5g+beidou integrated enhanced positioning method and outdoor multi-mode switching method and device

Abstract

The application provides a 5G+Beidou fusion enhanced positioning method, an outdoor multi-mode switching method and device, which comprises the following steps: detecting the shielding condition of the outdoor environment of a user according to the Beidou positioning accuracy value and the 5G positioning accuracy value at the current time; based on the detected shielding condition of the outdoor environment, corresponding positioning modes are executed; specifically, in the case of local shielding of the outdoor environment, a 5G+Beidou fusion enhanced positioning mode is adopted to obtain a 5G+Beidou fusion enhanced positioning result. The application adopts a federal Kalman filter and introduces a fault self-checking function, so that error data can be shielded, a higher-precision position information is obtained by setting an information distribution factor in the main filter; the application comprehensively considers factors such as the number of satellites and positioning accuracy requirements, sets mode switching conditions, avoids positioning jumps and repeated invalid positioning switching, saves computing resources, improves the reliability of outdoor positioning, and realizes reasonable and seamless switching of positioning modes.

Description

Technical Field

[0001] This invention relates to the field of navigation and positioning technology, and in particular to a 5G+BeiDou multi-mode fusion enhanced positioning method, outdoor multi-mode switching method and device for outdoor scenarios. Background Technology

[0002] For mobile terminal positioning in outdoor environments, either BeiDou positioning mode or 5G positioning mode can be used.

[0003] However, the outdoor environment has complex obstruction situations. Under different obstruction conditions, there are intermediate areas where both 5G positioning signals and BeiDou positioning signals can be received. When a user may be running in an outdoor area with severe obstruction, the BeiDou positioning system is basically ineffective. If the BeiDou satellite is still used for positioning, the positioning results will drift and cannot achieve the required high positioning accuracy.

[0004] Seamless positioning technology refers to the ability of a terminal device to select the optimal positioning method from multiple positioning schemes based on the characteristics of its environment during movement in complex environments, ensuring positioning accuracy. Furthermore, when switching positioning methods outdoors, seamless transitions and smooth, stable operation are required, ultimately achieving full coverage and high-precision positioning for mobile terminal users in outdoor scenarios. However, in reality, the positioning accuracy of the BeiDou positioning method is not solely dependent on the number of available satellites. If only the number of available satellites is used as a condition for positioning switching, and the switching is executed directly, the requirements for fast and accurate switching cannot be met, and stable, high-precision positioning services cannot be obtained. Summary of the Invention

[0005] This invention provides a 5G+BeiDou fusion enhanced positioning method, an outdoor multi-mode switching method and device for outdoor scenarios, to solve the problem that existing technologies cannot quickly and accurately switch positioning modes, making it difficult for mobile terminals to obtain high-precision positioning services in complex outdoor scenarios.

[0006] The 5G+BeiDou fusion enhanced positioning method for outdoor scenarios provided by this invention includes:

[0007] BeiDou positioning data is obtained using a BeiDou RTK positioning method based on an integer ambiguity fixed algorithm.

[0008] A high-precision OTDOA positioning method based on 5G ultra-dense networking is used to acquire 5G positioning data.

[0009] The acquired BeiDou positioning data and 5G positioning data are respectively input into the BeiDou local filter and the 5G local filter for filtering, and fault self-checks are performed respectively. The fault self-checks are used to filter out invalid positioning information acquired due to obstruction by obstacles.

[0010] The BeiDou positioning data and 5G positioning data after self-testing are respectively input into the main filter BeiDou data processing channel and 5G data processing channel. Information is fused according to the information allocation factor to obtain the 5G+BeiDou fusion enhanced positioning result. The main filter BeiDou data processing channel and 5G data processing channel are respectively set with information allocation factors, which are preset according to the number of available satellites and positioning accuracy requirements.

[0011] According to the 5G+BeiDou fusion enhanced positioning method for outdoor scenarios provided by the present invention, the BeiDou local filter, the 5G local filter, and the main filter are all federated Kalman filters.

[0012] According to the 5G+BeiDou fusion enhanced positioning method for outdoor scenarios provided by the present invention, the BeiDou RTK positioning method based on the integer ambiguity fixing algorithm specifically includes:

[0013] S31. Calculate the floating-point solution of the position coordinates of each epoch and the floating-point solution of all single-difference integer ambiguities using the EKF recursive formula;

[0014] S32. Convert the single-difference integer ambiguity floating-point solution into a double-difference integer ambiguity floating-point solution;

[0015] S33. Based on the LAMBDA algorithm, fix the double-difference integer ambiguity. If the Ratio value is not less than the predetermined threshold, use a specific correction formula to correct the floating-point solution of the position coordinates and output the fixed solution of the position coordinates. The positioning of this epoch ends; otherwise, go to step S34.

[0016] S34. Delete the ambiguity with the largest variance value in the set of ambiguities to be fixed in step S33. If the number of remaining ambiguities to be fixed is not less than the sum of the dimensions of the coordinate vector and velocity vector of the terminal device in the geocentric coordinate system, go to step S33; otherwise, output the floating-point solution of the position coordinates and the positioning of this epoch ends.

[0017] According to the 5G+BeiDou fusion enhanced positioning method for outdoor scenarios provided by the present invention, the OTDOA high-precision positioning method based on 5G ultra-dense networking includes:

[0018] S41: Set a specific threshold for all measured TOA values, and perform preliminary screening on the TOA values ​​within the threshold, deleting TOA values ​​that have obvious errors. Let N be the TOA measurement values ​​after preliminary screening and the number of corresponding base stations.

[0019] S42: Select a specific number of TOA values ​​from the N TOA measurement values ​​after initial screening, randomly select a reference base station, calculate the TDOA value, and substitute them into the OTDOA algorithm to obtain the corresponding estimated location;

[0020] S43: For all estimated locations obtained in step S52, perform clustering using the K-means clustering algorithm. Assume there are M categories, and count the number of estimated locations in each category, where M... max This represents the class with the highest estimated number, and the statistic M is... max The system is used to calculate the estimated TOA value and the corresponding base station; the statistical results are sorted from largest to smallest according to the number of uses, the top K TOA values ​​and the corresponding base stations are taken, and reference base stations are reselected to obtain the filtered K-1 TDOA values;

[0021] S44: Using the filtered K-1 TDOA values ​​and the corresponding base station locations, re-evaluate the location according to the basic algorithm to obtain the optimized location estimation result.

[0022] The present invention also provides an outdoor multi-mode switching method, comprising:

[0023] Based on the current BeiDou positioning accuracy GDOP value and the 5G positioning accuracy P value... 5G The value detects the occlusion status of the user's outdoor environment, which includes unobstructed, partially obstructed, and completely obstructed environments;

[0024] Based on the detected outdoor environmental obstructions, the corresponding positioning mode is executed, specifically including:

[0025] When the user's outdoor environment is unobstructed, the BeiDou positioning mode is used for positioning.

