Positioning method and system based on Beidou and 5G AeroMACS

Abstract

The invention relates to the technical field of satellite positioning and transmission, in particular to a positioning method and system based on Beidou and 5G AeroMACS, data transmission is carried out by adopting the method or system provided by the invention and adopting a 5G AeroMACS wireless network, a traditional 4G / 5G public network is not used, a safe and reliable data transmission link and high-bandwidth and low-delay transmission quality are provided, and the positioning method and system can be applied to the field of satellite positioning and transmission. The risk of data leakage generated through a communication link layer can be effectively reduced; an autonomous and controllable single Beidou positioning scheme is adopted, the risk of GPS precision reduction caused by various factors can be effectively reduced while a positioning effect higher than GPS precision is provided, continuous, stable and reliable positioning precision can be provided, and the positioning precision can be further improved through an algorithm provided by the scheme.

Description

Technical Field

[0001] The present invention relates to the field of satellite positioning and transmission technology, and in particular to a positioning method and system based on Beidou and 5G AeroMACS. Background Art

[0002] Under the specific requirements of the airport operating environment, the Beidou Satellite Navigation System (BDS) technology is used to monitor bridge displacement, which provides strong technical support for ensuring the safety of bridge structures and the stability of the overall airport operation. As a satellite positioning and navigation technology with completely independent intellectual property rights in my country, BDS technology has gradually become the preferred solution for monitoring the subtle displacement and deformation of bridges with its high-precision, all-weather, and real-time positioning capabilities, especially for complex and changeable airport environments. Applying BDS technology in airport bridge displacement monitoring can be achieved.

[0003] The traditional solution of positioning through GPS is easily affected by GPS services, resulting in reduced positioning accuracy, thus affecting the results of displacement analysis. Summary of the invention

[0004] The purpose of the present invention is to provide a positioning method and system based on Beidou and 5G AeroMACS to solve the above-mentioned problems in the prior art.

[0005] The present invention is achieved through the following technical solutions: The present invention provides a positioning method based on Beidou and 5G AeroMACS, comprising: Obtain frequency signals broadcast by Beidou satellites and transmit them to the data processing end through the 5G AeroMACS network; Establishing a first carrier pseudorange observation model, and obtaining carrier observation values ​​and pseudorange observation values ​​of frequency signals broadcast by Beidou satellites through the first carrier pseudorange observation model; The first carrier pseudorange observation model is processed by combining integer coefficients in cycles to obtain a second carrier pseudorange observation model; The double-difference ionospheric delay and the combined integer ambiguity are traversed within a preset coefficient range through the second carrier pseudorange observation model to obtain the five-frequency combination coefficient, and the most ideal five-frequency combination coefficient is set. When the five-frequency combination coefficient obtained at this time is the most ideal five-frequency combination coefficient, the optimal solution is obtained; Establishing a first processing model, and outputting a first result after processing the obtained optimal solution through the first processing model; The first results of multiple Beidou satellites are jointly solved by least squares using a geometric correlation model to obtain the three coordinate component values ​​in the pseudorange state.

[0006] Preferably, it also includes: Establishing a second processing model, processing the obtained three coordinate component values ​​through the second processing model to output a second result; A first single-difference carrier phase observation model is established through the second result, the difference of the carrier phase observation values ​​of the two receivers for the same satellite is obtained, and the difference is substituted into the first single-difference carrier phase observation model as the single-difference carrier phase observation value, and various error parameters are eliminated through differential combination to obtain a second single-difference carrier phase observation model; A double-difference carrier phase observation model is obtained by processing two different second single-difference carrier phase observation models, and a double-difference carrier phase observation value is output through the double-difference carrier phase observation model. The double-difference carrier phase observation value is combined with the baseline vector to obtain the positioning information of the receiver.

[0007] Preferably, the establishing of the first carrier pseudorange observation model comprises:

[0008] In the formula, is the quadratic difference operator between stations and satellites, The observation frequency is The carrier observation value in units of distance, The observation frequency is The pseudorange observations in distance units, is the station-to-satellite distance, is the tropospheric delay, is the first-order ionospheric delay at the first frequency, For the The ionospheric delay coefficient at each frequency point is is the signal frequency at the first frequency point, For the The signal frequency at the frequency point, For the The wavelength of the electrical carrier signal at a frequency point, For the The integer ambiguity at the frequency point is is the observation noise of the carrier observation, is the observation noise of the pseudorange observation.

