A high-speed rail antenna positioning method and system with anti-interference

Abstract

The application discloses a high-speed rail antenna positioning method and system with anti-interference, and the method comprises the following steps: an anti-interference antenna positioning system is composed of a vehicle-mounted antenna and a train nearby antenna; the vehicle-mounted antenna and the train nearby antenna construct an antenna set, a self-diagnosis signal detection algorithm is designed, and a first-level effective antenna set is obtained; a local area anti-interference positioning algorithm is designed for the first-level effective antenna set, and a second-level effective antenna set is obtained; whether the train is near a tunnel is judged by using the train nearby antenna in the second-level effective antenna set, and the train position is calculated by the vehicle-mounted antenna in the second-level effective antenna set; and the train position and the train nearby antenna position are output. The scheme realizes the quick elimination of problem antennas by constructing a cooperative antenna set through the vehicle-mounted antenna and the trackside antenna, and the anti-interference capability of the high-speed rail antenna is further improved through the joint operation of multiple variables such as the carrier-to-noise ratio, the train speed and the satellite signal loss rate, so that the positioning accuracy is improved.

Description

Technical Field

[0001] This invention belongs to the field of high-speed rail antenna positioning technology, and particularly relates to a high-speed rail antenna positioning method and system with anti-interference capabilities. Background Technology

[0002] High-speed railways have formed a networked, high-density, and high-speed operation pattern, placing stringent requirements on the continuity, reliability, and anti-interference capabilities of train operation control. Current mainstream train positioning relies on a combination of satellite navigation, inertial navigation, and track circuits. Satellite signals are susceptible to electromagnetic interference, multipath reflection, and attenuation due to obstruction, especially in mountainous areas, tunnel complexes, elevated sections, and densely populated station areas, where interference sources are complex and diverse. This leads to a sharp drop in the signal-to-noise ratio of onboard antennas, abnormal pseudorange and carrier phase observations, and positioning jumps, drifts, or even loss of lock. Traditional positioning systems often use single antennas or simple redundant configurations, lacking antenna-level self-diagnosis and anomaly removal mechanisms. Faulty antennas can easily introduce systemic biases. Furthermore, existing methods do not implement hierarchical management of antenna arrays, making it difficult to quickly isolate interference and faults at the front end. This results in a heavy burden on subsequent fusion calculations, insufficient robustness, and weak continuous positioning assurance capabilities in complex scenarios.

[0003] The numerous tunnels, cuttings, bridges, and station buildings along high-speed rail lines cause significant fluctuations in satellite signals, making traditional positioning prone to gaps and delays at tunnel entrances and transition sections. Current technologies lack interference coefficient discrimination and multi-antenna compensation strategies for scenarios near tunnels, and continue to use fixed calculation modes even when signals deteriorate, easily leading to positioning failures. Furthermore, the positioning output lacks joint anchoring of antenna health status and location, making it difficult for maintenance personnel to quickly locate antenna faults, impacting system availability and maintenance efficiency. Therefore, a new anti-interference antenna positioning method is urgently needed to support highly reliable and accurate positioning for high-speed rail. Summary of the Invention

[0004] This invention provides a high-speed rail antenna positioning method and system with anti-interference capabilities to solve the technical problems of poor anti-interference capability of positioning signals received by high-speed rail antennas, single judgment signal, and lack of multiple interference detection.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: On one hand, the present invention provides a high-speed rail antenna positioning method with anti-interference capabilities, the high-speed rail antenna positioning method with anti-interference capabilities comprising: S1: The train speed, train inertial navigation position and satellite signals are received through the on-board antenna located on the train body. The antenna near the train is located near the train track and receives satellite signals. S2: Construct an antenna set by combining the vehicle-mounted antenna and antennas near the train. Utilize the satellite signals received by the antenna set to design a self-diagnostic signal detection algorithm, calculate the self-diagnostic optimization coefficient, initialize the optimization threshold, and based on the self-diagnostic optimization coefficient and the optimization threshold, eliminate antennas with self-diagnostic problems to obtain a first-level effective antenna set. S3: For the first-level effective antenna set, design a local area anti-interference positioning algorithm. Calculate the train's onboard characteristics based on the train speed, train inertial navigation position, and satellite signals received by the onboard antennas in the first-level effective antenna set. Calculate the train's proximity characteristics based on the satellite signals received by the antennas near the train in the first-level effective antenna set. Calculate the consistency characteristic coefficient using the train's onboard characteristics and the train's proximity characteristics, and then filter the consistency characteristic coefficients to obtain the second-level effective antenna set. S4: Calculate the satellite interference coefficient using the train-near antennas in the secondary effective antenna set. Determine whether the train is near the tunnel based on the satellite interference coefficient. When the train is near the tunnel, design a multi-antenna compensation algorithm to calculate the train's position using both the train-near antennas in the secondary effective antenna set and the onboard antennas. When the train is not near the tunnel, calculate the train's position using the onboard antennas in the secondary effective antenna set. S5: Outputs the train position and the position of the antennas near the train.

[0006] Optionally, step S1 includes: The onboard antennas are located on the train body and receive train speed v, train inertial navigation position, and satellite signals. Each train car carries one onboard antenna, located at the geometric center of the car's roof. The number of onboard antennas is [number missing]. , This refers to the vehicle-mounted antennas; the number of vehicle-mounted antennas is the same as the number of train carriages. The antennas near the train are located beside the train tracks and receive satellite signals. The number of these antennas near the train is... , This indicates an antenna near the train.