[0026] When the outdoor environment where the user is located is partially obstructed, the above-described 5G+BeiDou fusion enhanced positioning method is used.

[0027] When the outdoor environment where the user is located is completely obstructed, the 5G positioning mode is used for positioning.

[0028] According to the outdoor multi-mode handover method provided by the present invention, based on the current BeiDou positioning accuracy GDOP value and the 5G positioning accuracy P value, 5G The value detects the obstruction of the user's outdoor environment. The determination of no obstruction specifically includes:

[0029] When the BeiDou positioning accuracy GDOP is less than the first threshold at the current moment, the count value at the current moment is multiplied by the reduction rate to obtain the first judgment value, and it is determined whether the first judgment value is less than the count threshold.

[0030] If the first determination value is not less than the counting threshold, then the BeiDou positioning accuracy GDOP value and the 5G positioning accuracy P value at the current time are used again. 5G The value detects the degree of obstruction in the user's outdoor environment;

[0031] If the first determination value is less than the counting threshold, it is determined to be unobstructed;

[0032] The first threshold is preset, and the counting threshold is preset according to different application scenarios.

[0033] According to the outdoor multi-mode handover method provided by the present invention, based on the current BeiDou positioning accuracy GDOP value and the 5G positioning accuracy P value, 5G The value detects the occlusion of the user's outdoor environment. The determination of the local occlusion specifically includes:

[0034] Monitoring the current BeiDou positioning accuracy (GDOP) and 5G positioning accuracy, if the current BeiDou positioning accuracy (GDOP) is greater than the first threshold and less than the second threshold, and the 5G positioning accuracy (P) is... 5G When the value is greater than the third threshold and less than the fourth threshold, the count is accumulated to obtain the count value at the current time, and it is determined whether the count value at the current time is greater than the counting threshold.

[0035] If the current count value is determined to be no greater than the count threshold, then the BeiDou positioning accuracy (GDOP) and 5G positioning accuracy at the current time will continue to be monitored.

[0036] If the current count value is greater than the count threshold, the occlusion is determined to be partial occlusion.

[0037] The first threshold, second threshold, third threshold, and fourth threshold are preset, with the first threshold being less than the second threshold and the third threshold being less than the fourth threshold; the initial value of the count value is 1, and the count threshold is preset according to different application scenarios.

[0038] According to the outdoor multi-mode handover method provided by the present invention, based on the current BeiDou positioning accuracy GDOP value and the 5G positioning accuracy P value, 5G The value detects the occlusion status of the user's outdoor environment. The determination of total occlusion specifically includes:

[0039] At the current moment, the BeiDou positioning accuracy (GDOP) is greater than the second threshold, while the 5G positioning accuracy (P) is... 5G When the count value is less than the third threshold, the count value at the current time is multiplied by the reduction rate to obtain the second judgment value, and it is determined whether the second judgment value is less than the count threshold.

[0040] If the second determination value is not less than the counting threshold, the occlusion determination step is executed again.

[0041] If the second determination value is less than the counting threshold, it is determined to be a full occlusion.

[0042] The first threshold, second threshold, third threshold, and fourth threshold are preset, with the first threshold being less than the second threshold and the third threshold being less than the fourth threshold; the initial value of the count value is 1, and different processing is applied according to different occlusion conditions; the count threshold is preset according to different application scenarios; the reduction rate is preset according to the sensor frequency of the positioning system used, and is within the range of 0 to 1.

[0043] This invention also provides a 5G+BeiDou fusion enhanced positioning device for outdoor scenarios, comprising:

[0044] Acquisition module: Used to acquire BeiDou high-precision positioning data using the BeiDou RTK positioning method based on integer ambiguity fixed algorithm;

[0045] The acquisition module is also used to acquire 5G high-precision positioning data using the OTDOA high-precision positioning method based on 5G ultra-dense networking.

[0046] Filtering module: It is used to input the acquired BeiDou positioning data and 5G positioning data into the BeiDou local filter and 5G local filter respectively for filtering, and to perform fault self-checks respectively. The fault self-checks are used to filter out invalid positioning information acquired due to obstruction.

[0047] Fusion positioning module: It is used to input the BeiDou positioning data and 5G positioning data after self-testing into the main filter BeiDou data processing channel and 5G data processing channel respectively, and perform information fusion according to the information allocation factor to obtain the 5G+BeiDou fusion enhanced positioning result. The main filter BeiDou data processing channel and 5G data processing channel are respectively set with information allocation factors, which are preset according to the number of available satellites and positioning accuracy requirements.

[0048] According to the 5G+BeiDou fusion enhanced positioning device for outdoor scenarios provided by the present invention, the filtering module includes:

[0049] The Federal Kalman filter is used to input the BeiDou high-precision positioning data and 5G high-precision positioning data acquired by the acquisition module into the Federal Kalman filter for filtering, and to perform fault self-check. The fault self-check is used to filter out invalid positioning information acquired due to obstruction.

[0050] The present invention also provides an outdoor multi-mode switching device, comprising:

[0051] The occlusion determination module is used to determine the occlusion based on the current BeiDou positioning accuracy (GDOP) and the 5G positioning accuracy (P). 5G The value detects the occlusion status of the user's outdoor environment, which includes unobstructed, partially obstructed, and completely obstructed environments;

[0052] The positioning mode switching module is used to execute the corresponding positioning mode based on the detected outdoor environmental obstruction, specifically including:

[0053] When the user's outdoor environment is unobstructed, the BeiDou positioning mode is used for positioning.

[0054] When the outdoor environment where the user is located is partially obstructed, the 5G+BeiDou fusion enhanced positioning mode is adopted. The 5G+BeiDou fusion enhanced positioning mode is realized by the 5G+BeiDou fusion enhanced positioning device mentioned above.

[0055] When the outdoor environment where the user is located is completely obstructed, the 5G positioning mode is used for positioning.

[0056] According to the outdoor multi-mode switching device provided by the present invention, the positioning mode switching module further includes a BeiDou local filter, a 5G local filter, a detection module, and a main filter.

[0057] The BeiDou local filter is used to process BeiDou RTK positioning data.

[0058] The 5G local filter is used to process 5G ultra-dense network OTDOA positioning data.

[0059] The detection module is used to detect local filters;

[0060] The main filter is used to input the BeiDou RTK positioning data and 5G ultra-dense network OTDOA positioning data, which have been processed by the local filter, into the main filter to complete the data fusion.

[0061] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the 5G+BeiDou fusion enhanced positioning method for outdoor scenarios or the outdoor multi-mode switching method as described above.

[0062] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the 5G+BeiDou fusion enhanced positioning method for outdoor scenarios or the outdoor multi-mode switching method as described above.