[0009] Preferably, the second carrier pseudorange observation model includes:

[0010]

[0011] In the formula, is the combination coefficient, is a natural number, , is the second carrier observation value, is the combined frequency, is the combined wavelength, is the combined ionospheric delay coefficient, is the combined integer ambiguity, is the combined noise amplification factor , The speed of light.

[0012] Preferably, the establishing of the first processing model comprises:

[0013] In the formula, is the pseudorange, To solve for the value, It is the random error of ambiguity caused by observation noise.

[0014] Preferably, the second processing model includes:

[0015] In the formula, Uploaded to the receiver The satellite's pseudorange observations, For the The geometric distance between the satellite and the receiver, For the The first observation parameter of the receiver, For the The satellite's second observation parameter, For the The third observation parameter of the satellite, For the The fourth observation parameter of the satellite, For the The fifth observation parameter of the satellite, The first The satellite's carrier phase observations, To observe the The satellite's integer ambiguity, is the carrier wavelength, is the signal frequency.

[0016] Preferably, the establishing of the first single-difference carrier phase observation model comprises:

[0017]

[0018]

[0019] In the formula, For the two receivers The difference in the satellite's carrier phase observations, The first The satellite's carrier phase observations, The first The satellite's carrier phase observations, The base station receiver and The distance of the satellite, is the first observation parameter of the base station receiver, , , They are the base station receiver relative to The third observation value parameter, the fourth observation value parameter, and the fifth observation value parameter of the satellite, The mobile station receiver observes The satellite's integer ambiguity, For the mobile station receiver and the The distance of the satellite, is the first observation parameter of the mobile station receiver, , , They are the relative The third observation value parameter, the fourth observation value parameter, and the fifth observation value parameter of the satellite, The mobile station receiver observes The satellite's integer ambiguity.

[0020] Preferably, the second single-difference carrier phase observation model includes:

[0021]

[0022]

[0023]

[0024] In the formula, For the two receivers The difference in the satellite's carrier phase observations, For the The single-difference distance to the satellite, is the single-difference first observation parameter, For the The single-difference integer ambiguity of the satellite, For the The single-difference fifth observation parameter of the satellite, For the The single-difference distance to the satellite, No. The single-difference integer ambiguity of the satellite, For the Single-difference fifth observation parameters of the satellite; The double-difference carrier phase observation model includes:

[0025]

[0026] In the formula, is the double-difference carrier phase observation value, is the double difference distance, is the double difference integer ambiguity, is the double-difference fifth observation parameter.

[0027] Preferably, the step of combining the double-difference carrier phase observation value with the baseline vector to obtain the positioning information of the receiver includes: According to the receiver's observation direction of the satellite is positive, the projection of the baseline vector in the positive direction is Equal in magnitude but opposite in direction, we get The first function model with the baseline vector; Obtaining a second function model related to the double-difference carrier phase observation value according to the first function model; The second function model is used to establish a set of equations when two receivers track M satellites simultaneously. After each double-difference integer ambiguity is determined by the LAMBDA algorithm, the value of the baseline vector is obtained.

[0028] In a second aspect, the present invention provides a bridge displacement detection system based on Beidou and 5G AeroMACS positioning, comprising: The first processing module is configured to establish a first carrier pseudorange observation model, obtain the carrier observation value and pseudorange observation value of the frequency signal broadcast by the Beidou satellite through the first carrier pseudorange observation model; process the first carrier pseudorange observation model by combining integer coefficients according to the week to obtain a second carrier pseudorange observation model; The second processing module is configured to traverse the double-difference ionospheric delay and the combined integer ambiguity within a preset coefficient range through the second carrier pseudorange observation model to obtain a five-frequency combination coefficient, and set the most ideal five-frequency combination coefficient. When the five-frequency combination coefficient obtained at this time is the most ideal five-frequency combination coefficient, the optimal solution is obtained; establish a first processing model, and output the first result processed by the first processing model to obtain the optimal solution; use a geometric correlation model to perform a least squares joint solution on the first results of multiple Beidou satellites to obtain three coordinate component values ​​in the pseudorange state; The main control device is connected to the first processing module and the second processing module, and is used to execute the above-mentioned positioning method based on Beidou and 5G AeroMACS.