[0007] Optionally, step S2 includes: An antenna set Q is constructed by combining the vehicle-mounted antenna and antennas near the train. The antenna set contains ( ) + ) antennas, of which , This represents the i-th vehicle-mounted antenna. Indicates the first One vehicle-mounted antenna, This represents the antenna near the j-th train. Indicates the first There are several antennas near the train, where i represents the serial number of the onboard antenna and j represents the serial number of the antenna near the train. Using satellite signals received by antennas within an antenna array, a self-diagnostic signal detection algorithm is designed, and the self-diagnostic optimization coefficients are calculated. The specific steps are as follows: (1) Obtain the train speed from the satellite signal of the i-th on-board antenna. Obtain the train speed from the satellite signal of the antenna near the j-th train. We obtain the set of train speeds V, where Calculate the maximum value in V. Calculate the minimum value in V. , This indicates the calculation of the maximum value. This indicates the calculation of the minimum value; (2) Calculate the speed optimization coefficient of the i-th vehicle-mounted antenna The specific calculation formula is as follows: ; in, Indicates the first Train speed in satellite signals from a single vehicle-mounted antenna. Indicates the first Train speed in satellite signals from antennas near the train Calculate the speed optimization coefficient of the antenna near the j-th train. The specific calculation formula is as follows: ; (3) Obtain the carrier-to-noise ratio in the satellite signal of the i-th vehicle-mounted antenna. Obtain the carrier-to-noise ratio in the satellite signal from the antenna near the j-th train. Calculate the carrier-to-noise ratio optimization coefficient for the i-th vehicle-mounted antenna. The specific calculation formula is as follows: ; in, Indicates the first The carrier-to-noise ratio of satellite signals from a vehicle-mounted antenna. Indicates the first Carrier-to-noise ratio in satellite signals from antennas near a train; Calculate the carrier-to-noise ratio optimization coefficients for the antenna near the j-th train. The specific calculation formula is as follows: ; (4) Calculate the self-diagnosis optimization coefficient from the speed optimization coefficient and the carrier-to-noise ratio optimization coefficient. The self-diagnosis optimization coefficient of the i-th vehicle-mounted antenna is: The specific calculation formula is as follows: ; The self-diagnostic optimization coefficient of the antenna near the j-th train is: The specific calculation formula is as follows: ; in, and This represents the normalization adjustment coefficient; Initialize the optimization threshold. If the self-diagnosis optimization coefficient of the i-th vehicle-mounted antenna or the self-diagnosis optimization coefficient of the j-th train-near antenna is greater than or equal to the optimization threshold, then the antenna is an antenna with a problem. If the self-diagnosis optimization coefficient of the i-th vehicle-mounted antenna or the self-diagnosis optimization coefficient of the j-th train-near antenna is less than the optimization threshold, then the antenna is an antenna without a problem. Remove the antennas with self-diagnosis problems to obtain the first-level effective antenna set.

[0008] Optionally, step S3 includes: In the set of first-order effective antennas, there are a total of One vehicle-mounted antenna, Antennas near the train; For a set of first-level effective antennas, a local area anti-interference localization algorithm is designed. The algorithm calculates the train's on-board characteristics from the on-board antennas in the first-level effective antenna set, and calculates the train's proximity characteristics from the antennas near the train in the first-level effective antenna set. The consistency characteristic coefficient is then calculated using both the on-board and proximity characteristics. The specific steps are as follows: (1) Calculate the train's onboard characteristics from the onboard antennas in the first-level effective antenna set, and the train's onboard characteristics of the i-th onboard antenna. The specific calculation formula is as follows: ; in, This indicates the number of antennas selected around the train's onboard antenna. This represents the x-axis coordinate of the i-th vehicle-mounted antenna. This represents the y-coordinate of the i-th vehicle-mounted antenna. This represents the z-axis coordinate of the i-th vehicle-mounted antenna. This indicates the relationship between the i-th vehicle-mounted antenna and its surroundings. The average x-axis coordinate of each vehicle-mounted antenna This indicates the relationship between the i-th vehicle-mounted antenna and its surroundings. The average y-axis coordinate of each vehicle-mounted antenna This indicates the relationship between the i-th vehicle-mounted antenna and its surroundings. The average z-axis coordinate of each vehicle-mounted antenna; (2) Calculate the train proximity characteristics from the train proximity antennas in the first-order effective antenna set, and calculate the train proximity characteristics of the j-th train proximity antenna. The specific calculation formula is as follows: ; in, This indicates the number of antennas selected around the antenna near the train. This represents the x-axis coordinate of the antenna near the i-th train. Let represent the y-axis coordinate of the antenna near the i-th train. This represents the z-axis coordinate of the antenna near the i-th train. This indicates the relationship between the antenna near the i-th train and its surroundings. The average x-axis coordinate of antennas near each train. This indicates the relationship between the antenna near the i-th train and its surroundings. The average y-axis coordinate of antennas near each train. This indicates the relationship between the antenna near the i-th train and its surroundings. The mean z-axis coordinate of antennas near each train; (3) Calculate the consistency characteristic coefficient using train onboard characteristics and train proximity characteristics. Calculate the maximum value of all vehicle-mounted antennas on the x-axis. The maximum value of the y-axis The maximum value of the z-axis minimum value of the x-axis minimum value of the y-axis minimum value of the z-axis ; Calculate the maximum value of all antennas near trains on the x-axis. The maximum value of the y-axis The maximum value of the z-axis minimum value of the x-axis minimum value of the y-axis minimum value of the z-axis ; The consistency characteristic coefficient is calculated using train-mounted features and train-nearby features. The consistency characteristic coefficient of the i-th onboard antenna is... The specific calculation formula is as follows: ; The consistency characteristic coefficient of the antenna near the j-th train The specific calculation formula is as follows: ; Initialize the screening threshold. If the consistency characteristic coefficient of the i-th vehicle-mounted antenna or the consistency characteristic coefficient of the j-th antenna near the train is greater than or equal to the screening threshold, then the antenna is an antenna with a problem. If the consistency characteristic coefficient of the i-th vehicle-mounted antenna or the consistency characteristic coefficient of the j-th antenna near the train is less than the screening threshold, then the antenna is an antenna without a problem. For vehicle-mounted antennas without problems, a random inertial navigation diagnostic algorithm is designed, with the following specific steps: (1) Randomly select a vehicle-mounted antenna that does not have a problem, and obtain the current time t of the vehicle-mounted antenna and the previous continuous time t. The vehicle-mounted antenna position at each moment is obtained, and the current moment and the continuous positions before the current moment are acquired. The train's inertial navigation position at any given moment; (2) Calculate the volatility T from the position of the onboard antenna and the position of the train's inertial navigation system. The volatility T of the i-th onboard antenna without problems at time t. The specific formula is as follows: ; in, This indicates that the i-th vehicle-mounted antenna at time t is continuous with the previous ones. The maximum x-axis coordinate at each time point This indicates that the train's inertial navigation position at time t is continuous with the previous position. The maximum x-axis coordinate at each time point This indicates that the i-th vehicle-mounted antenna at time t is continuous with the previous ones. The maximum value of the y-axis coordinate at each moment. This indicates that the train's inertial navigation position at time t is continuous with the previous position. The maximum value of the y-axis coordinate at each moment; This indicates that the i-th vehicle-mounted antenna at time t is continuous with the previous ones. The maximum value of the z-axis coordinate at each time point This indicates that the train's inertial navigation position at time t is continuous with the previous position. The maximum z-axis coordinate at each moment, where r represents an integer less than 1. ; (3) Initialize the maximum diagnostic threshold, if volatility If the volatility is greater than or equal to the maximum diagnostic threshold, the antenna is re-marked as a problematic antenna. If the value is less than the maximum diagnostic threshold, no action is taken; antennas with self-diagnostic problems are removed, resulting in a set of secondary effective antennas.