[0063] This invention provides a 5G+BeiDou fusion-enhanced positioning method, an outdoor multi-mode switching method, and a device for outdoor scenarios. Addressing the challenge of mobile terminals obtaining high-precision location services in complex outdoor environments, this invention employs an outdoor positioning switching algorithm based on a threshold mechanism and multi-sensor positioning accuracy. It utilizes the real-time positioning accuracy of sensors to determine the confidence level of each sensor system, achieving full fusion of BeiDou and 5G positioning systems within the switching area. This avoids positioning jumps and the significant computational waste caused by the ping-pong effect resulting from repeated ineffective positioning switching in critical areas. Furthermore, this invention improves upon both BeiDou and 5G positioning modes, inputting the positioning data from both modes into a federated Kalman filter and performing fault self-checks to filter out erroneous data. Finally, by setting an information allocation factor in the main filter, higher-precision location information is obtained through fusion, achieving optimal selection of the terminal positioning scheme in outdoor scenarios. This ensures that mobile terminals can still obtain high-precision location information even in obstructed outdoor conditions, effectively improving the reliability of outdoor positioning. Attached Figure Description

[0064] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0065] Figure 1 A flowchart illustrating a 5G+BeiDou fusion enhanced positioning method for outdoor scenarios provided in an embodiment of the present invention;

[0066] Figure 2 A flowchart of a BeiDou RTK positioning method based on an integer ambiguity fixing algorithm provided in an embodiment of the present invention;

[0067] Figure 3 This is a schematic diagram of a 5G TDOA positioning technology provided in an embodiment of the present invention;

[0068] Figure 4 A flowchart of an OTDOA high-precision positioning algorithm based on 5G ultra-dense networking is provided for an embodiment of the present invention;

[0069] Figure 5 This invention provides a model of a 5G+BeiDou fusion enhanced positioning system.

[0070] Figure 6 A flowchart of an outdoor multimode switching method provided in an embodiment of the present invention;

[0071] Figure 7An outdoor multi-mode switching strategy provided in an embodiment of the present invention;

[0072] Figure 8 This is a multi-mode fusion positioning implementation scheme under the outdoor multi-mode switching strategy provided in the embodiments of the present invention;

[0073] Figure 9 A schematic diagram of the structure of a 5G+BeiDou fusion enhanced positioning device for outdoor scenarios provided in an embodiment of the present invention;

[0074] Figure 10 This is a schematic diagram of the structure of the outdoor multimode switching device provided in an embodiment of the present invention;

[0075] Figure 11 This is a schematic diagram of the physical structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0076] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0077] The BeiDou system uses Global Navigation Satellite System (GNSS) technology and mainly consists of three parts: satellites, ground control, and user terminals. The BeiDou system's satellites are primarily composed of networking satellites and backup satellites. Through multi-satellite networking, it can provide global navigation services. The ground control system is mainly responsible for satellite control, navigation data processing, and transmission. User terminals include vehicle-mounted terminals, handheld terminals, and ship terminals, which can receive BeiDou navigation signals and perform positioning, navigation, and other operations.

[0078] With the evolution and development of 5G mobile communication technology, 5G positioning based on cellular networks is also being applied to vertical industries and civilian location services. Compared with traditional satellite navigation systems, 5G positioning technology has advantages such as higher accuracy, lower latency, and wider coverage. 5G positioning technology mainly relies on the signal transmission and processing capabilities of the 5G network, using multipath signal transmission and beamforming techniques to achieve the positioning and tracking of mobile terminals. Under the 5G network, through signal measurement and collaborative processing from multiple base stations, three-dimensional and high-precision positioning of mobile terminals can be achieved. 5G positioning technology has broad application prospects in fields such as intelligent transportation, the Internet of Things (IoT), precision agriculture, and precision medicine. For example, in the field of intelligent transportation, 5G positioning technology can provide vehicles with more accurate location information and road condition information, enabling intelligent driving and intelligent traffic control; in the IoT field, 5G positioning technology can enable real-time monitoring and management of IoT devices, improving the intelligence level of the IoT; in the field of precision medicine, 5G positioning technology provides medical institutions with more accurate location information and real-time monitoring data, improving the quality and efficiency of medical services.

[0079] In outdoor scenarios, there are areas where both 5G and BeiDou positioning signals can be received. In such cases, using a single positioning mode will not provide a stable and accurate positioning service. When a user moves from the service area of ​​one positioning system to an intermediate area and receives a signal from another positioning system, directly switching positioning will result in a positioning outcome that contradicts the requirement for seamless, smooth, and stable service.

[0080] To address the aforementioned issues, this invention provides a 5G+BeiDou fusion-enhanced positioning method, an outdoor multi-mode switching method, and a device for outdoor scenarios. It considers two modes in outdoor scenarios: BeiDou Real-time Kinematic (RTK) positioning and 5G Observed Time Difference of Arrival (OTDOA) positioning. In outdoor scenarios, by comprehensively considering factors such as the number of satellites and positioning accuracy requirements, it achieves reasonable and seamless switching between BeiDou RTK positioning, 5G OTDOA positioning, and the 5G+BeiDou fusion-enhanced positioning mode based on the federated Kalman filter algorithm. In outdoor scenarios, it employs a multi-mode positioning scheme combining BeiDou and 5G. When only BeiDou is effective, it executes the BeiDou RTK positioning mode; when satellites are obstructed and only 5G positioning is effective, it executes the 5G OTDOA positioning mode; and when both BeiDou and 5G are effective, it executes the 5G+BeiDou fusion-enhanced positioning mode based on the Kalman filter algorithm. This effectively improves the reliability of mobile terminal positioning services in outdoor environments with obstructions and other environmental degradation.

[0081] To reduce terminal positioning errors, a 5G+BeiDou fusion positioning enhancement mode based on the federated Kalman filter algorithm was designed when both modes coexist. This was achieved by improving the BeiDou RTK algorithm to a BeiDou RTK positioning method based on a fixed integer ambiguity algorithm, and improving the 5G OTDOA algorithm to an OTDOA high-precision positioning method based on 5G ultra-dense networking. At the same time, a fault self-checking mechanism was adopted to effectively reduce the degree of data pollution while improving positioning accuracy.

[0082] The 5G+BeiDou fusion enhanced positioning method for outdoor scenarios provided in this invention can be applied to outdoor scenarios with complex obstructions.

[0083] The following is combined Figures 1-5 This invention describes a 5G+BeiDou fusion-enhanced positioning method for outdoor scenarios.

[0084] Figure 1 A flowchart of a 5G+BeiDou fusion enhanced positioning method for outdoor scenarios is provided in this embodiment of the invention, as shown below. Figure 1 As shown, the method includes:

[0085] Step 101: Obtain BeiDou positioning data using the BeiDou RTK positioning method based on integer ambiguity fixing algorithm;

[0086] Step 102: Obtain 5G positioning data using the OTDOA high-precision positioning method based on 5G ultra-dense networking;

[0087] Step 103: Input the acquired BeiDou positioning data and 5G positioning data into the BeiDou local filter and 5G local filter respectively for filtering, and perform fault self-check. The fault self-check is used to filter out invalid positioning information acquired due to obstruction by obstacles.

