A GNSS receiver positioning method, system, device and medium in a strong interference environment

Abstract

The present application is applicable to the field of satellite navigation technology and provides a GNSS receiver positioning method in a strong interference environment, comprising: monitoring in-band and out-band signals received by the GNSS receiver to determine whether the GNSS receiver is in a strong interference environment; for a GNSS receiver in a strong interference environment, suppressing or eliminating the in-band and out-band signals by an interference suppression method to obtain a first signal; monitoring the in-band and out-band signals or the first signal, and eliminating the interference signal in the in-band and out-band signals or the first signal based on the difference between the strong interference signal and the GNSS satellite signal in the time domain and the frequency domain to obtain a second signal; within each epoch, based on the second signal, using a particle filter algorithm to position the GNSS receiver to obtain trajectory information of the GNSS receiver; using a multi-source data fusion algorithm to fuse the trajectory information and auxiliary navigation information to obtain the position information of the GNSS receiver. The present application can improve the anti-interference capability and positioning effectiveness of the GNSS receiver.

Description

Technical Field

[0001] The present application relates to the field of satellite navigation technology, and in particular to a GNSS receiver positioning method, system, device and medium in a strong interference environment. Background Art

[0002] Currently, the Satellite Navigation System (GNSS) has been widely used in multiple industries, including communications, finance, electricity, telecommunications, and aviation. The system provides users with high-precision positioning, navigation, and timing services, greatly promoting the efficient development of these industries.

[0003] However, satellite navigation signals have inherent radio characteristics such as long transmission distances and low signal power, making them extremely susceptible to various types of intentional or unintentional interference. Strong interference, often with high power and wide coverage, can block the navigation and positioning information received, processed, and output by GNSS receivers, preventing users from receiving downlink navigation signals from GNSS satellites, severely impacting their normal use. Furthermore, existing GNSS receivers also have limitations when facing interference. In particular, in environments with a signal-to-interference ratio (SIR) greater than 20dB, the success rate for capturing, tracking, and positioning navigation satellites falls below 50%, severely impacting the user experience in challenging electromagnetic environments. Furthermore, GNSS receivers also have limited in-band immunity to interference from pulse-type and undesired modulation signals, further limiting their application in complex electromagnetic environments.

[0004] In summary, although satellite navigation systems (GNSS) have been widely used in multiple industries, the inherent radio characteristics of satellite navigation signals make the application of satellite navigation systems extremely susceptible to interference, and existing GNSS receivers also have certain limitations in anti-interference. Summary of the Invention

[0005] The embodiments of the present application provide a GNSS receiver positioning method, system, device and medium in a strong interference environment, which can monitor and eliminate interference signals in a strong interference environment, thereby improving the anti-interference capability and positioning effectiveness of the GNSS receiver.

[0006] In a first aspect, an embodiment of the present application provides a GNSS receiver positioning method in a strong interference environment, comprising:

[0007] monitoring the power levels of in-band and out-band signals received by a GNSS receiver to determine whether the GNSS receiver is in a strong interference environment;

[0008] For a GNSS receiver in a strong interference environment, an interference suppression method is used to suppress or eliminate the in-band and out-band signals to obtain a first signal;

[0009] monitoring the in-band and out-band signals or the first signal, and removing the interference signal from the in-band and out-band signals or the first signal based on the differences between the strong interference signal and the GNSS satellite signal in the time domain and the frequency domain to obtain a second signal;

[0010] In each epoch, based on the second signal, a particle filter algorithm is used to locate the GNSS receiver to obtain trajectory information of the GNSS receiver;

[0011] A multi-source data fusion algorithm is used to fuse the trajectory information and auxiliary navigation information to obtain the position information of the GNSS receiver. The auxiliary navigation information includes inertial navigation motion information, dead reckoning information, communication information or Bluetooth information.

[0012] Furthermore, monitoring the power levels of in-band and out-band signals received by the GNSS receiver to determine whether the GNSS receiver is in a strong interference mode includes:

[0013] collecting in-band and out-band signals in the GNSS receiver during a plurality of epochs, and calculating power levels of the in-band and out-band signals;

[0014] If the power level of the in-band and out-band signals within the preset time is higher than a preset power level, it is determined that the GNSS receiver is in a strong interference environment.

[0015] Furthermore, the in-band and out-band signals include an in-band signal and an out-band signal, the in-band signal is a GNSS satellite signal, and the out-band signal is an interference signal;

[0016] The interference suppression method is to suppress the level of the in-band signal and eliminate the out-of-band signal;

[0017] The adopting of the interference suppression method to suppress or eliminate the in-band and out-band signals to obtain the first signal includes:

[0018] Preprocessing the in-band and out-band signals, and performing frequency analysis on the preprocessed in-band and out-band signals to obtain frequency analysis results;

[0019] Determine the target frequency range of GNSS satellite signals based on GNSS system characteristics;

[0020] Distinguishing an in-band signal from an out-of-band signal in the in-band and out-of-band signals based on the frequency analysis result and the target frequency range;

[0021] If the power level of the in-band signal is higher than the preset power level, suppressing the signal level of the in-band signal so that the power level of the in-band signal is lower than the preset power level;

[0022] The out-of-band signal is removed by using a band-stop filter.