[0009] Optionally, step S4 includes: In the set of secondary effective antennas, there are a total of One vehicle-mounted antenna, Antennas near the train; Initialize the sliding window, which contains... At any given time, obtain the satellite signal loss rate of antennas near the train in the secondary effective antenna set, and calculate the satellite interference coefficient K. The specific calculation formula is as follows: ; Where g represents the antenna near the train, f represents the time in the sliding window, and e represents the exponent. This represents the satellite signal loss rate of the antenna near the g-th train at time f; Initialize the filtering threshold. If the satellite interference coefficient is less than or equal to the filtering threshold, the train is near the tunnel. If the satellite interference coefficient is greater than the filtering threshold, the train is not near the tunnel. When the train is near a tunnel, a multi-antenna compensation algorithm is designed to calculate the train's position using both the nearby antennas and the onboard antennas in the secondary effective antenna set. When the train is not near a tunnel, the onboard antennas in the secondary effective antenna set are used to calculate the train's position.

[0010] On the other hand, the present invention also provides a high-speed rail antenna positioning system with anti-interference capabilities, the high-speed rail antenna positioning system with anti-interference capabilities comprising: The signal receiving module receives train speed, train inertial navigation position and satellite signals through the on-board antenna located on the train body. The antenna near the train is located near the train track and receives satellite signals. The self-diagnosis optimization module constructs an antenna set by combining the vehicle-mounted antenna and antennas near the train. Using the satellite signals received by the antenna set, a self-diagnosis signal detection algorithm is designed to calculate the self-diagnosis optimization coefficient, initialize the optimization threshold, and remove antennas with self-diagnosis problems based on the self-diagnosis optimization coefficient and the optimization threshold to obtain a first-level effective antenna set. The feature extraction module designs a local area anti-interference positioning algorithm for the first-level effective antenna set. It calculates the train's onboard features based on the train speed, train inertial navigation position, and satellite signals received by the onboard antennas in the first-level effective antenna set, and calculates the train's nearby features based on the satellite signals received by the antennas near the train in the first-level effective antenna set. It calculates the consistency feature coefficient using the onboard features and the train's nearby features, and filters the consistency feature coefficients to obtain the second-level effective antenna set. The antenna compensation module uses the train-near antennas in the secondary effective antenna set to calculate the satellite interference coefficient. Based on the satellite interference coefficient, it determines whether the train is near a tunnel. When the train is near a tunnel, a multi-antenna compensation algorithm is designed, which uses the train-near antennas in the secondary effective antenna set and the on-board antenna to jointly calculate the train's position. When the train is not near a tunnel, the on-board antenna in the secondary effective antenna set calculates the train's position, and outputs the train position and the position of the train-near antennas.

[0011] The beneficial effects of the technical solution provided by this invention include at least the following: 1. This invention achieves antenna-level self-diagnosis and first-level effective antenna set optimization, improving anti-interference and fault tolerance capabilities from the source. It constructs a collaborative antenna set using vehicle-mounted and trackside antennas, designs a self-diagnostic signal detection algorithm based on satellite observations, calculates optimization coefficients, and combines thresholds to quickly eliminate problematic antennas, forming a first-level effective antenna set. This blocks interference and fault propagation from the receiving front end. Compared to traditional single-antenna or non-diagnostic redundancy schemes, this method can identify abnormal gain, phase distortion, channel faults, and strong interference antennas in real time, preventing ill-conditioned observations from entering the positioning calculation. The self-diagnosis mechanism quantifies antenna health, achieving fault isolation within seconds, significantly improving the system's robustness in complex electromagnetic environments. First-level screening reduces the computational load of subsequent algorithms, improves real-time performance, and adapts to the high dynamic response requirements of high-speed rail. This design breaks through the limitations of traditional back-end filtering anti-interference methods by establishing a "receive-diagnosis-optimization" front-end anti-interference link, significantly improving the effective antenna signal-to-noise ratio and observation consistency, greatly reducing the probability of positioning jumps, and providing reliable input for high-precision positioning. 2. Constructing local area anti-interference positioning to achieve two-level accurate optimization and robust fusion. Based on the first-level effective set, this invention extracts features from vehicle-mounted and trackside antennas respectively, calculates consistency feature coefficients, and filters them to obtain a second-level effective antenna set, achieving in-depth purification of observation quality and enhanced spatial redundancy. This method combines train-based positioning with trackside benchmark verification, utilizing the spatial distribution of multiple antennas to form cross-validation, suppressing deviations caused by multipath interference, obstruction, and local electromagnetic interference. Compared to traditional single-source positioning or simple weighted fusion, this method significantly improves positioning accuracy and stability through feature-level consistency discrimination, effectively suppressing non-line-of-sight and abrupt interference. The second-level set combines vehicle-mounted mobility with trackside benchmark reliability, forming a space-air-ground collaborative positioning architecture, laying the foundation for tunnel scene compensation and high-precision output across the entire domain. 3. Establish an interference perception and tunnel adaptive compensation mechanism to achieve seamless and continuous positioning across the entire line. This invention utilizes a two-level effective set to calculate the satellite interference coefficient. When the train is near a tunnel, the antenna near the train and the onboard antenna jointly calculate the position to maintain continuous and stable output. In open areas, the onboard antenna calculates independently, balancing efficiency and accuracy. This mechanism solves the problems of discontinuity, drift, and recovery lag in traditional positioning at tunnel entrances, achieving smooth transitions in blind zones. Simultaneously, it outputs the train position and the position near the train, forming position anchoring and fault tracing capabilities, facilitating rapid diagnosis and scheduling decisions during operation and maintenance. This invention integrates interference perception, scene recognition, and compensation calculation, significantly improving overall availability and reliability, meeting the stringent positioning requirements of high-speed rail automatic driving and intelligent operation and maintenance, and promoting the upgrading of railway positioning technology towards autonomy and intelligence. Attached Figure Description