[0088] Step 104: Input the BeiDou positioning data and 5G positioning data after self-testing into the main filter BeiDou data processing channel and 5G data processing channel respectively. Perform information fusion according to the information allocation factor to obtain the 5G+BeiDou fusion enhanced positioning result. The main filter BeiDou data processing channel and 5G data processing channel are respectively set with information allocation factors. The information allocation factors are preset according to the number of available satellites and positioning accuracy requirements.

[0089] The above steps will be explained in detail below with reference to specific embodiments.

[0090] Step 101: Obtain BeiDou positioning data using the BeiDou RTK positioning method based on integer ambiguity fixing algorithm;

[0091] Specifically, traditional BeiDou positioning generally uses RTK positioning mode, which includes the following steps:

[0092] The state vector of the mobile terminal is denoted as... Where r r v represents the coordinate vector of the terminal device in the geocentric coordinate system. r Let B represent the velocity vector of the terminal device, and let B represent the single-difference integer ambiguity of the carrier phase. The double-difference carrier phase observation is denoted as... The pseudorange double difference observation is denoted as Where j and k represent satellite numbers, r represents terminal equipment, and b represents RTK reference station, the formulas for carrier phase double difference observation and pseudorange double difference observation are expressed as follows:

[0093]

[0094]

[0095] Assuming the terminal device and the base station jointly view m satellites, the observation vector in the Kalman filter state-space model can be written as y = (Φ T ,P T ) T ,in Standard Kalman filters require a linear state-space model, which necessitates linearizing the observation vectors. Let... The observation matrix H(x) is then expressed as

[0096]

[0097] in,

[0098]

[0099]

[0100] In the formula, λ represents the carrier wavelength, and matrix D represents the single-difference to double-difference transformation matrix. This represents the unit line-of-sight vector between the mobile device r and the satellite i.

[0101] Define the state transition matrix as follows for:

[0102]

[0103] Therefore, the linear state-space model of the RTK localization algorithm can be expressed as:

[0104]

[0105] Where, ξ k For process noise, ω kTo measure noise, based on the above formula, the floating-point solutions for the carrier phase single-difference integer ambiguity and the terminal device coordinates can be solved using the following extended Kalman filter (EKF) recursive formula:

[0106]

[0107] P k∣k =(IK k H k )P k∣k-1

[0108] K k =P k∣k-1 H k (H k P k∣k-1 +R k ) -1

[0109]

[0110]

[0111] in, and P represents the predicted and filtered values ​​for this epoch. k∣k-1 and P k∣k This represents the corresponding estimation error covariance matrix. The process noise covariance matrix at epoch tk is expressed as follows:

[0112]

[0113] in, τ r =t k+1 -t k Indicates the receiver sampling interval, (σ) ve ,σ vn ,σ vu E represents the standard deviation of the terminal device's speed error in the east, north, and sky directions. r The transformation matrix from the geocentric Earth-fixed coordinate system to the local coordinate system is defined as follows:

[0114]

[0115] R k The measurement noise covariance matrix at epoch tk is expressed as follows:

[0116]

[0117] Among them, R φ,i Indicates frequency point B iThe carrier phase double-difference observation measurement error, R P,i Indicates frequency point B i The pseudorange double-difference observation measurement error on R. φ,i and R P,i They can be represented as follows:

[0118]

[0119]

[0120] Because the floating-point solution of position coordinates has low precision, it is necessary to fix the integer number of carrier phase cycles before correction. For the RTK positioning algorithm, this is achieved by fixing the epoch t. k The objective is to determine the integer ambiguity of all carrier phases at any given time. The method is as follows:

[0121] First, the single-difference integer ambiguity floating-point solution is transformed into a double-difference integer ambiguity floating-point solution using a single-difference to double-difference transformation, as shown in the following formula:

[0122]

[0123]

[0124] in, Let G represent the floating-point solution of integer ambiguity with double difference, and let G represent the single-difference to double-difference transformation matrix, defined as:

[0125]

[0126] Secondly, based on the single-difference to double-difference transformation formula, the problem of fixed carrier phase integer ambiguity is equivalent to the following optimization problem:

[0127]

[0128] The optimization problem is solved by using the LAMBDA algorithm to obtain the carrier phase integer ambiguity.

[0129] Finally, determine whether the ratio of the optimal solution to the second-best solution obtained by the LANMBDA algorithm is greater than a threshold. If it is greater than the threshold, the position coordinates of the terminal device can be corrected according to the following formula:

[0130]

[0131] In this embodiment, the traditional BeiDou RTK positioning algorithm calculates the geographic location coordinates of the mobile terminal by fixing all carrier phase integer ambiguities in the observation epoch. However, in practice, due to factors such as the deterioration of the satellite positioning system environment and strong electromagnetic interference in outdoor production scenarios, the accuracy of traditional RTK positioning observations and measurements will be severely reduced, and the LAMBDA algorithm cannot accurately fix all carrier phase integer ambiguities. Therefore, in order to enable the LAMBDA algorithm to accurately obtain the carrier phase integer ambiguities and avoid the impact on positioning accuracy due to the inability to estimate them, this invention adopts a partial ambiguity fixing technique. The principle of this partial ambiguity fixing technique is to fix other integer ambiguities by deleting certain specific ambiguities to be fixed. Therefore, the ambiguity variances calculated during the EKF recursion process are sorted from largest to smallest, and the ambiguity with the highest ranking is deleted. Figure 2 A flowchart of a BeiDou RTK positioning method based on an integer ambiguity fixing algorithm is provided for an embodiment of the present invention, as shown below. Figure 2 As shown, the steps of this method are as follows:

[0132] Step 1: Calculate the floating-point solution of the position coordinates for each epoch and the floating-point solution of all single-difference integer ambiguities using the EKF recursive formula;

[0133] Step 2: Convert the single-difference integer ambiguity floating-point solution to the double-difference integer ambiguity floating-point solution;

[0134] Step 3: Use the LAMBDA algorithm to fix the double-difference integer ambiguity. If the Ratio value is not less than 3, correct the floating-point solution of the position coordinates according to the correction formula, and output the fixed solution of the position coordinates. The positioning for this epoch is complete; otherwise, jump to step 4. The correction formula is defined as:

[0135]

[0136] Where, r r v represents the coordinate vector of the terminal device in the geocentric coordinate system. r The velocity vector of the terminal device is represented by j and k, the satellite number is represented by r, and Q is represented by q. RN Q represents the covariance matrix of the measurement noise and the measurement noise after single-difference to double-difference conversion. N This represents the autocovariance matrix of the measurement noise after conversion from single-difference to double-difference. This represents a floating-point solution with double-difference integer ambiguity. The carrier phase integer ambiguity obtained by the LAMBDA algorithm

[0137] Step 4: Delete the ambiguity with the largest variance value from the set of ambiguities to be fixed in Step 3. If the number of remaining ambiguities to be fixed is not less than the sum of the dimensions of the coordinate vector and velocity vector of the terminal device in the geocentric coordinate system (which can be set to 6 in this embodiment), skip to Step 3; otherwise, output the floating-point solution of the position coordinates, and the positioning for this epoch ends.