[0023] Furthermore, monitoring the in-band and out-band signals or the first signal includes:

[0024] For a GNSS receiver in a strong interference environment, monitoring a first signal obtained after being processed by the interference suppression method;

[0025] For a GNSS receiver that is not in a strong interference environment, in-band and out-band signals received by the GNSS receiver are monitored.

[0026] Furthermore, the removing of the in-band and out-band signals or the interference signal in the first signal based on the difference between the strong interference signal and the GNSS satellite signal in the time domain and the frequency domain to obtain the second signal includes:

[0027] Converting the in-band signal or the first signal among the in-band and out-band signals to obtain a digital signal;

[0028] In the time domain, performing adaptive threshold filtering on the digital signal to obtain a time domain signal, and performing signal identification on the time domain signal to obtain a first identification result;

[0029] In the frequency domain, performing adaptive threshold filtering on the digital signal to obtain a frequency domain signal, and performing signal identification on the frequency domain signal to obtain a second identification result;

[0030] If the first authentication result matches the second authentication result, determining that the true signal in the first authentication result or the second authentication result is the second signal;

[0031] If the first identification result does not match the second identification result, the real signals in the first identification result and the second identification result are fused through a pre-trained time-frequency domain signal fusion model to obtain a second signal.

[0032] Further, after obtaining the second signal, the method includes:

[0033] Calculate the carrier-to-noise ratio of the second signal, and determine whether the interference signal in the in-band and out-band signals or the first signal is successfully removed by determining whether the carrier-to-noise ratio within a preset time is greater than a preset carrier-to-noise ratio threshold.

[0034] Furthermore, within each epoch, positioning the GNSS receiver using a particle filter algorithm based on the second signal to obtain trajectory information of the GNSS receiver includes:

[0035] In each epoch, based on the second signal, acquiring satellite data of the GNSS receiver, and performing normalization processing on the satellite data to obtain standard data, wherein the satellite data includes pseudo moment, carrier phase, and Doppler data;

[0036] Using a Monte Carlo method, a set of particle data groups is initialized for each epoch, and the particle data groups are used to represent the position state information of the GNSS receiver in each epoch, wherein the position state information includes the position information and velocity information of the GNSS receiver;

[0037] In each epoch, calculating the matching degree between each particle in the particle data set and the standard data to obtain a matching degree list;

[0038] Based on the matching degree list, importance sampling is performed on the particle data group to generate a matching particle group;

[0039] Performing weighted averaging on the position state information of all particles in the matching particle group to obtain the predicted position state information of the GNSS receiver in each epoch;

[0040] The predicted position state information of each epoch is smoothed to obtain the trajectory information of the GNSS receiver.

[0041] In a second aspect, an embodiment of the present application provides a GNSS receiver positioning system in a strong interference environment, comprising:

[0042] Strong interference environment judgment module: used to monitor the power level of the in-band and out-band signals received by the GNSS receiver to determine whether the GNSS receiver is in a strong interference environment;

[0043] A first interference signal detection module is configured to suppress or remove the in-band and out-band signals using an interference suppression method for a GNSS receiver in a strong interference environment to obtain a first signal;

[0044] A second interference signal detection module is configured to monitor the in-band and out-band signals or the first signal, and remove the interference signal from the in-band and out-band signals or the first signal based on the differences between the strong interference signal and the GNSS satellite signal in the time domain and the frequency domain to obtain a second signal;

[0045] A GNSS receiver positioning module is configured to locate the GNSS receiver in each epoch using a particle filter algorithm based on the second signal to obtain trajectory information of the GNSS receiver;

[0046] Navigation information fusion and dead reckoning module: used to use a multi-source data fusion algorithm to fuse the trajectory information and auxiliary navigation information to obtain the position information of the GNSS receiver. The auxiliary navigation information includes inertial navigation motion information, dead reckoning information, communication information or Bluetooth information.

[0047] In a third aspect, an embodiment of the present application provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the GNSS receiver positioning method in a strong interference environment is implemented.

[0048] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, implementing the above-mentioned GNSS receiver positioning method in a strong interference environment.

[0049] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0050] The present application provides a GNSS receiver positioning method in a strong interference environment. In a strong interference environment, the GNSS receiver can adaptively monitor and eliminate interference signals. Through the interference suppression method, the influence of interference signals in the strong interference environment on the GNSS positioning accuracy is effectively reduced. In addition, based on the difference between the strong interference signal and the GNSS satellite signal in the time domain and the frequency domain, the interference signal can be further eliminated, so that the GNSS receiver has the ability to jointly monitor the interference signal in the strong interference environment using multiple parameters such as interference-to-signal ratio, time domain, and frequency domain. In addition, for the positioning of the GNSS receiver, the final position information of the GNSS receiver is determined by fusing and extrapolating the trajectory information and auxiliary navigation information obtained by the particle filter algorithm, making full use of the complementarity between various information, improving the reliability and accuracy of the GNSS receiver positioning, and realizing high-precision positioning of the GNSS receiver in a strong interference environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0052] Figure 1 This is a flowchart of a GNSS receiver positioning method in a strong interference environment provided by one embodiment of the present invention;