[0012] Figure 1 This is a schematic diagram of the overall execution flow of a high-speed rail antenna positioning method with anti-interference capabilities provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the antenna division near a train in a high-speed rail antenna positioning system with anti-interference capabilities, provided as an embodiment of the present invention. Detailed Implementation

[0013] The present invention will be further described below with reference to the accompanying drawings, but this is not intended to limit the present invention in any way. Any modifications or substitutions made based on the teachings of the present invention shall fall within the protection scope of the present invention. Example 1

[0014] This embodiment provides a high-speed rail antenna positioning method with anti-interference capabilities, which can be implemented by electronic devices, such as... Figure 1 As shown. Specifically, the method in this embodiment includes the following steps: The train receives train speed, inertial navigation position, and satellite signals via onboard antennas located on the train itself. In this scheme, satellite signals mainly refer to carrier-to-noise ratio, signal loss rate, and train position. Each train car carries one onboard antenna, located at the geometric center of the car's roof. The number of onboard antennas is [number missing]. , This refers to the vehicle-mounted antennas; the number of vehicle-mounted antennas is the same as the number of train carriages. The antennas near the train tracks are located to receive satellite signals. The number of these antennas is... , Indicates the antenna near the train; It should be further explained that this solution uses a combination of vehicle-mounted antennas and antennas near the train for interference identification. Not only can dynamic identification be performed through vehicle-mounted antennas, but the static advantages of antennas near the train can also be utilized to further improve the anti-interference capability of high-speed rail antenna positioning by combining dynamic and static methods, thereby improving the positioning accuracy. It needs further clarification that the definition of "nearby" in this scheme for "train-nearby antennas" is based primarily on distance, taking into account the actual train operation conditions. Antennas within a 10-kilometer radius of the train's geometric center are considered train-nearby antennas. Figure 2 As shown, the antennas near the train are updated according to the distance. In this embodiment, the antennas are updated every ten kilometers when the train runs. This ensures that the antennas near the train are consistent in a short period of time when interference is identified and judged. On the other hand, real-time updating of the antennas near the train has high hardware costs and requires a lot of computing power. Therefore, this solution has considerable economic value. The vehicle-mounted antenna and the antennas near the train constitute an antenna set Q, which contains ( + ) antennas, of which , This represents the i-th vehicle-mounted antenna. Indicates the first One vehicle-mounted antenna, This represents the antenna near the j-th train. Indicates the first There are several antennas near the train, where i represents the serial number of the onboard antenna and j represents the serial number of the antenna near the train. Using satellite signals received by antennas within an antenna array, a self-diagnostic signal detection algorithm is designed, and the self-diagnostic optimization coefficients are calculated. The specific steps are as follows: (1) Obtain the train speed from the satellite signal of the i-th on-board antenna. Obtain the train speed from the satellite signal of the antenna near the j-th train. We obtain the set of train speeds V, where Calculate the maximum value in V. Calculate the minimum value in V. , This indicates the calculation of the maximum value. This indicates the calculation of the minimum value; (2) Calculate the speed optimization coefficient of the i-th vehicle-mounted antenna The specific calculation formula is as follows: ; in, Indicates the first Train speed in satellite signals from a single vehicle-mounted antenna. Indicates the first Train speed in satellite signals from antennas near the train Calculate the speed optimization coefficient of the antenna near the j-th train. The specific calculation formula is as follows: ; (3) Obtain the carrier-to-noise ratio in the satellite signal of the i-th vehicle-mounted antenna. Obtain the carrier-to-noise ratio in the satellite signal from the antenna near the j-th train. Calculate the carrier-to-noise ratio optimization coefficient for the i-th vehicle-mounted antenna. The specific calculation formula is as follows: ; in, Indicates the first The carrier-to-noise ratio of satellite signals from a vehicle-mounted antenna. Indicates the first Carrier-to-noise ratio in satellite signals from antennas near a train; Calculate the carrier-to-noise ratio optimization coefficients for the antenna near the j-th train. The specific calculation formula is as follows: ; (4) Calculate the self-diagnosis optimization coefficient from the speed optimization coefficient and the carrier-to-noise ratio optimization coefficient. The self-diagnosis optimization coefficient of the i-th vehicle-mounted antenna is: The specific calculation formula is as follows: ; The self-diagnostic optimization coefficient of the antenna near the j-th train is: The specific calculation formula is as follows: ; in, and This represents the normalization adjustment coefficient; Initialize the optimization threshold. If the self-diagnosis optimization coefficient of the i-th vehicle-mounted antenna or the self-diagnosis optimization coefficient of the j-th train-near antenna is greater than or equal to the optimization threshold, then the antenna is an antenna with a problem. If the self-diagnosis optimization coefficient of the i-th vehicle-mounted antenna or the self-diagnosis optimization coefficient of the j-th train-near antenna is less than the optimization threshold, then the antenna is an antenna without a problem. Remove the antennas with self-diagnosis problems to obtain the first-level effective antenna set.