[0138] It is understood that the algorithm provided in this embodiment of the invention ensures the accuracy of the fixation by cyclically fixing some ambiguities, and also ensures the sufficiency of the number of fixations as much as possible. The BeiDou RTK outdoor positioning enhancement scheme based on partial ambiguity fixing technology can guarantee positioning accuracy in harsh outdoor environments. By deleting certain integer ambiguities to be fixed, it improves the reliability of the outdoor BeiDou positioning system in outdoor scenarios and enhances the accuracy of BeiDou RTK outdoor positioning.

[0139] Step 102: Obtain 5G positioning data using the OTDOA high-precision positioning method based on 5G ultra-dense networking; in this step, the general 5G positioning adopts the OTDOA positioning mode. Figure 3 This is a schematic diagram of a 5G TDOA positioning mode provided in an embodiment of the present invention, as shown below. Figure 3 As shown, this positioning mode is performed through the following steps:

[0140] First, the time of a selected gNB is used as a reference; by default, it is the gNB serving the UE at the positioning time. Next, the Time of Arrival (TOA) of the reference signals sent by each gNB is measured at the UE, and the measured values ​​are sent to the network-side location server (Evolved Serving Mobile Location Center, E-SMLC). There, the Time Difference of Arrival (TDOA) between the reference base station and other base stations is calculated based on the TOA. The UE's position is then obtained by solving the hyperbolic equation determined by the two sets of TDOA values. Figure 3 This is a schematic diagram of a 5G TDOA positioning technology provided in an embodiment of the present invention, as shown below. Figure 3 As shown:

[0141] Assume the coordinates of the UE are (x, y) and the coordinates of the base station i are (x, y). i ,y i The time for base station i to send the signal is T. i The time it takes for the UE to receive this signal is τ. This can be obtained from base station i.

[0142]

[0143] The equation can be derived from the time difference between the arrival times of base station 1 and base station 2 at the UE:

[0144]

[0145] Since determining the UE's two-dimensional location requires establishing at least two equations, i.e., three base stations, base station 1 is used as the reference cell, and the following set of equations is established:

[0146]

[0147] The position of the UE can be obtained by solving the above system of equations.

[0148] Based on the above calculations, the 5G cellular network proposed in this invention, to meet the characteristics of ultra-high speed and ultra-low latency, deploys a large number of wireless transceiver nodes in diverse environmental scenarios, forming a highly dense network, namely 5G Ultra-Dense Networks (UDN). In the ultra-dense network scenario for 5G, the coverage radius of the base station is reduced from hundreds of meters to less than 100 meters. Combined with positioning technology, 5G precise positioning technology assisted by ultra-dense networking can be realized. The receiving device may be within the coverage area of ​​multiple base stations, and the distance between the receiving devices is closer to the base stations, which can reduce the path loss of the signal and bring performance improvement to the time-of-arrival (TOA / TDOA) positioning estimation algorithm.

[0149] In detail, this embodiment proposes a high-precision positioning enhancement scheme for outdoor scenarios based on 5G ultra-dense networking technology. First, NLOS error identification is performed based on binary hypothesis testing. Then, cluster analysis is performed on TDOA combinations for screening. Finally, the screened data is used to achieve high-precision OTDOA positioning.

[0150] Specifically, in OTDOA positioning systems, it is necessary to determine the LOS / NLOS propagation state of the signal between the receiver and each base station. This section uses the LOS propagation probability model in the urban micro-scale (UMi) scenario proposed in 3GPP TR 38.901 to determine the signal propagation state. The probability of LOS propagation for the signal transmitted by the base station is calculated as follows:

[0151]

[0152] Besides the effects of NLOS propagation mentioned above, receiver noise and inter-cell interference are also sources of positioning error. In the case of LOS propagation, the accuracy of ranging observations is directly related to the signal-to-noise ratio (SNR) of the received signal. Using path loss models for LOS and NLOS signals in the UMi scenario, the power of the received signal can be further calculated:

[0153] Under LOS conditions:

[0154]

[0155] in,

[0156] PL1 = 32.4 + 21log 10 (d 3D )+20log 10 (f c )

[0157] PL2 = 32.4 + 40log 10 (d 3D )+20log 10 (f c )-9.5log 10 ((d′ BP ) 2 +(h BS -h UT ) 2 )

[0158]

[0159] Under NLOS conditions:

[0160] PL UMi-LOS =max(PL UMi-LOS ,PL′ UMi-LOS )

[0161] Among them, PL′ UMi-LOS =35.3log 10 (d 3D )+22.4+21.3log 10 (f c )-0.3(h UT -1.5).

[0162] In an OTDOA positioning system, the terminal device first measures the Time of Arrival (TOA) of reference signals transmitted from different base stations, and then selects a reference base station to calculate the TOA value. The reference signal can be the primary synchronization signal (PSS) or secondary synchronization signal (SSS) of a 5G NR base station. The TOA observation value corresponding to the i-th base station can be expressed as:

[0163]

[0164] Where, r i ε is the distance between the receiving device and base station i, Δτ is the clock error, and ε is the distance between the receiving device and base station i. i These are noises and interferences caused by timing errors. In OFDM signal systems used in 5G NR, ε i The variance can be calculated:

[0165]

[0166] Among them, T SN represents the OFDM symbol duration. a The set of subcarriers used for the reference signal. Let be the relative power weight of the k-th subcarrier. The signal-to-noise ratio (SNR) of the received signal corresponding to the i-th base station is:

[0167]

[0168] Calculate the Time Difference of Received Signal (TDOA) value between each base station. The location of the receiving equipment is represented as X = [x, y]. T The location of the base station is represented as I. i =[x i ,y i ] T .

[0169]

[0170] Furthermore, to measure the impact of base station distribution on OTDOA positioning performance in ultra-dense networks, the geometrical distribution quality of base stations in a 5G ultra-dense network system can be evaluated using the geometrical precision factor (GDOP). Its value is negatively correlated with positioning accuracy. GDOP is calculated as follows:

[0171]

[0172] Where G is the Jacobian matrix of the distance measurement equation, it can be expressed as:

[0173]

[0174] In 5G ultra-dense networks, due to the denser base stations and closer proximity of receiving equipment, measurement noise is better suppressed, and more measurement data can be obtained to improve positioning accuracy. However, for NLOS observations, which are significantly affected by the OTDOA algorithm, the accuracy is impacted as the total amount of observation data increases. Using all observation data for positioning calculation affects positioning accuracy. Therefore, error discrimination and suppression algorithms can be used for NLOS.