[0029] The technical solution of the embodiment of the present invention has at least the following advantages and beneficial effects: The method or system provided by the present invention adopts the 5G AeroMACS wireless network for data transmission instead of the traditional 4G / 5G public network, provides a secure and reliable data transmission link and a high-bandwidth and low-latency transmission quality, and can effectively reduce the risk of data leakage generated at the communication link level; adopts an autonomous and controllable single Beidou positioning solution, which can provide a positioning effect with higher accuracy than GPS, and can also effectively reduce the risk of GPS accuracy degradation caused by various factors, and can provide continuous, stable and reliable positioning accuracy. The algorithm provided by the solution can further improve the positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 It is a schematic diagram of the transmission process of the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0033] The terms "first, second" and the like in the specification and claims of this application and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. The naming or numbering of steps in this application does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The named or numbered process steps can be changed in the execution order according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved.

[0034] The modules or submodules described independently may be physically separated or not: they may be implemented by software or hardware, and some modules or submodules may be implemented by software, and the processor may call the software to implement the functions of these modules or submodules, and other modules or submodules may be implemented by hardware, such as by hardware circuits. In addition, some or all of the modules may be selected according to actual needs to achieve the purpose of the present application.

[0035] The DS system, combined with RTK (real-time kinematic positioning) technology, can achieve positioning accuracy up to the millimeter level. When monitoring small structural changes such as bridges, it can capture subtle displacements caused by external forces, temperature changes or long-term loads, providing data support for timely maintenance measures.

[0036] Real-time monitoring and early warning system: By integrating BDS receivers and sensor networks, bridge position and deformation data can be continuously collected and transmitted to the central monitoring platform in real time. Once displacement or abnormal changes exceeding the preset threshold are detected, the system immediately triggers an early warning, allowing airport managers to respond quickly and avoid potential safety accidents.

[0037] Long-term trend analysis and prediction: Using the long-term data collected by BDS, we can analyze the performance change trend of the bridge structure over time and predict major deformation or damage that may occur in the future. This helps to formulate a more scientific and reasonable maintenance plan, extend the service life of the bridge, and reduce maintenance costs.

[0038] Anti-interference design: There are many electromagnetic interference sources in the airport environment, such as radar, communication equipment, etc. The use of anti-interference technology and algorithms designed specifically for BDS monitoring can ensure stable signal reception and high-precision positioning in complex electromagnetic environments, ensuring the reliability and accuracy of monitoring data.

[0039] Integration with smart airport systems: Seamlessly integrate BDS monitoring data into the airport's smart management system and work with other intelligent monitoring modules (such as video surveillance and weather forecast systems) to form a comprehensive, multi-level airport security protection network that can improve the safety and efficiency of overall operations.

[0040] The bridge displacement detection system using Beidou + 5G AeroMACS technology is based on the core technology of the Beidou satellite positioning system independently developed by my country. It is based on key core technologies such as Beidou baseband signal processing, dynamic high-precision positioning, and high-precision algorithms. It can realize real-time monitoring of millimeter-level displacement changes of bridges, and automatically adjust the sampling frequency to automatically collect, transmit, store, and solve and analyze the monitoring data, so as to realize accurate and intelligent early warning, and provide convenient, efficient and fast services for on-site monitoring and remote surveillance.

[0041] The whole detection system consists of one or more BDS monitoring stations, control center, and client, and data is transmitted through the 5G AeroMACS network. Figure 1 As shown. BDS monitoring stations are installed on the top of bridges that need to be monitored, and base stations are installed in areas with stable geological conditions. The satellite signal receiving antennas of BDS monitoring stations and base stations have the characteristics of low power consumption, small size, and can effectively resist the influence of multipath effects. BDS monitoring stations and base stations use solar power supply systems to maintain their continuous power supply. Both BDS monitoring stations and base stations are equipped with 5G AeroMACS communication modules to ensure that the observation data they receive can be sent to the control center through the 5G AeroMACS network. The client is installed on the mobile phones of relevant managers in the form of mobile software. Managers can use the mobile software to set and change the relevant parameters of BDS monitoring stations and base stations within their authority; managers can use the mobile software to view the displacement monitoring of bridges and quickly take corresponding decisions and response measures based on the received warning information.