[0053] Figure 2 yes Figure 1Another flowchart of a GNSS receiver positioning method in a strong interference environment according to the embodiment shown;

[0054] Figure 3 This is a structural diagram of a GNSS receiver positioning system in a strong interference environment provided by one embodiment of the present invention;

[0055] Figure 4 It is a structural diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0057] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0058] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0059] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0060] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0061] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0062] See also Figure 1 As shown, the present invention is a GNSS receiver positioning method in a strong interference environment, comprising the following steps:

[0063] S100, monitoring the power levels of in-band and out-band signals received by a GNSS receiver to determine whether the GNSS receiver is in a strong interference environment;

[0064] In this embodiment, since when the GNSS receiver is in a strong interference environment, its interference signal will seriously affect the reception quality of the GNSS satellite signal, resulting in inaccurate or deviation in the positioning results. Therefore, when processing the in-band and out-band signals received by the GNSS receiver, it is necessary to first determine whether the GNSS receiver is in a strong interference environment. For GNSS receivers in a strong interference environment, the in-band and out-band signals received by it are first preliminarily suppressed or eliminated.

[0065] In some embodiments, step S100 includes:

[0066] collecting in-band and out-band signals in the GNSS receiver during a plurality of epochs, and calculating power levels of the in-band and out-band signals;

[0067] If the power level of the in-band and out-band signals within the preset time is higher than a preset power level, it is determined that the GNSS receiver is in a strong interference environment.

[0068] In this embodiment, the power levels of the in-band and out-band signals are calculated as follows:

[0069]

[0070] Wherein, x(t) represents the in-band and out-band signals, and T represents the preset time.

[0071] If the power level of the in-band and out-of-band signals obtained by the above formula is greater than a preset power level, it indicates that the GNSS receiver is in a strong interference environment. Since interference intensity exceeding 90 dB in an environment can significantly impact the GNSS receiver, potentially leading to signal quality degradation, increased positioning error, or even signal loss, in one embodiment of the present application, the preset power level is 90 dB and the duration exceeds 100 seconds, i.e., the preset time is 100 seconds. This effectively avoids false alarms caused by brief, transient interference fluctuations and ensures the accuracy and reliability of strong interference environment monitoring.

[0072] S200: For a GNSS receiver in a strong interference environment, suppress or eliminate the in-band and out-band signals using an interference suppression method to obtain a first signal;

[0073] In some embodiments, the in-band and out-band signals include an in-band signal and an out-band signal, the in-band signal is a GNSS satellite signal, and the out-band signal is an interference signal;

[0074] The interference suppression method is to suppress the level of the in-band signal and eliminate the out-of-band signal;

[0075] The step of suppressing or eliminating the in-band and out-band signals by using an interference suppression method to obtain a first signal includes:

[0076] Preprocessing the in-band and out-band signals, and performing frequency analysis on the preprocessed in-band and out-band signals to obtain frequency analysis results;

[0077] Determine the target frequency range of GNSS satellite signals based on GNSS system characteristics;

[0078] Distinguishing an in-band signal from an out-of-band signal in the in-band and out-of-band signals based on the frequency analysis result and the target frequency range;

[0079] If the power level of the in-band signal is higher than the preset power level, suppressing the signal level of the in-band signal so that the power level of the in-band signal is lower than the preset power level;

[0080] The out-of-band signal is removed by using a band-stop filter.

[0081] The interference suppression method in this embodiment processes in-band and out-of-band signals separately. In-band signals are navigation-related information that a GNSS receiver needs to receive, process, and output, namely, GNSS satellite signals. Therefore, when processing in-band and out-of-band signals in a strong interference environment, the in-band signals are suppressed to reduce their power level to below a threshold, resulting in a level-suppressed in-band signal. It is understood that the suppressed in-band signal should still maintain sufficient strength for subsequent processing and resolution. In some embodiments, the in-band signal suppression method utilizes an attenuator, for example. Out-of-band signals typically include various interference signals or noise, which can easily affect GNSS receiver signal reception. Therefore, when processing in-band and out-of-band signals in a strong interference environment, the out-of-band signals are eliminated, for example, by using a band-stop filter to shield the out-of-band signals based on their frequency range. Specifically, by setting the band-stop filter's stopband frequency range to match the frequency range of the out-of-band signal, the input in-band and out-of-band signals are filtered by the band-stop filter to eliminate the out-of-band signals from the in-band and out-of-band signals. It can be understood that the signal obtained after the above suppression and elimination is the first signal.

[0082] In this embodiment, an interference suppression method is used to suppress or eliminate the in-band and out-band signals. It is necessary to distinguish between the in-band and out-band signals in the in-band and out-band signals. Therefore, it is necessary to determine the target frequency range of the GNSS satellite signal based on the characteristics of the GNSS system. Signals that do not fall within the target frequency range are out-of-band signals that need to be eliminated, and signals that fall within the target frequency range are in-band signals that need to be suppressed.