[0175] This embodiment provides a method for identifying NLOS errors based on binary hypothesis testing. NLOS error identification is a prerequisite for effectively reducing the impact of NLOS propagation. Specifically, after identifying an NLOS signal, an appropriate algorithm is used to suppress or eliminate NLOS weighing values ​​with large errors for optimal localization. Commonly used NLOS identification algorithms include hypothesis testing and residual analysis. Hypothesis testing assumes a specific probability model between the observed signal and the NLOS error. Depending on the channel environment, an exponential, uniform, or Gaussian distribution is selected as the NLOS error distribution, and a binary hypothesis test is used to determine the NLOS signal. Residual analysis first defines residual values ​​and determines whether it is an NLOS signal based on the magnitude of the residual values.

[0176] Specifically, a binary hypothesis testing method is used to determine the LOS and NLOS of the received signal. The binary hypothesis testing method describes the identification of NLOS as a binary hypothesis testing problem. Let be the probability density function in the LOS case. The probability density function for the NLOS case:

[0177] The prior probability is P(H0).

[0178] The prior probability is P(H1).

[0179] When the prior probabilities P(H0) and P(H1) are known, a decision criterion is constructed based on the generalized likelihood ratio test:

[0180]

[0181] The NLOS error is assumed to be a Gaussian distributed random variable.

[0182]

[0183]

[0184] Where n is the number of measurements, and Let α = r + μ nlos .

[0185]

[0186] α is needed, α NLOS The following conditions must be met:

[0187]

[0188]

[0189] Solving for:

[0190]

[0191]

[0192] The above formulas represent the sample means, respectively. and variance We can obtain:

[0193]

[0194]

[0195] Applying the same treatment to the denominator in equation (2), we can obtain:

[0196]

[0197] Substituting (3) and (4) into (4) yields:

[0198]

[0199] Transform the above expression into logarithmic form:

[0200]

[0201] If the above formula holds true, the decision is H1; otherwise, it is H0. Using the binary hypothesis testing method, given the prior information—the prior probability P(H0) of LOS, the prior probability P(H1) of NLOS, and the variance of the distance measurement of the LOS data—… Under the premise of calculating the average delay measurement obtained by the terminal device Substitute (5) to determine whether the received signal is an NLOS signal.

[0202] This embodiment also provides an NLOS error suppression algorithm based on a combinatorial optimization screening algorithm. The main idea of ​​the NLOS error suppression algorithm is to set different weighting factors according to the different degrees to which the measured values ​​are affected by NLOS, so as to improve positioning accuracy. An improved least squares method can be used to mitigate NLOS errors, or a residual weighting algorithm can be used to suppress the effects of NLOS.

[0203] In 5G ultra-dense network scenarios, receiving devices can obtain a large number of TOA measurements for OTDOA positioning; however, the positioning results are affected by NLOS signals. Therefore, this section proposes a TOA-based combined optimization filtering algorithm. This algorithm borrows the basic principles of data clustering to filter TOA measurements, namely the NLOS error discrimination method mentioned earlier. Considering the characteristics of 5G ultra-dense network scenarios—that receiving devices can obtain a large number of TOA measurements—the NLOS suppression algorithm is not used to process the filtered NLOS signals. Instead, these measurements are directly discarded, and the remaining measurements are used for optimal positioning.

[0204] The large number of measurements unique to 5G ultra-dense network scenarios ensures that sufficient data is available for OTDOA positioning after discarding some measurements. Under this premise, optimal positioning not only simplifies computational complexity but also ensures that the identified NLOS signals have no impact on the positioning results.

[0205] The NLOS error suppression algorithm proposed in this embodiment, based on a combinatorial optimization screening algorithm, first obtains a large number of positioning results by selecting different TDOA combinations using the TDOA combinatorial optimization screening algorithm. Then, it uses the K-means clustering algorithm (also known as the K-means clustering algorithm) to perform cluster analysis on the positioning results, thereby screening the corresponding TDOA values ​​and base stations. Finally, it uses the screened measurement values ​​to perform OTDOA positioning. Figure 4 A flowchart of an OTDOA high-precision positioning algorithm based on 5G ultra-dense networking is provided for an embodiment of the present invention, as follows: Figure 4 As shown, the specific process of the precise positioning algorithm based on 5G ultra-dense networking is as follows:

[0206] Step 1: Preliminary selection: For all measured TOA values, set a large threshold and delete TOA measurements that show obvious errors. The number of TOA measurements and corresponding base stations after preliminary screening is N.

[0207] Step Two: Preliminary Estimation. Select three TOA values ​​from the initial TOA pool, randomly choose a reference base station, and calculate the TDOA value. Substituting each of the following cases into the OTDOA algorithm, we can obtain... There are several different estimated locations.

[0208] Step 3: Precise Filtering. All locations obtained in Step 2 are clustered using the K-means clustering algorithm. Assume there are M clusters. Count the estimated number of locations in each cluster, where M... max This represents the class with the highest estimated number, and the statistic M is... maxThe system is used to calculate the estimated TOA value and the corresponding base station. Then, the statistical results are sorted from largest to smallest according to usage frequency. The top K TOA values ​​and their corresponding base stations are taken, and a new reference base station is selected to obtain the filtered K-1 TOA values.

[0209] Step 4: Precise estimation. Using the filtered K-1 TDOA values ​​and their corresponding base station locations, re-estimate the location according to the basic algorithm to obtain the optimized location estimation result.

[0210] Specifically, in two-dimensional space, the state vector at time k is defined as X(k) = [X(k), S... x (k),Y(k),S y (k)] T Where X(k) and S x (k) represents the eastward position vector and velocity vector of the terminal device to be located, Y(k) and S(k) are given. y (k) represents the locomotive's northward position vector and velocity vector, and T is the time interval; V is defined as... x (k), V y (k) is a zero-mean, variance ? Given two independent orthogonal vectors of Gaussian white noise V(k), the equation of the terminal device at time k+1 is as follows, according to the motion formula:

[0211]

[0212] S x (k+1)=S x (k)+TV x (k)

[0213]

[0214] S y (k+1)=S y (k)+TV y (k)

[0215] Summarized as follows:

[0216]

[0217] make

[0218] The state equation of the subsystem is:

[0219] X(k+1)=Φ(k)X(k)+H(k)V1(k)

[0220] Similarly, suppose the coordinates of the terminal device at time k are (x z (k),y z(k)), whose coordinate equation can be expressed as:

[0221]

[0222] The observation equations of the system can be obtained as follows:

[0223] Z(k)=T(k)X(k)+M(k)V2(k)

[0224] in:

[0225] V x (k) and V y (k) are mutually independent.