[0042] The bridge displacement monitoring system based on Beidou + 5G AeroMACS technology established by the present invention usually installs the BDS positioning antenna at the top of the bridge, which can stably and reliably obtain the displacement change information of the structure and grasp its operating status in real time; at the same time, the whole detection system effectively combines daily inspections and regular inspections, and can accurately evaluate the power safety, durability and applicability, understand the safety status of the bridge structure in real time, and promptly warn of its dangerous status and potential threats, thereby playing a role in protecting the safe operation of bridges related to airport operations that are subject to long-term real-time monitoring.

[0043] Please refer to Figure 1 The present invention provides a positioning method based on Beidou and 5G AeroMACS, characterized by comprising: S101: Obtain the frequency signal broadcast by Beidou satellite and transmit it to the data processing end through the 5G AeroMACS network; S102: Establishing a first carrier pseudorange observation model, and obtaining carrier observation values ​​and pseudorange observation values ​​of frequency signals broadcast by Beidou satellites through the first carrier pseudorange observation model; First, the observation value of the frequency signal carrier broadcast by BeiDou-3 is processed using the first carrier pseudorange observation model, taking into account the influence of tropospheric and ionospheric delays: The first carrier pseudorange observation model includes:

[0044] In the formula, is the quadratic difference operator between stations and satellites, The observation frequency is The carrier observation value in units of distance, The observation frequency is The pseudorange observations in distance units, is the station-to-satellite distance, is the tropospheric delay, is the first-order ionospheric delay at the first frequency, For the The ionospheric delay coefficient at each frequency point is is the signal frequency at the first frequency point, For the The signal frequency at the frequency point, For the The wavelength of the electrical carrier signal at a frequency point, For the The integer ambiguity at the frequency point is is the observation noise of the carrier observation, is the observation noise of the pseudorange observation.

[0045] S103: Processing the first carrier pseudorange observation model by combining integer coefficients in cycles to obtain a second carrier pseudorange observation model; Based on the five-frequency case of BDS-3, the above observation equations are substituted by integer coefficients in a week to form the second carrier pseudorange observation model, including:

[0046]

[0047] In the formula, is the combination coefficient, is a natural number, , is the second carrier observation value, is the combined frequency, is the combined wavelength, is the combined ionospheric delay coefficient, is the combined integer ambiguity, is the combined noise amplification factor , The speed of light.

[0048] S104: traverse the double-difference ionospheric delay and the combined integer ambiguity within a preset coefficient range through the second carrier pseudorange observation model to obtain a five-frequency combination coefficient, and set the most ideal five-frequency combination coefficient. When the five-frequency combination coefficient obtained at this time is the most ideal five-frequency combination coefficient, the optimal solution is obtained; The second carrier pseudorange observation model is combined with the long baseline five-frequency ultra-wide lane solution and positioning model to calculate the double difference ionospheric delay. and combined fuzziness exist By traversing the coefficient range, the BDS-3 is obtained in the five-frequency combination coefficient (1,-1,0,0,0) ambiguity / week, (0,0,-1,1,0) ambiguity / week, (0,0,0,-1,1) ambiguity / week, and the optimal solution can be obtained when the five-frequency combination coefficient is (0,1,-1,0,0) ambiguity / week.

[0049] S105: Establishing a first processing model, and outputting a first result after processing the obtained optimal solution through the first processing model; The above-mentioned optimal solutions are combined with pseudoranges and solved using the first processing model:

[0050] In the formula, is the pseudorange, To solve for the value, is the random error of ambiguity caused by observation noise.

[0051] S106: The first results of multiple Beidou satellites are jointly solved by least squares using a geometric correlation model to obtain three coordinate component values ​​in a pseudorange state.

[0052] The double-difference observation equations of multiple satellite pairs, that is, the pseudorange and ambiguity fixed ultra-wide lane equations in the above formula are combined, and the least squares joint solution is performed using the geometric correlation model to obtain the pseudorange state. The three coordinate component values ​​of . At this time, the coordinate accuracy value can reach decimeter-level positioning accuracy.