[0083] Specifically, the GNSS receiver receives the radio frequency signal from the satellite, i.e., the above-mentioned in-band and out-of-band signals, and performs pre-processing operations such as down-conversion, amplification, and filtering on the received radio frequency signal. It can be understood that down-conversion converts the radio frequency signal into an intermediate frequency signal, and filtering can remove some out-of-band interference and noise. The pre-processed signal is subjected to frequency analysis, such as using methods such as fast Fourier transform. It can be understood that the frequency analysis results can reveal the intensity or power distribution of different frequency components in the signal, and determine the target frequency range of the in-band signal based on the characteristics of the GNSS system. In the frequency analysis results, the part that matches the target frequency range is identified, i.e., the in-band signal. The part of the frequency analysis result that does not belong to the target frequency range is the out-of-band signal, which corresponds to the in-band signal.

[0084] S300: Monitor the in-band and out-band signals or the first signal, and remove the interference signal from the in-band and out-band signals or the first signal based on the differences between the strong interference signal and the GNSS satellite signal in the time domain and the frequency domain to obtain a second signal;

[0085] In this embodiment, based on the differences between the strong interference signal and the GNSS satellite signal in the time domain and frequency domain, the interference signal in the in-band and out-band signals or the first signal can be further eliminated. Through steps S100 to S300, the GNSS receiver is enabled to have the ability to jointly monitor the interference signal using multiple parameters such as interference-to-signal ratio, time domain, and frequency domain in a strong interference environment.

[0086] In some embodiments, monitoring the in-band and out-of-band signals or the first signal includes:

[0087] For a GNSS receiver in a strong interference environment, monitoring a first signal obtained after being processed by the interference suppression method;

[0088] For a GNSS receiver that is not in a strong interference environment, in-band and out-band signals received by the GNSS receiver are monitored.

[0089] In this embodiment, step S100 can be used to determine whether the GNSS receiver is in a strong interference environment, and step S200 suppresses or eliminates the in-band and out-band signals in the strong interference environment to generate a first signal. It can be understood that when the in-band signal is processed through the above steps S100 and S200, only the signal whose power level in the in-band and out-band signals exceeds the preset power level is processed. Therefore, the present application further processes the in-band and out-band signals of the GNSS receiver through step S300 to eliminate the interference signal whose power level in the in-band and out-band signals or the first signal is lower than the preset power level. It can be understood that for a GNSS receiver in a strong interference environment, its in-band and out-band signals are subjected to strong interference signal processing in step S200 to obtain the first signal, and the first signal is used in the subsequent interference signal monitoring process. For a GNSS receiver not in a strong interference environment, its in-band and out-band signals are subjected to interference signal processing in step S300, thereby improving the anti-interference capability of the GNSS receiver.

[0090] In some embodiments, the removing of the in-band and out-band signals or the interference signal in the first signal based on the difference between the strong interference signal and the GNSS satellite signal in the time domain and the frequency domain to obtain the second signal includes:

[0091] Converting the in-band signal or the first signal among the in-band and out-band signals to obtain a digital signal;

[0092] In the time domain, performing adaptive threshold filtering on the digital signal to obtain a time domain signal, and performing signal identification on the time domain signal to obtain a first identification result;

[0093] In the frequency domain, performing adaptive threshold filtering on the digital signal to obtain a frequency domain signal, and performing signal identification on the frequency domain signal to obtain a second identification result;

[0094] If the first authentication result matches the second authentication result, determining that the true signal in the first authentication result or the second authentication result is the second signal;

[0095] If the first identification result does not match the second identification result, the real signals in the first identification result and the second identification result are fused through a pre-trained time-frequency domain signal fusion model to obtain a second signal.

[0096] In this embodiment, when processing the in-band signal or the first signal, the in-band signal or the first signal in the in-band and out-band signals needs to be converted into a digital signal. The digital signal also has the advantages of strong anti-interference ability and long transmission distance. It can also be processed by a computer with efficient algorithms, such as Fourier transform and filtering, to achieve signal identification and extraction, thereby improving the efficiency of signal processing.

[0097] In this embodiment, for in-band and out-band signals generated by a GNSS receiver that is not in a strong interference environment, it is necessary to distinguish the in-band and out-band signals according to the method of distinguishing the in-band and out-band signals in step S200. The in-band signals are subjected to interference elimination in step S300, while the out-band signals are eliminated by a band-stop filter. The specific process is as described in the above step S200 and will not be repeated here.

[0098] Since the interference signal and the GNSS satellite signal have significant differences in the time domain and frequency domain, such as the waveform, frequency component, phase, etc. of the signal, in this embodiment, the in-band signal or the first signal in the in-band and out-band signals are analyzed in the time domain and frequency domain respectively to identify the corresponding interference signal and eliminate the interference signal.