[0015] It should be noted that the homogeneous approach, which combines speed and carrier-to-noise ratio optimization, enables antenna self-diagnosis. and As a normalization adjustment coefficient, it adjusts two different parameters, speed and load-to-noise ratio, to the same level of value. For example, the train speed is generally 500 meters per second, and the load-to-noise ratio is 40, so it can be... Set to 10, Setting it to 100 enables data normalization.

[0016] In the set of first-order effective antennas, there are a total of One vehicle-mounted antenna, Antennas near the train; For a set of first-level effective antennas, a local area anti-interference localization algorithm is designed. The algorithm calculates the train's on-board characteristics from the on-board antennas in the first-level effective antenna set, and calculates the train's proximity characteristics from the antennas near the train in the first-level effective antenna set. The consistency characteristic coefficient is then calculated using both the on-board and proximity characteristics. The specific steps are as follows: (1) Calculate the train's onboard characteristics from the onboard antennas in the first-level effective antenna set, and the train's onboard characteristics of the i-th onboard antenna. The specific calculation formula is as follows: ; in, This indicates the number of antennas selected around the train's onboard antenna. This represents the x-axis coordinate of the i-th vehicle-mounted antenna. This represents the y-coordinate of the i-th vehicle-mounted antenna. This represents the z-axis coordinate of the i-th vehicle-mounted antenna. This indicates the relationship between the i-th vehicle-mounted antenna and its surroundings. The average x-axis coordinate of each vehicle-mounted antenna This indicates the relationship between the i-th vehicle-mounted antenna and its surroundings. The average y-axis coordinate of each vehicle-mounted antenna This indicates the relationship between the i-th vehicle-mounted antenna and its surroundings. The average z-axis coordinate of each vehicle-mounted antenna; (2) Calculate the train proximity characteristics from the train proximity antennas in the first-order effective antenna set, and calculate the train proximity characteristics of the j-th train proximity antenna. The specific calculation formula is as follows: ; in, This indicates the number of antennas selected around the antenna near the train. This represents the x-axis coordinate of the antenna near the i-th train. Let represent the y-axis coordinate of the antenna near the i-th train. This represents the z-axis coordinate of the antenna near the i-th train. This indicates the relationship between the antenna near the i-th train and its surroundings. The average x-axis coordinate of antennas near each train. This indicates the relationship between the antenna near the i-th train and its surroundings. The average y-axis coordinate of antennas near each train. This indicates the relationship between the antenna near the i-th train and its surroundings. The mean z-axis coordinate of antennas near each train; It should be further explained that in this plan It is based on and The value is determined, and 0.5 times the minimum value is taken as the minimum value. The value, for example when It is 10. When it is 20, take It is 5, when It is 9. At 20:00, It is 4; (3) Calculate the consistency characteristic coefficient using train onboard characteristics and train proximity characteristics. Calculate the maximum value of all vehicle-mounted antennas on the x-axis. The maximum value of the y-axis The maximum value of the z-axis minimum value of the x-axis minimum value of the y-axis minimum value of the z-axis ; Calculate the maximum value of all antennas near trains on the x-axis. The maximum value of the y-axis The maximum value of the z-axis minimum value of the x-axis minimum value of the y-axis minimum value of the z-axis ; The consistency characteristic coefficient is calculated using train-mounted features and train-nearby features. The consistency characteristic coefficient of the i-th onboard antenna is... The specific calculation formula is as follows: ; The consistency characteristic coefficient of the antenna near the j-th train The specific calculation formula is as follows: ; Initialize the screening threshold. If the consistency characteristic coefficient of the i-th vehicle-mounted antenna or the consistency characteristic coefficient of the j-th antenna near the train is greater than or equal to the screening threshold, then the antenna is an antenna with a problem. If the consistency characteristic coefficient of the i-th vehicle-mounted antenna or the consistency characteristic coefficient of the j-th antenna near the train is less than the screening threshold, then the antenna is an antenna without a problem. It should be further explained that in this scheme, if detection... or If the value is 0, the algorithm will fail. To address the above problem, in this solution, based on the train's onboard features and the features near the train, the consistency feature coefficient can also be calculated in the following way. Eliminate and Sub-items that are zero, for example If the coefficient is zero, then the consistency characteristic coefficient of the i-th vehicle-mounted antenna is zero. The specific calculation formula is as follows: ; For example If the coefficient is zero, then the consistency characteristic coefficient of the antenna near the i-th train is zero. The specific calculation formula is as follows: Consistency characteristic coefficient of the antenna near the j-th train. The specific calculation formula is as follows: ; For vehicle-mounted antennas without problems, a random inertial navigation diagnostic algorithm is designed, with the following specific steps: (1) Randomly select a vehicle-mounted antenna that does not have a problem, and obtain the current time t of the vehicle-mounted antenna and the previous continuous time t. The vehicle-mounted antenna position at each moment is obtained, and the current moment and the continuous positions before the current moment are acquired. The train's inertial navigation position at any given moment; (2) Calculate the volatility T from the position of the onboard antenna and the position of the train's inertial navigation system. The volatility T of the i-th onboard antenna without problems at time t. The specific formula is as follows: ; in, This indicates that the i-th vehicle-mounted antenna at time t is continuous with the previous ones. The maximum x-axis coordinate at each time point This indicates that the train's inertial navigation position at time t is continuous with the previous position. The maximum x-axis coordinate at each time point This indicates that the i-th vehicle-mounted antenna at time t is continuous with the previous ones. The maximum value of the y-axis coordinate at each moment. This indicates that the train's inertial navigation position at time t is continuous with the previous position. The maximum value of the y-axis coordinate at each moment; This indicates that the i-th vehicle-mounted antenna at time t is continuous with the previous ones. The maximum value of the z-axis coordinate at each time point This indicates that the train's inertial navigation position at time t is continuous with the previous position. The maximum value of the z-axis coordinate at each moment; (3) Initialize the maximum diagnostic threshold. If the volatility is greater than or equal to the maximum diagnostic threshold, the antenna is remarked as an antenna with a problem. If the volatility is less than the maximum diagnostic threshold, no action is taken. It should be further explained that by using the train's inertial navigation position to further identify the position of the on-board antenna, the random errors caused by problems with both the antennas near the train and the on-board antenna can be avoided, thereby further improving the positioning accuracy and anti-interference capability of this solution. By removing antennas with self-diagnostic problems, a set of effective secondary antennas is obtained.