[0226] In addition, a 5G OTDOA positioning local filter was designed to process 5G ultra-dense network OTDOA positioning data.

[0227] Specifically, in 5G ultra-dense network scenarios, the geometric distribution of base stations results in a large number of NLOS signals that affect positioning accuracy. This positioning module first uses a binary hypothesis testing method to identify and remove errors from the NLOS signals. Then, it uses a combinatorial optimization filtering method based on K-meas clustering to obtain the optimal positioning combination, thereby achieving OTDOA positioning. Due to the influence of distance and other errors, to further improve the positioning accuracy of this module, the system output positioning data is processed by Kalman filtering, described as follows:

[0228]

[0229] Where f is the motion law function of the terminal device, h is the OTDOA high-precision positioning model in the 5G UDN scenario, and the state vector of the mobile terminal at time p is represented by S. p =[x p ,y p ,v x,p ,v y,p Let Φ be the state transition matrix, and let Q be the noise vector W. k The covariance matrix of the terminal at time p is given by:

[0230] S p+1 =ΦS p +W p

[0231] in,

[0232]

[0233] in, To drive the variance of the noise, which compensates for the limitations of the matrix Φ in describing motion laws and is applicable to any motion law, the target observation equation is defined as follows:

[0234] Z p =h(S p )+V p

[0235] Among them, Z p It is the observation data vector, V p It is observation noise, due to h(S) p () is a nonlinear transformation, which linearizes the above equation to:

[0236] Z p =H p S p +V p

[0237] Kalman filtering can be used to dynamically reconstruct the true location information of the target in real time, removing observed noise and interference. Whenever new observation data is acquired, combined with the predicted value from the previous moment, the optimal estimate of the current location can be obtained.

[0238] Step 103: Input the acquired BeiDou positioning data and 5G positioning data into the Federal Kalman BeiDou Local Filter and 5G Local Filter respectively for filtering, and perform fault self-check. The fault self-check is used to filter out invalid positioning information acquired due to obstruction by obstacles.

[0239] Specifically, the BeiDou positioning data and 5G positioning data obtained by the BeiDou RTK positioning method based on integer ambiguity fixed algorithm and the OTDOA high-precision positioning method based on 5G ultra-dense networking are respectively input into the Federal Kalman BeiDou local filter and the 5G local filter for filtering, and fault self-check is performed.

[0240] Preferably, this embodiment uses residual verification to detect the local filter;

[0241] Specifically, in order to ensure the final fusion accuracy of the main filter, the local filter must first perform a self-check to determine whether a subsystem has malfunctioned and whether to input data to the main filter.

[0242] During the positioning process, the positioning submodule may experience BeiDou positioning failures due to obstruction, receiver damage, or damage to the BeiDou communication card, as well as 5G positioning failures due to lack of communication base stations, unpaid communication cards, communication card malfunctions, or damage to the communication module. When the positioning submodule malfunctions, the state output data of the corresponding local filter changes significantly. Therefore, residual verification can be used for detection, and the calculation formula is shown below:

[0243] ε=ZZ(k-1)

[0244] Where ε is the residual, Z is the measured value, and Z(k-1) is the observed value. When ε is greater than the set value, it can be considered that the corresponding sub-filter has malfunctioned and stops inputting data to the main filter.

[0245] Step 104: Input the BeiDou positioning data and 5G positioning data after self-testing into the main filter BeiDou data processing channel and 5G data processing channel respectively. Perform information fusion according to the information allocation factor to obtain the 5G+BeiDou fusion enhanced positioning result. The main filter BeiDou data processing channel and 5G data processing channel are respectively set with information allocation factors. The information allocation factors are preset according to the number of available satellites and positioning accuracy requirements.

[0246] Specifically, the BeiDou positioning data and 5G positioning data after self-testing are input into the main filter BeiDou data processing channel and 5G data processing channel, respectively. Information is fused according to the information allocation factor to obtain the 5G+BeiDou fusion enhanced positioning result. The main filter BeiDou data processing channel and 5G data processing channel are respectively set with information allocation factors, which are preset according to the number of available satellites and positioning accuracy requirements.

[0247] In this embodiment, based on the number of detected satellites, an information allocation factor is set in the BeiDou data processing channel and the 5G data channel of the main filter. The BeiDou RTK positioning data and the 5G ultra-dense networking OTDOA positioning data after local filter processing are respectively input into the BeiDou data processing channel and the 5G data channel of the main filter for processing to complete data fusion.

[0248] Specifically, the data from the BeiDou RTK positioning module and the 5G ultra-dense network OTDOA positioning module are processed by a local filter, and then the main filter completes the data fusion processing of the two positioning sub-modules, thereby outputting the optimal 5G+BeiDou fusion positioning result. The fusion positioning formula is as follows:

[0249]

[0250] The optimal result is then fed back to the local filter as follows:

[0251]

[0252] In the formula: P represents the covariance matrix; Q represents the noise covariance matrix; X represents the state vector; β i Represents the information allocation factor, satisfying

[0253] Preferably, since the outdoor environment is complex and changeable, using a fixed information allocation factor will greatly affect the accuracy of the fused data. Considering that there are many base stations and the signal is relatively stable under the 5G ultra-dense network architecture, the information allocation factor can be inclined towards the 5G cellular positioning method. The information allocation factor can be dynamically changed according to the number of available satellites.

[0254] In one specific embodiment, the determination of the information allocation factor value under different environments can be divided into three cases according to the degree of influence of building obstruction on positioning, as shown in Table 1:

[0255] Table 1. Information allocation factor values ​​under different environments

[0256] Number of available BeiDou satellites ≥ 5 0.5 0.5 3 ≤ Number of available satellites < 5 (0.1，0.5) (0.5，0.9) Number of available satellites < 3 ≈0 ≈1

[0257] This invention provides a 5G+BeiDou fusion-enhanced positioning method for outdoor scenarios, which designs a seamless multi-mode positioning switching mechanism based on factors such as the number of satellites. By rationally deciding among three modes—BeiDou positioning, 5G OTDOA positioning, and 5G+BeiDou fusion positioning—the optimal selection of the terminal positioning scheme in outdoor scenarios is achieved, ensuring that the mobile terminal can still obtain high-precision location information even in outdoor obstructed conditions, effectively improving the reliability of outdoor positioning. This invention proposes a positioning enhancement scheme based on a federated Kalman filter algorithm. By inputting the positioning data obtained from the improved BeiDou RTK positioning mode and the 5G ultra-dense network OTDOA positioning mode into the federated Kalman filter and performing fault self-checking, erroneous data is filtered out. Finally, higher-precision location information is obtained through fusion by the main filter.