[0053] An exemplary embodiment of the present invention further includes: S201: Establishing a second processing model, processing the obtained three coordinate component values ​​by the second processing model to output a second result; After obtaining the x, y, and z coordinate values ​​of a single receiver with decimeter-level positioning accuracy, the pseudo-range coordinate values ​​of multiple receivers deployed around the bridge are transmitted back to the backend server through the 5G AeroMACS network. The coordinate position data is subjected to secondary processing through a second processing model.

[0054] The second processing model includes:

[0055] In the formula, Uploaded to the receiver The satellite's pseudorange observations, For the The geometric distance between the satellite and the receiver, For the The first observation parameter of the receiver, For the The satellite's second observation parameter, For the The third observation parameter of the satellite, For the The fourth observation parameter of the satellite, For the The fifth observation parameter of the satellite, The first The satellite's carrier phase observations, To observe the The satellite's integer ambiguity, is the carrier wavelength, is the signal frequency.

[0056] Among them, the first observation value parameter, the second observation value parameter, the third observation value parameter, the fourth observation value parameter and the fifth observation value parameter will all be eliminated in the subsequent calculation process.

[0057] S202: Establishing a first single-difference carrier phase observation model through the second result, obtaining the difference of the carrier phase observation values ​​of the two receivers for the same satellite, substituting it into the first single-difference carrier phase observation model as the single-difference carrier phase observation value, eliminating various error parameters through differential combination, and obtaining a second single-difference carrier phase observation model; Establishing the first single-difference carrier phase observation model includes:

[0058]

[0059]

[0060] In the formula, For the two receivers The difference in the satellite's carrier phase observations, The first The satellite's carrier phase observations, The first The satellite's carrier phase observations, The base station receiver and The distance of the satellite, is the first observation parameter of the base station receiver, , , They are the base station receiver relative to The third observation value parameter, the fourth observation value parameter, and the fifth observation value parameter of the satellite, The mobile station receiver observes The satellite's integer ambiguity, For the mobile station receiver and the The distance of the satellite, is the first observation parameter of the mobile station receiver, , , They are the relative position of the mobile station receiver to the The third observation value parameter, the fourth observation value parameter, and the fifth observation value parameter of the satellite, The mobile station receiver observes The satellite's integer ambiguity.

[0061] Based on the fact that the baseline length between the mobile station and the base station is short and the height is the same during bridge monitoring, it can be assumed that the receiver is affected by the delay of the ionosphere and the troposphere in the same way. and Further elimination yields: .

[0062] The second single-difference carrier phase observation model includes:

[0063]

[0064]

[0065]

[0066] In the formula, For the two receivers The difference in the satellite's carrier phase observations, For the The single-difference distance to the satellite, is the single-difference first observation parameter, For the The single-difference integer ambiguity of the satellite, For the The single-difference fifth observation parameter of the satellite, For the The single-difference distance to the satellite, No. The single-difference integer ambiguity of the satellite, is the single-difference fifth observation parameter.

[0067] S203: Processing through two different second single-difference carrier phase observation models obtains a double-difference carrier phase observation model, outputs a double-difference carrier phase observation value through the double-difference carrier phase observation model, and combines the double-difference carrier phase observation value with the baseline vector to obtain the positioning information of the receiver.

[0068] The double-difference carrier phase observation model includes:

[0069]

[0070] In the formula, is the double-difference carrier phase observation value, is the double difference distance, is the double difference integer ambiguity, is the double-difference fifth observation parameter.

[0071] In an exemplary embodiment of the present invention, the double-difference carrier phase observation value is combined with the baseline vector to obtain the positioning information of the receiver, including: S301: According to the observation direction of the receiver to the satellite is positive, the projection of the baseline vector in the positive direction is Equal in magnitude but opposite in direction, we get The first function model with the baseline vector; In the scenario of bridge displacement monitoring described in the present invention, the distance between the receiver and the observation satellite is much greater than the distance between the mobile station and the reference station. In this case, the observation vectors of the mobile station and the reference station for the same observation satellite appear to be parallel. Then the distance vector The trigonometric relationship can be used to establish a relationship with the baseline vector. Taking the receiver's observation direction of the satellite as positive, the projection of the baseline vector in the positive direction is The magnitude is equal but the direction is opposite, and we can get the first function model: as well as ,in, is the baseline vector, Relative to the The calculation coefficients of the satellite, Relative to the Calculation coefficients for satellites.