[0099] In this embodiment, adaptive threshold filtering is performed on a digital signal in the time domain or frequency domain to obtain a time domain signal or a frequency domain signal, and signal identification is performed in the time domain or frequency domain, respectively. Specifically, a time domain threshold is adaptively determined based on the characteristics of the digital signal, wherein the selection of the time domain threshold takes into account characteristics such as the signal's amplitude and frequency. The digital signal is filtered based on the time domain threshold to remove portions of the digital signal that are less than the time domain threshold to obtain a time domain signal. Time-frequency analysis methods such as short-time Fourier transform are used to extract the time domain features of the time domain signal. For signals in the frequency domain, fast Fourier transform is used to convert the digital signal from the time domain to the frequency domain, thereby analyzing the characteristics of the data signal in the frequency domain. Specifically, a frequency domain threshold is adaptively determined based on the characteristics of the digital signal in the frequency domain. An adaptive threshold filtering algorithm is used to filter the digital signal in the frequency domain to remove noise and interference components to obtain a frequency domain signal. Feature extraction is performed on the frequency domain signal to obtain frequency domain features, such as frequency, amplitude, and phase.

[0100] In this embodiment, a signal identification model is constructed using a machine learning algorithm such as a support vector machine. The time domain features or frequency domain features are input into the signal identification model to identify the signal type of the time domain signal or frequency domain signal, thereby identifying interference signals in the corresponding time domain signal or frequency domain signal. The signal identification model compares key parameters such as the amplitude, frequency, and phase of the detected signal with preset GNSS satellite signal parameters, identifying signals with parameter differences outside the allowable range as interference signals and signals with parameter differences within the allowable range as true signals.

[0101] For the signal identification results in the time domain and frequency domain, if the identification results in the two domains match, the true signal in the first identification result or the second identification result is determined as the second signal. If there are differences or uncertainties in the identification results in the two domains, the true signals in the first identification result and the second identification result are fused through the time-frequency domain signal fusion model to obtain the second signal.

[0102] For the time-frequency domain signal fusion model, the time domain features of the time domain signal and the frequency domain features of the frequency domain signal are extracted, and the support vector machine algorithm is used to fuse the above time domain features and frequency domain features to establish a time-frequency domain signal fusion model.

[0103] In some embodiments, after obtaining the second signal, the method includes:

[0104] Calculate the carrier-to-noise ratio of the second signal, and determine whether the interference signal in the in-band and out-band signals or the first signal is successfully removed by determining whether the carrier-to-noise ratio within a preset time is greater than a preset carrier-to-noise ratio threshold.

[0105] In this embodiment, the carrier-to-noise ratio of the second signal is calculated to determine whether the signal received by the GNSS receiver has successfully suppressed or eliminated the corresponding interference signal. In a preferred embodiment, if the carrier-to-noise ratio is continuously above 30 dB and this carrier-to-noise ratio state persists for more than 100 seconds, it indicates that the signal quality and stability received by the GNSS receiver are good.

[0106] S400: In each epoch, based on the second signal, using a particle filter algorithm to locate the GNSS receiver to obtain trajectory information of the GNSS receiver;

[0107] In some embodiments, step S400 includes:

[0108] In each epoch, based on the second signal, acquiring satellite data of the GNSS receiver, and performing normalization processing on the satellite data to obtain standard data, wherein the satellite data includes pseudo moment, carrier phase, and Doppler data;

[0109] Using a Monte Carlo method, a set of particle data groups is initialized for each epoch, and the particle data groups are used to represent the position state information of the GNSS receiver in each epoch, wherein the position state information includes the position information and velocity information of the GNSS receiver;

[0110] In each epoch, calculating the matching degree between each particle in the particle data set and the standard data to obtain a matching degree list;

[0111] Based on the matching degree list, importance sampling is performed on the particle data group to generate a matching particle group;

[0112] Performing weighted averaging on the position state information of all particles in the matching particle group to obtain the predicted position state information of the GNSS receiver in each epoch;

[0113] The predicted position state information of each epoch is smoothed to obtain the trajectory information of the GNSS receiver.

[0114] In this embodiment, based on the satellite data generated when the GNSS receiver receives the second signal obtained by suppressing or eliminating the interference signal, a particle filter algorithm is used to locate the GNSS receiver to obtain corresponding trajectory information.

[0115] In this embodiment, the satellite data generated in each epoch is processed separately, that is, the satellite data is normalized to obtain standard data, and the standard data is matched with a particle group generated using a Monte Carlo method to represent the position state information of the GNSS receiver, ultimately obtaining the predicted position state information of the GNSS receiver. Specifically, the pseudo-moments, carrier phase, and Doppler data in the satellite data are preprocessed to remove outliers and invalid data. The preprocessed satellite data is normalized according to a preset normalization algorithm, and the data is mapped to the interval [0, 1] to obtain standardized satellite data, that is, standard data. A Monte Carlo method is used to initialize a set of particle data representing the position state information of a GNSS receiver. Each particle in the particle data set contains a three-dimensional position coordinate and a three-dimensional velocity component. The three-dimensional position coordinates and three-dimensional velocity components of multiple particles are weighted averaged to form a data set representing the position and velocity information of the GNSS receiver. For each particle, the degree of match between its position state information and the aforementioned standard data is calculated to generate a matching list. In this matching list, the higher the matching degree, the closer the particle is to the true GNSS receiver position state information. Therefore, based on the matching degree of each particle in the matching list, importance sampling is performed on the particles, and particles with low matching degrees are eliminated. New particles are generated based on the distribution of the remaining particles to ensure that the number of particles in the particle data set remains unchanged. Finally, a matching particle set is generated. The position state information of all particles in the matching particle set is weighted averaged to obtain the predicted position state information of the GNSS receiver. The predicted position state information generated in each epoch is smoothed to obtain the trajectory information of the GNSS receiver. The GNSS receiver is positioned using this trajectory information.