[0017] In the set of secondary effective antennas, there are a total of One vehicle-mounted antenna, Antennas near the train; Initialize the sliding window, which contains... At any given time, obtain the satellite signal loss rate of antennas near the train in the secondary effective antenna set, and calculate the satellite interference coefficient K. The specific calculation formula is as follows: ; Where g represents the antenna near the train, f represents the time in the sliding window, and e represents the exponent. This represents the satellite signal loss rate of the antenna near the g-th train at time f; Initialize the filtering threshold. If the satellite interference coefficient is less than or equal to the filtering threshold, the train is near the tunnel. If the satellite interference coefficient is greater than the filtering threshold, the train is not near the tunnel. When the train is near a tunnel, a multi-antenna compensation algorithm is designed to calculate the train's position using both the train-near antennas and the onboard antennas in the secondary effective antenna set. The train's position is the average of the train's position received by all onboard antennas and the train's position received by all train-near antennas. When the train is not near a tunnel, the train's position is calculated using the onboard antennas in the secondary effective antenna set, where the train's position is the average of the positions of all onboard antennas. Output the train's location and the location of antennas near the train. Example 2

[0018] This embodiment provides a high-speed rail antenna positioning system with anti-interference capabilities, such as... Figure 2 As shown, the high-speed rail antenna positioning system with anti-interference capabilities includes the following modules: The signal receiving module receives train speed, train inertial navigation position and satellite signals through the on-board antenna located on the train body. The antenna near the train is located near the train track and receives satellite signals. The self-diagnosis optimization module constructs an antenna set by combining the vehicle-mounted antenna and antennas near the train. Using the satellite signals received by the antenna set, a self-diagnosis signal detection algorithm is designed to calculate the self-diagnosis optimization coefficient, initialize the optimization threshold, and remove antennas with self-diagnosis problems based on the self-diagnosis optimization coefficient and the optimization threshold to obtain a first-level effective antenna set. The feature extraction module designs a local area anti-interference positioning algorithm for the first-level effective antenna set. It calculates the train's onboard features based on the train speed, train inertial navigation position, and satellite signals received by the onboard antennas in the first-level effective antenna set, and calculates the train's nearby features based on the satellite signals received by the antennas near the train in the first-level effective antenna set. It calculates the consistency feature coefficient using the onboard features and the train's nearby features, and filters the consistency feature coefficients to obtain the second-level effective antenna set. The antenna compensation module uses the antennas near the train in the secondary effective antenna set to calculate the satellite interference coefficient. Based on the satellite interference coefficient, it determines whether the train is near the tunnel. When the train is near the tunnel, a multi-antenna compensation algorithm is designed to calculate the train position using both the antennas near the train in the secondary effective antenna set and the on-board antenna. When the train is not near the tunnel, the on-board antenna in the secondary effective antenna set calculates the train position and outputs the train position and the position of the antennas near the train. As used herein, the term "preferred" is meant as an example, illustration, or illustration. Any aspect or design described herein as "preferred" need not be construed as being more advantageous than other aspects or designs. Rather, the use of the term "preferred" is intended to present the concept in a specific manner. As used in this application, the term "or" is intended to mean an inclusive "or" rather than an exclusionary "or." That is, unless otherwise specified or clear from the context, "X uses A or B" naturally includes either of the permutations. That is, if X uses A; X uses B; or X uses both A and B, then "X uses A or B" is satisfied in any of the foregoing examples.

[0019] Furthermore, although this disclosure has been shown and described with respect to one or more implementations, equivalent variations and modifications will occur to those skilled in the art based on a reading and understanding of this specification and the accompanying drawings. This disclosure includes all such modifications and variations and is limited only by the scope of the appended claims. In particular, with respect to the various functions performed by the aforementioned components (e.g., elements, etc.), the terminology used to describe such components is intended to correspond to any component (unless otherwise indicated) that performs the specified function of said component (e.g., is functionally equivalent to it), even if structurally not equivalent to the disclosed structure performing the functions in the exemplary implementations of this disclosure shown herein. Moreover, although specific features of this disclosure have been disclosed with respect to only one of several implementations, such features may be combined with one or more features of other implementations that may be desirable and advantageous for a given or particular application. Furthermore, with regard to the use of the terms “comprising,” “having,” “containing,” or variations thereof in the Detailed Description or claims, such terms are intended to be included in a manner similar to the term “including.”

[0020] The functional units in this invention embodiment can be integrated into a processing module, or each unit can exist physically separately, or multiple units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. The aforementioned devices or systems can execute the storage methods in the corresponding method embodiments.

[0021] In summary, the above embodiments are one implementation of the present invention, but the implementation of the present invention is not limited to the embodiments described above. Any changes, modifications, substitutions, combinations, or simplifications made that deviate from the spirit and principle of the present invention should be considered equivalent substitutions and are included within the protection scope of the present invention.

Claims

1. A high-speed rail antenna positioning method with anti-interference capabilities, characterized in that, Includes the following steps: S1: The train speed, train inertial navigation position and satellite signals are received through the on-board antenna located on the train body. The antenna near the train is located near the train track and receives satellite signals. S2: Construct an antenna set by combining the vehicle-mounted antenna and antennas near the train. Utilize the satellite signals received by the antenna set to design a self-diagnostic signal detection algorithm, calculate the self-diagnostic optimization coefficient, initialize the optimization threshold, and based on the self-diagnostic optimization coefficient and the optimization threshold, eliminate antennas with self-diagnostic problems to obtain a first-level effective antenna set. S3: For the first-level effective antenna set, design a local area anti-interference positioning algorithm. Calculate the train's onboard characteristics based on the train speed, train inertial navigation position, and satellite signals received by the onboard antennas in the first-level effective antenna set. Calculate the train's proximity characteristics based on the satellite signals received by the antennas near the train in the first-level effective antenna set. Calculate the consistency characteristic coefficient using the train's onboard characteristics and the train's proximity characteristics, and then filter the consistency characteristic coefficients to obtain the second-level effective antenna set. S4: Calculate the satellite interference coefficient using the train-near antennas in the secondary effective antenna set. Determine whether the train is near the tunnel based on the satellite interference coefficient. When the train is near the tunnel, design a multi-antenna compensation algorithm to calculate the train's position using both the train-near antennas in the secondary effective antenna set and the onboard antennas. When the train is not near the tunnel, calculate the train's position using the onboard antennas in the secondary effective antenna set. S5: Outputs the train position and the position of the antennas near the train.