[0072] S302: Obtaining a second function model related to the double-difference carrier phase observation value according to the first function model; Using the above results, build the double difference distance With baseline vector The mathematical relationship between , we get: , so the baseline vector can be obtained With double difference measurement The second function model between is: .

[0073] S303: A set of equations is established through the second function model when the two receivers simultaneously track M satellites, and after each double-difference integer ambiguity is determined through the LAMBDA algorithm, the value of the baseline vector is obtained.

[0074] Finally, when the receiver tracks M satellites simultaneously, (M-1) double-difference carrier phase equations can be used as follows:

[0075] In the formula, For the Satellite and The double-difference carrier phase observations of the satellite, Relative to the The calculation coefficients of the satellite, Relative to the The calculation coefficients of the satellite, For the Satellite and The double-difference integer ambiguity of the satellite, For the Satellite and Double-difference fifth observation parameters of the satellite.

[0076] The above method can achieve the final result required for bridge displacement detection with centimeter to millimeter level accuracy, and realize continuous monitoring of bridge displacement and subsequent early warning processing.

[0077] The present invention also provides a bridge displacement detection system based on Beidou and 5G AeroMACS positioning, comprising: The first processing module is configured to establish a first carrier pseudorange observation model, obtain the carrier observation value and pseudorange observation value of the frequency signal broadcast by the Beidou satellite through the first carrier pseudorange observation model; process the first carrier pseudorange observation model by combining integer coefficients according to the week to obtain a second carrier pseudorange observation model; The second processing module is configured to traverse the double-difference ionospheric delay and the combined integer ambiguity within a preset coefficient range through the second carrier pseudorange observation model to obtain a five-frequency combination coefficient, and set the most ideal five-frequency combination coefficient. When the five-frequency combination coefficient obtained at this time is the most ideal five-frequency combination coefficient, the optimal solution is obtained; establish a first processing model, and output the first result processed by the first processing model to obtain the optimal solution; use a geometric correlation model to perform a least squares joint solution on the first results of multiple Beidou satellites to obtain three coordinate component values ​​in the pseudorange state; A main control device is connected to the first processing module and the second processing module, and is used to execute the positioning method based on Beidou and 5G AeroMACS as mentioned in the claim.

[0078] The precise positioning technology in the present invention uses Beidou satellite carrier phase difference measurement technology to perform precise displacement monitoring. A BDS satellite receiver is placed at each monitoring point to perform uninterrupted all-weather automatic monitoring. Compared with conventional monitoring methods, Beidou satellite carrier phase difference measurement technology provides: There is no need for line of sight between the measuring stations, only an open space above the measuring stations is required. The monitoring points can be arranged flexibly and conveniently, which can reduce unnecessary intermediate transition points. It can simultaneously provide three-dimensional displacement information of monitoring points with high detection accuracy; Beidou satellite measurement technology is not restricted by climatic conditions. After being equipped with lightning protection facilities, it can achieve all-weather observation; It is easy to operate and can easily realize highly automated detection, greatly reducing the intensity of field work.

[0079] The main components of the equipment involved in the present invention are: 1. Data acquisition system The data acquisition system consists of BDS satellite signal receivers (including monitoring stations and base stations) and other monitoring sensors. The BDS satellite signal receiver uses a high-precision system based on Beidou satellite single-mode positioning signals, and uses a large terrain choke antenna that can effectively suppress the impact of multipath effects. Combined with a stable phase center (less than 0.8 mm), it can also suppress radio frequency interference to ensure that the system is safer and more reliable; the remaining monitoring sensors use advanced monitoring technology and equipment to monitor targets in real time.

[0080] 2. Data transmission system In order to ensure the smooth and stable positioning observation data, ensure the normal operation of the system and the accuracy of data solution, the 5G AeroMACS communication network is used for data transmission in the solution of the present invention. The BDS receiver integrates a 5G AeroMACS network module, which can be connected to the 5G AeroMACS network built at the airport, providing a high-bandwidth and low-latency communication network foundation, which can effectively guarantee the bandwidth and quality of data communication between the data acquisition end and the control center, and can also provide sufficient bandwidth reserves for system expansion, and facilitate the networking of the monitoring system.