[0116] S500: Using a multi-source data fusion algorithm, the trajectory information and the auxiliary navigation information are fused to obtain the position information of the GNSS receiver, where the auxiliary navigation information includes inertial navigation motion information, dead reckoning information, communication information, or Bluetooth information.

[0117] In some embodiments, the satellite data generated by the GNSS receiver when receiving the second signal may be contaminated by co-channel interference signals, such as malicious interference, multipath interference, and other electromagnetic interference. When the GNSS receiver encounters co-channel interference when receiving the second signal, its positioning results will often be biased or erroneous. This may pose serious safety risks and efficiency losses for applications that rely on high-precision navigation and positioning, such as aviation navigation, autonomous driving, and precision measurement. Therefore, in this application, the trajectory information obtained in step S400 is fused with the navigation data generated by the navigation system or sensor used in the navigation and positioning process to improve the effectiveness of the GNSS receiver's positioning.

[0118] In this embodiment, the navigation data generated by the auxiliary navigation system or sensor during the use of the GNSS receiver is used as auxiliary navigation information, and the auxiliary navigation information is integrated and calculated with the above-mentioned trajectory information to determine the final position information of the GNSS receiver, thereby fully utilizing the complementarity between various information to improve the reliability and accuracy of the GNSS receiver positioning, thereby achieving high-precision positioning of the GNSS receiver in a strong interference environment.

[0119] In some embodiments, the auxiliary navigation information includes inertial navigation motion information, dead reckoning information, communication information or Bluetooth information, wherein the inertial navigation motion information is the motion information about the GNSS receiver carrier such as the vehicle provided by the inertial navigation system using sensors such as accelerometers and gyroscopes; the dead reckoning information is the subsequent position information obtained by integrating the acceleration and turning rate based on the known initial position and velocity; the communication information is the position information provided by the mobile communication network; and the Bluetooth information is the data obtained by Bluetooth and UWB (ultra-wideband) technology that can be used for precise positioning within a short distance.

[0120] In this embodiment, the GNSS receiver's operating status and environmental characteristics are used to determine the auxiliary navigation information available to the receiver. For example, for aviation navigation, inertial navigation motion information, dead reckoning information, communication information, and Bluetooth information can be obtained; for autonomous vehicles, inertial navigation motion information, dead reckoning information, communication information, and Bluetooth information can be obtained. A preprocessing method is used for the different types of auxiliary navigation information available from the GNSS receiver to remove significant outliers and gross errors, preparing for subsequent data fusion. Based on the receiver's operating status and environmental characteristics, a Kalman filter or particle filter algorithm is adaptively selected to establish a multi-source data fusion model. The filter parameters are dynamically adjusted by comprehensively considering the characteristics and weights of each type of auxiliary navigation information.

[0121] Specifically, during the data fusion process, trajectory information and inertial navigation (INS) information are deeply coupled, leveraging the high-frequency characteristics of INS to compensate for positioning gaps when satellite data is obstructed, thereby improving positioning continuity. Simultaneously, the long-term stability of GNSS is leveraged to correct for accumulated INS errors, enhancing positioning accuracy. To address the vulnerability of satellite data to obstruction and interference in complex environments, the GNSS receiver fuses dead reckoning information and uses the receiver's historical trajectory and velocity to estimate the current position, supplementing and correcting GNSS positioning and enhancing positioning reliability. If a communication network or Bluetooth is available, differential correction data from nearby reference stations or other users is obtained, further improving GNSS positioning accuracy through differential positioning techniques. Communication links are then used to enable data transmission and sharing of positioning results. At each stage of data fusion, adaptive Kalman filtering or particle filtering algorithms are employed to dynamically adjust filter parameters and weights based on the distribution characteristics of positioning errors and prior information, ensuring more stable and reliable positioning results. After multi-source data fusion and filtering, the GNSS receiver can output high-precision and consistent positioning results. Through appropriate data formats and interface specifications, it facilitates integration and use with other systems and applications, meeting the business needs of high-precision positioning.

[0122] See also Figure 3 As shown, the present invention also provides a GNSS receiver positioning system in a strong interference environment, the system comprising:

[0123] Strong interference environment determination module 301: used to monitor the power level of the in-band and out-band signals received by the GNSS receiver, and determine whether the GNSS receiver is in a strong interference environment;

[0124] The first interference signal detection module 302 is configured to suppress or remove the in-band and out-band signals using an interference suppression method for a GNSS receiver in a strong interference environment to obtain a first signal;

[0125] A second interference signal detection module 303 is configured to monitor the in-band and out-band signals or the first signal, and remove the interference signal from the in-band and out-band signals or the first signal based on the differences between the strong interference signal and the GNSS satellite signal in the time domain and the frequency domain to obtain a second signal;

[0126] The GNSS receiver positioning module 304 is configured to position the GNSS receiver based on the second signal using a particle filter algorithm in each epoch to obtain trajectory information of the GNSS receiver.

