that Figure 11 the structure shown in FIG. 10 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. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0123] In one embodiment, a computer device is provided, comprising a memory and a processor, the memory storing a computer program, the processor implementing the steps of the method in the above embodiments when executing the computer program.

[0124] In one embodiment, a computer readable storage medium is provided, storing a computer program, the computer program being executed by a processor to implement the steps of the method in the above embodiments.

[0125] It is understood by a person skilled in the art that all or part of the processes of the above-mentioned embodiments 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. Any reference to memory, storage, database or other medium used in the embodiments provided in the present application 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), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM) and the like.

[0126] The contents not described in detail in the specification are the prior art known to those skilled in the art.

[0127] The technical features of the above embodiments can be combined in any way. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0128] 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 present application. It should be noted that for those skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. An adaptive GNSS interference suppression method, characterized in that, include: Obtain the discrete sequence of the GNSS received signal and set multiple windows of different lengths; Based on multiple windows, the discrete sequence is subjected to windowing processing and short-time Fourier transform respectively, and the transformation result corresponding to each window is obtained; Energy detection is performed on the frequency domain value of the transformation result of each window to obtain the energy detection result of each window, and the number of discrete points of the energy detection result of each window that satisfy the preset first condition is determined. Select all windows whose number of discrete points satisfies the preset second condition, and select the window with the longest length as the normal window; Set a delay window based on the normal window settings; Based on the normal window and the delayed window, the discrete sequence is subjected to windowing processing and short-time Fourier transform respectively to obtain the normal window transform result and the delayed window transform result; Interference removal is performed on the normal window transform results and the delayed window transform results respectively, and inverse short-time Fourier transform is performed on them respectively to obtain the time domain signals of the normal windowed channel and the delayed windowed channel. The two time-domain signals are superimposed to output anti-interference data, thereby achieving adaptive interference suppression. Based on multiple windows, the discrete sequence is subjected to windowing processing and short-time Fourier transform respectively, resulting in the transform results for each window, including: In the formula, This is the result of the window transformation. For the index of the short-time Fourier transform frame, This is the index number of the spectrum obtained after the short-time Fourier transform. These are window function indices, each corresponding one-to-one with a discrete signal index and also one-to-one with a point index within the window. For window length, For discrete time domain signals, The frame shift represents the number of points between adjacent windows. For window functions, It is a natural constant. It is the imaginary unit.

2. The adaptive GNSS interference suppression method according to claim 1, characterized in that, Obtain the discrete sequence of the GNSS received signal, and set multiple windows of different lengths, including: Obtain the discrete sequence of the GNSS received signal, and set the window length to [value missing]. , Take different integer values, The minimum value is , The maximum value is This allows for the creation of multiple windows of varying lengths; among them, To round down, Logarithm to base 2 The sampling rate of the receiver's AD chip. The frequency change rate of the interference signal needs to be suppressed.

3. The adaptive GNSS interference suppression method according to claim 2, characterized in that, The window is a Hamming window, and the window function is: In the formula, For window functions, For window function index, This is the window length.

4. An adaptive GNSS interference suppression method according to any one of claims 1 to 3, characterized in that, The first condition is preset as follows: In the formula, The energy detection results for the window. This represents the frequency domain value of the window's transformation result.

5. An adaptive GNSS interference suppression method according to any one of claims 1 to 3, characterized in that, The second condition is preset as follows: In the formula, The number of discrete points in the window whose energy detection results satisfy the preset first condition. This is the window length.

6. An adaptive GNSS interference suppression method according to any one of claims 1 to 3, characterized in that, Based on the normal window, set a delay window, including: Based on the normal window, set the delay to... , Given the window length, the delay window is obtained.

7. An adaptive GNSS interference suppression method according to any one of claims 1 to 3, characterized in that, Interference removal is performed on the normal window transformation results and the delayed window transformation results respectively, including: in, In the formula, For the spectrum data after interference removal, The data is in the frequency domain after short-time Fourier transform. To eliminate interference thresholds, The mean of the signal. As a weighting factor, This is an estimate of the standard deviation.

8. The adaptive GNSS interference suppression method according to claim 7, characterized in that, Performing the inverse short-time Fourier transform includes: In the formula, For time-domain signals, For window length, This is the index number of the spectrum obtained after the short-time Fourier transform. It is a frequency domain signal. It is a natural constant. The imaginary unit, The window function index corresponds one-to-one with the discrete signal index and also one-to-one with the index of the window point.

9. The adaptive GNSS interference suppression method according to claim 8, characterized in that, The two time-domain signals are superimposed to output anti-interference data, including: In the formula, To prevent data from being interfered with, For normal windowed channel time domain data, For time-domain data of the delay channel, It is half the length of the window.

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