2. The high-speed rail antenna positioning method with anti-interference capability according to claim 1, characterized in that, Step S1 includes: The onboard antennas are located on the train body and receive train speed v, train inertial navigation position, and satellite signals. Each train car carries one onboard antenna, located at the geometric center of the car's roof. The number of onboard antennas is [number missing]. , This refers to the vehicle-mounted antennas; the number of vehicle-mounted antennas is the same as the number of train carriages. The antennas near the train are located beside the train tracks and receive satellite signals. The number of these antennas near the train is... , This indicates an antenna near the train.

3. The high-speed rail antenna positioning method with anti-interference capability according to claim 1, characterized in that, Step S2 includes: An antenna set Q is constructed by combining the vehicle-mounted antenna and antennas near the train. The antenna set contains ( ) + ) antennas, of which , This represents the i-th vehicle-mounted antenna. Indicates the first One vehicle-mounted antenna, This represents the antenna near the j-th train. Indicates the first There are several antennas near the train, where i represents the serial number of the onboard antenna and j represents the serial number of the antenna near the train. Using satellite signals received by antennas within an antenna array, a self-diagnostic signal detection algorithm is designed, and the self-diagnostic optimization coefficients are calculated. The specific steps are as follows: (1) Obtain the train speed from the satellite signal of the i-th on-board antenna. Obtain the train speed from the satellite signal of the antenna near the j-th train. We obtain the set of train speeds V, where Calculate the maximum value in V. Calculate the minimum value in V. , This indicates the calculation of the maximum value. This indicates the calculation of the minimum value; (2) Calculate the speed optimization coefficient of the i-th vehicle-mounted antenna The specific calculation formula is as follows: ； in, Indicates the first Train speed in satellite signals from a single vehicle-mounted antenna. Indicates the first Train speed in satellite signals from antennas near the train Calculate the speed optimization coefficient of the antenna near the j-th train. The specific calculation formula is as follows: ； (3) Obtain the carrier-to-noise ratio in the satellite signal of the i-th vehicle-mounted antenna. Obtain the carrier-to-noise ratio in the satellite signal from the antenna near the j-th train. Calculate the carrier-to-noise ratio optimization coefficient for the i-th vehicle-mounted antenna. The specific calculation formula is as follows: ； in, Indicates the first The carrier-to-noise ratio of satellite signals from a vehicle-mounted antenna. Indicates the first Carrier-to-noise ratio in satellite signals from antennas near a train; Calculate the carrier-to-noise ratio optimization coefficients for the antenna near the j-th train. The specific calculation formula is as follows: ； (4) Calculate the self-diagnosis optimization coefficient from the speed optimization coefficient and the carrier-to-noise ratio optimization coefficient. The self-diagnosis optimization coefficient of the i-th vehicle-mounted antenna is: The specific calculation formula is as follows: ； The self-diagnostic optimization coefficient of the antenna near the j-th train is: The specific calculation formula is as follows: ； in, and This represents the normalization adjustment coefficient; Initialize the optimization threshold. If the self-diagnosis optimization coefficient of the i-th vehicle-mounted antenna or the self-diagnosis optimization coefficient of the j-th train-near antenna is greater than or equal to the optimization threshold, then the antenna is an antenna with a problem. If the self-diagnosis optimization coefficient of the i-th vehicle-mounted antenna or the self-diagnosis optimization coefficient of the j-th train-near antenna is less than the optimization threshold, then the antenna is an antenna without a problem. Remove the antennas with self-diagnosis problems to obtain the first-level effective antenna set.