[0127] The navigation information fusion and dead reckoning module 305 is used to use a multi-source data fusion algorithm to fuse the trajectory information and the auxiliary navigation information to obtain the position information of the GNSS receiver. The auxiliary navigation information includes inertial navigation motion information, dead reckoning information, communication information or Bluetooth information.

[0128] In this application, the above-mentioned GNSS receiver positioning system in a strong interference environment is applied to the RF front-end of the GNSS receiver, which can monitor and eliminate the strong interference signals of the RF front-end, and the GNSS receiver positioning system in a strong interference environment is encapsulated as a software system and applied to the GNSS receiver. There is no need to modify the hardware of the GNSS receivers that exist on a large scale in the market. Only the above-mentioned software system needs to be updated to realize the monitoring and elimination of strong interference signals, which can effectively improve the availability of the receiver.

[0129] In this embodiment, Figure 2 As shown, the strong interference environment judgment module 301 determines whether the environment in which the GNSS receiver is located is a strong interference environment. If the environment in which the GNSS receiver is located is a strong interference environment, the first interference signal detection module 302 monitors and processes the corresponding in-band and out-band signals. If the environment in which the GNSS receiver is located is not a strong interference environment, the second interference signal detection module 303 monitors and processes the corresponding in-band and out-band signals. At the same time, the second interference signal detection module 303 can further monitor and process the first signal generated after processing by the first interference signal detection module 302, thereby improving the anti-interference capability of the GNSS receiver. Finally, the second signal generated after processing by the second interference signal detection module 303 is used for positioning solution of the GNSS receiver in the GNSS receiver positioning module 304. At the same time, the navigation information fusion and inference module 305 is introduced to fuse and infer the trajectory information generated in the GNSS receiver positioning module 304 with the auxiliary navigation information, thereby improving the positioning effectiveness of the GNSS receiver.

[0130] In this embodiment, the second interference signal detection module 303 includes a time domain detection submodule and a frequency domain detection submodule, which are used to monitor and identify the in-band and out-band signals or the first signal in the time domain and the frequency domain respectively.

[0131] It is understandable that if Figure 1 The contents of the embodiment of the GNSS receiver positioning method in a strong interference environment shown in FIG. 1 are all applicable to the embodiment of the GNSS receiver positioning system in a strong interference environment. The functions specifically implemented by the embodiment of the GNSS receiver positioning system in a strong interference environment are the same as those in FIG. Figure 1 The embodiment of the GNSS receiver positioning method in a strong interference environment shown in FIG. 1 is the same as that shown in FIG. 1 , and the beneficial effects achieved are the same as those of FIG. Figure 1 The beneficial effects achieved by the embodiment of the GNSS receiver positioning method in a strong interference environment are also the same.

[0132] It should be noted that the information interaction, execution process and other contents between the above-mentioned systems are based on the same concept as the embodiment of the method of the present invention. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0133] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0134] See also Figure 4 As shown, an embodiment of the present invention further provides a computer device 4, comprising: a memory 402 and a processor 401 and a computer program 403 stored on the memory 402. When the computer program 403 is executed on the processor 401, a GNSS receiver positioning method in a strong interference environment as described in any one of the above methods is implemented.

[0135] The computer device 4 can be a desktop computer, a notebook computer, a palmtop computer, a cloud server or other computing devices. The computer device 4 can include, but is not limited to, a processor 401 and a memory 402. Those skilled in the art will understand that Figure 4 This is merely an example of the computer device 4 and does not constitute a limitation on the computer device 4 . The computer device 4 may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device 4 may also include input and output devices, network access devices, etc.

[0136] The processor 401 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor may be a microprocessor or any conventional processor.

[0137] In some embodiments, the memory 402 may be an internal storage unit of the computer device 4, such as a hard disk or memory of the computer device 4. In other embodiments, the memory 402 may also be an external storage device of the computer device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the computer device 4. Furthermore, the memory 402 may include both an internal storage unit of the computer device 4 and an external storage device. The memory 402 is used to store an operating system, application programs, a boot loader, data, and other programs, such as the program code of the computer program. The memory 402 may also be used to temporarily store data that has been output or is about to be output.

[0138] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for positioning a GNSS receiver in a strong interference environment as described in any one of the above methods is implemented.

[0139] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process in the above-mentioned embodiment method by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device capable of carrying computer program code to a camera / computer device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electric carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard drive, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals or telecommunication signals.

[0140] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A GNSS receiver positioning method in a strong interference environment, characterized in that: include: monitoring the power levels of in-band and out-band signals received by a GNSS receiver to determine whether the GNSS receiver is in a strong interference environment; For a GNSS receiver in a strong interference environment, an interference suppression method is used to suppress or eliminate the in-band and out-band signals to obtain a first signal; monitoring the in-band and out-band signals or the first signal, and removing the interference signal from the in-band and out-band signals or the first signal based on the differences between the strong interference signal and the GNSS satellite signal in the time domain and the frequency domain to obtain a second signal; In each epoch, based on the second signal, a particle filter algorithm is used to locate the GNSS receiver to obtain trajectory information of the GNSS receiver; A multi-source data fusion algorithm is used to fuse the trajectory information and auxiliary navigation information to obtain the position information of the GNSS receiver. The auxiliary navigation information includes inertial navigation motion information, dead reckoning information, communication information or Bluetooth information.