[0081] 3. Data processing (control) center system It is composed of the monitoring center's server system, monitoring software and database, and is the heart of the entire system. It is responsible for analyzing and solving the original observation data generated by the receiver monitoring, improving the positioning accuracy to the millimeter level, so as to detect slight changes in the bridge displacement and promptly alert the client when the displacement threshold is reached according to the bridge displacement risk model.

[0082] 4. Auxiliary support system It consists of an outdoor cabinet or chassis, a distribution box and UPS, lightning protection and remote power monitoring, alarm devices and printing equipment.

[0083] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0084] 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. The computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0085] This solution integrates the bridge displacement detection system of BDS positioning technology and 5G AeroMACS communication technology, and follows the "China Civil Aviation New Generation Aviation Broadband Communication Technology Roadmap". It can not only meet the current safety supervision requirements, but also proactively adapt to the technical needs of future airport development, ensuring the advancement and sustainability of the bridge safety monitoring system. Under the increasingly stringent requirements for airport operations, high-precision, real-time displacement monitoring of bridges is not only an upgrade of traditional maintenance methods, but also an indispensable part of smart airport construction. By integrating advanced technologies such as 5G AeroMACS, dynamic monitoring and intelligent analysis of the health status of bridges can be achieved, potential risks can be effectively prevented, and the safe and smooth operation of airports in various complex situations can be ensured, setting an example for the efficiency and safety of the global aviation industry.

[0086] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A positioning method based on Beidou and 5G AeroMACS, characterized in that: include: Obtain frequency signals broadcast by Beidou satellites and transmit them to the data processing end through the 5G AeroMACS network; Establish a first carrier pseudorange observation model at the data processing end, and obtain the carrier observation value and pseudorange observation value of the frequency signal broadcast by the Beidou satellite through the first carrier pseudorange observation model; The first carrier pseudorange observation model is processed by combining integer coefficients in cycles to obtain a second carrier pseudorange observation model; The double-difference ionospheric delay and the combined integer ambiguity are traversed within a preset coefficient range through the second carrier pseudorange observation model to obtain the five-frequency combination coefficient, and the most ideal five-frequency combination coefficient is set. When the five-frequency combination coefficient obtained at this time is the most ideal five-frequency combination coefficient, the optimal solution is obtained; Establishing a first processing model, and outputting a first result after processing the obtained optimal solution through the first processing model; The first results of multiple Beidou satellites are jointly solved by least squares using a geometric correlation model to obtain the three coordinate component values ​​in the pseudorange state.

2. The positioning method based on Beidou and 5G AeroMACS according to claim 1, characterized in that: Also includes: Establishing a second processing model, processing the obtained three coordinate component values ​​through the second processing model to output a second result; A first single-difference carrier phase observation model is established through the second result, the difference of the carrier phase observation values ​​of the two receivers for the same satellite is obtained, and the difference is substituted into the first single-difference carrier phase observation model as the single-difference carrier phase observation value, and various error parameters are eliminated through differential combination to obtain a second single-difference carrier phase observation model; A double-difference carrier phase observation model is obtained by processing two different second single-difference carrier phase observation models, and a double-difference carrier phase observation value is output through the double-difference carrier phase observation model. The double-difference carrier phase observation value is combined with the baseline vector to obtain the positioning information of the receiver.

3. The positioning method based on Beidou and 5G AeroMACS according to claim 2, characterized in that: The establishing of the first carrier pseudorange observation model comprises: In the formula, is the quadratic difference operator between stations and satellites, The observation frequency is The carrier observation value in units of distance, The observation frequency is The pseudorange observations in distance units, is the station-to-satellite distance, is the tropospheric delay, is the first-order ionospheric delay at the first frequency, For the The ionospheric delay coefficient at each frequency point is is the signal frequency at the first frequency point, For the The signal frequency at the frequency point, For the The wavelength of the electrical carrier signal at a frequency point, For the The integer ambiguity at the frequency point is is the observation noise of the carrier observation, is the observation noise of the pseudorange observation.

4. The positioning method based on Beidou and 5G AeroMACS according to claim 3, characterized in that: The second carrier pseudorange observation model includes: In the formula, is the combination coefficient, is a natural number, , is the second carrier observation value, is the combined frequency, is the combined wavelength, is the combined ionospheric delay coefficient, is the combined integer ambiguity, is the combined noise amplification factor , The speed of light.