4. The high-speed rail antenna positioning method with anti-interference capability according to claim 1, characterized in that, Step S3 includes: In the set of first-order effective antennas, there are a total of One vehicle-mounted antenna, Antennas near the train; For a set of first-level effective antennas, a local area anti-interference localization algorithm is designed. The algorithm calculates the train's on-board characteristics from the on-board antennas in the first-level effective antenna set, and calculates the train's proximity characteristics from the antennas near the train in the first-level effective antenna set. The consistency characteristic coefficient is then calculated using both the on-board and proximity characteristics. The specific steps are as follows: (1) Calculate the train's onboard characteristics from the onboard antennas in the first-level effective antenna set, and the train's onboard characteristics of the i-th onboard antenna. The specific calculation formula is as follows: ； in, This indicates the number of antennas selected around the train's onboard antenna. This represents the x-axis coordinate of the i-th vehicle-mounted antenna. This represents the y-coordinate of the i-th vehicle-mounted antenna. This represents the z-axis coordinate of the i-th vehicle-mounted antenna. This indicates the relationship between the i-th vehicle-mounted antenna and its surroundings. The average x-axis coordinate of each vehicle-mounted antenna This indicates the relationship between the i-th vehicle-mounted antenna and its surroundings. The average y-axis coordinate of each vehicle-mounted antenna This indicates the relationship between the i-th vehicle-mounted antenna and its surroundings. The average z-axis coordinate of each vehicle-mounted antenna; (2) Calculate the train proximity characteristics from the train proximity antennas in the first-order effective antenna set, and calculate the train proximity characteristics of the j-th train proximity antenna. The specific calculation formula is as follows: ； in, This indicates the number of antennas selected around the antenna near the train. This represents the x-axis coordinate of the antenna near the i-th train. Let represent the y-axis coordinate of the antenna near the i-th train. This represents the z-axis coordinate of the antenna near the i-th train. This indicates the relationship between the antenna near the i-th train and its surroundings. The average x-axis coordinate of antennas near each train. This indicates the relationship between the antenna near the i-th train and its surroundings. The average y-axis coordinate of antennas near each train. This indicates the relationship between the antenna near the i-th train and its surroundings. The average z-axis coordinate of antennas near each train; (3) Calculate the consistency characteristic coefficient using train onboard characteristics and train proximity characteristics. Calculate the maximum value of all vehicle-mounted antennas on the x-axis. The maximum value of the y-axis The maximum value of the z-axis minimum value of the x-axis minimum value of the y-axis minimum value of the z-axis ; Calculate the maximum value of all antennas near trains on the x-axis. The maximum value of the y-axis The maximum value of the z-axis minimum value of the x-axis minimum value of the y-axis minimum value of the z-axis ; The consistency characteristic coefficient is calculated using train-mounted features and train-nearby features. The consistency characteristic coefficient of the i-th onboard antenna is... The specific calculation formula is as follows: ； The consistency characteristic coefficient of the antenna near the j-th train The specific calculation formula is as follows: ； Initialize the screening threshold. If the consistency characteristic coefficient of the i-th vehicle-mounted antenna or the consistency characteristic coefficient of the j-th antenna near the train is greater than or equal to the screening threshold, then the antenna is an antenna with a problem. If the consistency characteristic coefficient of the i-th vehicle-mounted antenna or the consistency characteristic coefficient of the j-th antenna near the train is less than the screening threshold, then the antenna is an antenna without a problem. For vehicle-mounted antennas without problems, a random inertial navigation diagnostic algorithm is designed, with the following specific steps: (1) Randomly select a vehicle-mounted antenna that does not have a problem, and obtain the current time t of the vehicle-mounted antenna and the previous continuous time t. The vehicle-mounted antenna position at each moment is obtained, and the current moment and the continuous positions before the current moment are acquired. The train's inertial navigation position at any given moment; (2) Calculate the volatility T from the position of the onboard antenna and the position of the train's inertial navigation system. The volatility T of the i-th onboard antenna without problems at time t. The specific formula is as follows: ； in, This indicates that the i-th vehicle-mounted antenna at time t is continuous with the previous ones. The maximum x-axis coordinate at each time point This indicates that the train's inertial navigation position at time t is continuous with the previous position. The maximum x-axis coordinate at each time point This indicates that the i-th vehicle-mounted antenna at time t is continuous with the previous ones. The maximum value of the y-axis coordinate at each moment. This indicates that the train's inertial navigation position at time t is continuous with the previous position. The maximum value of the y-axis coordinate at each moment; This indicates that the i-th vehicle-mounted antenna at time t is continuous with the previous ones. The maximum value of the z-axis coordinate at each time point This indicates that the train's inertial navigation position at time t is continuous with the previous position. The maximum z-axis coordinate at each moment, where r represents an integer less than 1. ; (3) Initialize the maximum diagnostic threshold, if volatility If the volatility is greater than or equal to the maximum diagnostic threshold, the antenna is re-marked as a problematic antenna. If the value is less than the maximum diagnostic threshold, no action will be taken. By removing antennas with self-diagnostic problems, a set of effective secondary antennas is obtained.

5. The high-speed rail antenna positioning method with anti-interference capability according to claim 1, characterized in that, Step S4 includes: In the set of secondary effective antennas, there are a total of One vehicle-mounted antenna, Antennas near the train; Initialize the sliding window, which contains... At any given time, obtain the satellite signal loss rate of antennas near the train in the secondary effective antenna set, and calculate the satellite interference coefficient K. The specific calculation formula is as follows: ； Where g represents the antenna near the train, f represents the time in the sliding window, and e represents the exponent. This represents the satellite signal loss rate of the antenna near the g-th train at time f; Initialize the filtering threshold. If the satellite interference coefficient is less than or equal to the filtering threshold, the train is near the tunnel. If the satellite interference coefficient is greater than the filtering threshold, the train is not near the tunnel. When the train is near a tunnel, a multi-antenna compensation algorithm is designed to calculate the train's position using both the nearby antennas and the onboard antennas in the secondary effective antenna set. When the train is not near a tunnel, the onboard antennas in the secondary effective antenna set are used to calculate the train's position.

6. A high-speed rail antenna positioning system with anti-interference capabilities, characterized in that, include: The signal receiving module receives train speed, train inertial navigation position and satellite signals through the on-board antenna located on the train body. The antenna near the train is located near the train track and receives satellite signals. The self-diagnosis optimization module constructs an antenna set by combining the vehicle-mounted antenna and antennas near the train. Using the satellite signals received by the antenna set, a self-diagnosis signal detection algorithm is designed to calculate the self-diagnosis optimization coefficient, initialize the optimization threshold, and remove antennas with self-diagnosis problems based on the self-diagnosis optimization coefficient and the optimization threshold to obtain a first-level effective antenna set. The feature extraction module designs a local area anti-interference positioning algorithm for the first-level effective antenna set. It calculates the train's onboard features based on the train speed, train inertial navigation position, and satellite signals received by the onboard antennas in the first-level effective antenna set, and calculates the train's nearby features based on the satellite signals received by the antennas near the train in the first-level effective antenna set. It calculates the consistency feature coefficient using the onboard features and the train's nearby features, and filters the consistency feature coefficients to obtain the second-level effective antenna set. The antenna compensation module uses the antennas near the train in the secondary effective antenna set to calculate the satellite interference coefficient. Based on the satellite interference coefficient, it determines whether the train is near the tunnel. When the train is near the tunnel, a multi-antenna compensation algorithm is designed to calculate the train position using both the antennas near the train in the secondary effective antenna set and the on-board antenna. When the train is not near the tunnel, the on-board antenna in the secondary effective antenna set calculates the train position and outputs the train position and the position of the antennas near the train. To achieve the anti-interference high-speed rail antenna positioning method as described in any one of claims 1-5.

Images