2. The method according to claim 1, wherein The monitoring of the power levels of the in-band and out-band signals received by the GNSS receiver to determine whether the GNSS receiver is in a strong interference mode includes: collecting in-band and out-band signals in the GNSS receiver during a plurality of epochs, and calculating power levels of the in-band and out-band signals; If the power level of the in-band and out-band signals within the preset time is higher than a preset power level, it is determined that the GNSS receiver is in a strong interference environment.

3. The method according to claim 1, wherein The in-band and out-band signals include in-band signals and out-band signals, the in-band signals are GNSS satellite signals, and the out-band signals are interference signals; The interference suppression method is to suppress the level of the in-band signal and eliminate the out-of-band signal; The adopting of the interference suppression method to suppress or eliminate the in-band and out-band signals to obtain the first signal includes: Preprocessing the in-band and out-band signals, and performing frequency analysis on the preprocessed in-band and out-band signals to obtain frequency analysis results; Determine the target frequency range of GNSS satellite signals based on GNSS system characteristics; Distinguishing an in-band signal from an out-of-band signal in the in-band and out-of-band signals based on the frequency analysis result and the target frequency range; If the power level of the in-band signal is higher than the preset power level, suppressing the signal level of the in-band signal so that the power level of the in-band signal is lower than the preset power level; The out-of-band signal is removed by using a band-stop filter.

4. The method according to claim 1, wherein The monitoring of the in-band and out-band signals or the first signal includes: For a GNSS receiver in a strong interference environment, monitoring a first signal obtained after being processed by the interference suppression method; For a GNSS receiver that is not in a strong interference environment, in-band and out-band signals received by the GNSS receiver are monitored.

5. The method according to claim 1, wherein The step of removing the in-band and out-band signals or the interference signal in the first signal based on the differences between the strong interference signal and the GNSS satellite signal in the time domain and the frequency domain to obtain the second signal includes: Converting the in-band signal or the first signal among the in-band and out-band signals to obtain a digital signal; In the time domain, performing adaptive threshold filtering on the digital signal to obtain a time domain signal, and performing signal identification on the time domain signal to obtain a first identification result; In the frequency domain, performing adaptive threshold filtering on the digital signal to obtain a frequency domain signal, and performing signal identification on the frequency domain signal to obtain a second identification result; If the first authentication result matches the second authentication result, determining that the true signal in the first authentication result or the second authentication result is the second signal; If the first identification result does not match the second identification result, the real signals in the first identification result and the second identification result are fused through a pre-trained time-frequency domain signal fusion model to obtain a second signal.

6. The method according to claim 5, wherein After obtaining the second signal, the method includes: Calculate the carrier-to-noise ratio of the second signal, and determine whether the interference signal in the in-band and out-band signals or the first signal is successfully removed by determining whether the carrier-to-noise ratio within a preset time is greater than a preset carrier-to-noise ratio threshold.

7. The method according to claim 1, wherein The method of positioning the GNSS receiver based on the second signal using a particle filter algorithm in each epoch to obtain trajectory information of the GNSS receiver includes: In each epoch, based on the second signal, acquiring satellite data of the GNSS receiver, and performing normalization processing on the satellite data to obtain standard data, wherein the satellite data includes pseudo moment, carrier phase, and Doppler data; Using a Monte Carlo method, a set of particle data groups is initialized for each epoch, and the particle data groups are used to represent the position state information of the GNSS receiver in each epoch, wherein the position state information includes the position information and velocity information of the GNSS receiver; In each epoch, calculating the matching degree between each particle in the particle data set and the standard data to obtain a matching degree list; Based on the matching degree list, importance sampling is performed on the particle data group to generate a matching particle group; Performing weighted averaging on the position state information of all particles in the matching particle group to obtain the predicted position state information of the GNSS receiver in each epoch; The predicted position state information of each epoch is smoothed to obtain the trajectory information of the GNSS receiver.

8. A GNSS receiver positioning system in a strong interference environment, characterized in that: include: Strong interference environment judgment module: used to monitor the power level of the in-band and out-band signals received by the GNSS receiver to determine whether the GNSS receiver is in a strong interference environment; A first interference signal detection module is configured to suppress or remove the in-band and out-band signals using an interference suppression method for a GNSS receiver in a strong interference environment to obtain a first signal; A second interference signal detection module is configured to monitor the in-band and out-band signals or the first signal, and remove the interference signal from the in-band and out-band signals or the first signal based on the differences between the strong interference signal and the GNSS satellite signal in the time domain and the frequency domain to obtain a second signal; A GNSS receiver positioning module is configured to locate the GNSS receiver in each epoch using a particle filter algorithm based on the second signal to obtain trajectory information of the GNSS receiver; Navigation information fusion and dead reckoning module: used to use a multi-source data fusion algorithm to fuse the trajectory information and auxiliary navigation information to obtain the position information of the GNSS receiver. The auxiliary navigation information includes inertial navigation motion information, dead reckoning information, communication information or Bluetooth information.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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