5. The positioning method based on Beidou and 5G AeroMACS according to claim 4, characterized in that: The establishing of the first processing model comprises: In the formula, is the pseudorange, To solve for the value, It is the random error of ambiguity caused by observation noise.

6. The positioning method based on Beidou and 5G AeroMACS according to claim 5, characterized in that: The second processing model includes: In the formula, Uploaded to the receiver The satellite's pseudorange observations, For the The geometric distance between the satellite and the receiver, For the The first observation parameter of the receiver, For the The satellite's second observation parameter, For the The third observation parameter of the satellite, For the The fourth observation parameter of the satellite, For the The fifth observation parameter of the satellite, The first The satellite's carrier phase observations, To observe the The satellite's integer ambiguity, is the carrier wavelength, is the signal frequency.

7. The positioning method based on Beidou and 5G AeroMACS according to claim 6, characterized in that: The establishing of the first single-difference carrier phase observation model comprises: In the formula, For the two receivers The difference in the satellite's carrier phase observations, The first The satellite's carrier phase observations, The first The satellite's carrier phase observations, The base station receiver and The distance of the satellite, is the first observation parameter of the base station receiver, , , They are the base station receiver relative to The third observation value parameter, the fourth observation value parameter, and the fifth observation value parameter of the satellite, The mobile station receiver observes The satellite's integer ambiguity, For the mobile station receiver and the The distance of the satellite, is the first observation parameter of the mobile station receiver, , , They are the relative The third observation value parameter, the fourth observation value parameter, and the fifth observation value parameter of the satellite, The mobile station receiver observes The satellite's integer ambiguity.

8. The positioning method based on Beidou and 5G AeroMACS according to claim 7, characterized in that: The second single-difference carrier phase observation model includes: In the formula, For the two receivers The difference in the satellite's carrier phase observations, For the The single-difference distance to the satellite, is the single-difference first observation parameter, For the The single-difference integer ambiguity of the satellite, For the The single-difference fifth observation parameter of the satellite, For the The single-difference distance to the satellite, No. The single-difference integer ambiguity of the satellite, For the Single-difference fifth observation parameters of the satellite; The double-difference carrier phase observation model includes: In the formula, is the double-difference carrier phase observation value, is the double difference distance, is the double-difference integer ambiguity, is the double-difference fifth observation parameter.

9. The positioning method based on Beidou and 5G AeroMACS according to claim 8, characterized in that: The step of combining the double-difference carrier phase observation value with the baseline vector to obtain the positioning information of the receiver includes: According to the receiver's observation direction of the satellite is positive, the projection of the baseline vector in the positive direction is Equal in magnitude but opposite in direction, we get The first function model with the baseline vector; Obtaining a second function model related to the double-difference carrier phase observation value according to the first function model; The second function model is used to establish a set of equations when two receivers track M satellites simultaneously. After each double-difference integer ambiguity is determined by the LAMBDA algorithm, the value of the baseline vector is obtained.

10. A positioning system based on Beidou and 5G AeroMACS, characterized in that: include The first processing module is configured to establish a first carrier pseudorange observation model, obtain the carrier observation value and pseudorange observation value of the frequency signal broadcast by the Beidou satellite through the first carrier pseudorange observation model; process the first carrier pseudorange observation model by combining integer coefficients according to the week to obtain a second carrier pseudorange observation model; The second processing module is configured to traverse the double-difference ionospheric delay and the combined integer ambiguity within a preset coefficient range through the second carrier pseudorange observation model to obtain a five-frequency combination coefficient, and set the most ideal five-frequency combination coefficient. When the five-frequency combination coefficient obtained at this time is the most ideal five-frequency combination coefficient, the optimal solution is obtained; A first processing model is established, and the obtained optimal solution is output through the first processing model to obtain a first result after processing; the first results of multiple Beidou satellites are jointly solved by least squares using a geometric correlation model to obtain three coordinate component values ​​in a pseudorange state; A main control device, connected to the first processing module and the second processing module, is used to execute a positioning method based on Beidou and 5G AeroMACS as described in any one of claims 1-9.

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