[0258] In detail, Figure 5 This invention provides a 5G+BeiDou fusion enhanced positioning system model, such as... Figure 5 As shown, when both BeiDou RTK positioning and 5G ultra-dense network-assisted OTDOA positioning modes are available, this invention proposes a 5G+BeiDou fusion-enhanced positioning mode based on the federated Kalman filter algorithm to meet the high-precision positioning needs of the terminal. First, BeiDou RTK positioning based on an integer ambiguity fixed algorithm and an OTDOA high-precision positioning enhancement algorithm based on 5G ultra-dense network are used. Then, the data obtained from the two positioning algorithms are input into BeiDou and 5G local filters for filtering. Due to the structural characteristics of the federated Kalman filter algorithm, when a subsystem fails, it affects the calculation of optimal fusion, resulting in a larger error in the filtering result and contaminating the data filtering accuracy of other subsystems. To avoid subsystem failures in the federated Kalman filter algorithm affecting the final fusion positioning result, a local filter fault self-checking module is added based on a general federated Kalman filter model. Finally, the processed data from the two positioning methods are input into the main filter for optimal fusion and time update, thereby obtaining the location information of the fusion positioning mode.

[0259] This invention also provides an outdoor multi-mode switching method. Figure 6 A flowchart of an outdoor multimode switching method provided in an embodiment of the present invention is shown below. Figure 6 As shown, the method includes:

[0260] Step 601: Based on the current BeiDou positioning accuracy GDOP value and the 5G positioning accuracy P value... 5G The value detects the occlusion status of the user's outdoor environment, which includes unobstructed, partially obstructed, and completely obstructed environments;

[0261] In this step, the switching between positioning systems is based on the accuracy of the two sets of positioning sensors, and multiple threshold values ​​are used to reduce the probability of switching errors.

[0262] In detail, on the one hand, in BeiDou positioning, the Geometric Dilution Precision (GDOP) is an important parameter for measuring positioning quality. The magnitude of GDOP is affected by the geometric distribution of observable satellites in space. If the number of currently visible satellites is no less than four and their distribution in space is relatively dispersed, BeiDou positioning mode can achieve a higher positioning accuracy. The larger the GDOP value, the worse the positioning accuracy at the current moment. User Equivalent Range Error (UERE) includes User Range Error (URE) and User Equipment Error (UEE). URE mainly depends on satellite clock errors, satellite positions, and ephemeris errors, while UEE is related to the user's environment. The accuracy P of BeiDou positioning can be evaluated through GDOP and UERE. BD :

[0263] P BD =GDOP × UERE;

[0264] On the other hand, 5G OTDOA positioning errors are related to factors such as the geometric distribution between beacons and base stations, signal strength, whether the tag is currently stationary or moving, and magnetic field interference. Therefore, the 5G positioning accuracy varies for users in different areas of outdoor scenarios. Multiple samples of 5G positioning data from outdoor scenarios were taken, and the positioning accuracy P corresponding to different distances between the tag and the base station within that area was calculated. 5G .

[0265] The obstruction of the outdoor environment includes no obstruction, partial obstruction, and complete obstruction.

[0266] In detail, the non-occlusion specifically comprises: when the BeiDou positioning accuracy GDOP at the current moment is less than a first threshold, multiplying a count value at the current moment by a reduction rate to obtain a first judgment value, and judging whether the first judgment value is less than a count threshold; if it is judged that the first judgment value is not less than the count threshold, then again according to the BeiDou positioning accuracy GDOP value at the current moment and the 5G positioning accuracy P 5G value, detecting the occlusion condition of an outdoor environment where a user is located; if it is judged that the first judgment value is less than the count threshold, determining that there is no occlusion.

[0267] The partial occlusion specifically comprises: monitoring the BeiDou positioning accuracy GDOP at the current moment and 5G positioning accuracy P 5G , when the BeiDou positioning accuracy GDOP at the current moment is greater than the first threshold and less than a second threshold, and the 5G positioning accuracy P 5G is greater than a third threshold and less than a fourth threshold, performing cumulative counting to obtain the count value at the current moment, and judging whether the count value at the current moment is greater than the count threshold; if it is judged that the count value at the current moment is not greater than the count threshold, continuing to monitor the BeiDou positioning accuracy GDOP and 5G positioning accuracy at the current moment; if it is judged that the count value at the current moment is greater than the count threshold, determining that the occlusion condition is partial occlusion;

[0268] The complete occlusion specifically comprises: when the BeiDou positioning accuracy GDOP at the current moment is greater than the second threshold, and the 5G positioning accuracy P 5G is less than the third threshold, multiplying the count value at the current moment by the reduction rate to obtain a second judgment value, and judging whether the second judgment value is less than the count threshold; if it is judged that the second judgment value is not less than the count threshold, executing the occlusion condition judgment step again; if it is judged that the second judgment value is less than the count threshold, determining that the occlusion is complete occlusion, wherein the first threshold, the second threshold, the third threshold, and the fourth threshold are preset, the first threshold is smaller than the second threshold, and the third threshold is smaller than the fourth threshold; an initial value of the count value is 1, different processing is corresponding to different occlusion conditions, the count threshold is preset according to different application scenarios; the reduction rate is preset according to a sensor frequency of a used positioning system, and is within a range of 0 to 1.

[0269] In a specific embodiment, after the above setting and calculation, according to the calculation results of GDOP and P 5G , a count value n is introduced; a count threshold N, N≥n; a reduction rate R (0<R<1, the value of R needs to be set according to a sensor frequency), and two threshold α1 and α2 of 5G OTDOA positioning accuracy, wherein α1<α2.

[0270] In this embodiment, according to the actual application scenario, the first threshold is preset as 3, the second threshold as 7, the third threshold as α1, and the fourth threshold as α2. After positioning is started, the value of GDOP is judged first. If GDOP is less than 3, it indicates that the Beidou positioning module can provide relatively accurate positioning at this time, the current spatial distribution of observable satellites is good, and the user is in an unobstructed outdoor environment; if 3<GDOP<7, and the positioning accuracy of 5G OTDOA satisfies the condition α1<P 5G <α2, it is determined that the user is currently in an outdoor environment with partial occlusion; if GDOP>7 and P satisfies 5G <α1, the user may have moved to a severely occluded location area outdoors, and it is determined that the user is currently in a fully occluded outdoor environment.

[0271] It can be understood that the Beidou positioning dilution of precision GDOP and 5G positioning dilution of precision P introduced in the embodiments of the present invention 5G essentially adopt an outdoor positioning switching algorithm based on a threshold mechanism and multi-sensor positioning accuracy. The confidence of each sensor system is determined by the real-time positioning accuracy of the sensors, the occlusion condition of the current outdoor environment is judged, and the outdoor occlusion condition is quantitatively considered, so that when the positioning terminal device moves in a complex environment, it can select the best positioning mode from the multi-mode positioning schemes according to the current quantitative result to ensure positioning accuracy. Meanwhile, when switching outdoor positioning modes, seamless, smooth and stable positioning connection is satisfied, and finally full-coverage high-precision positioning for mobile terminal users in outdoor scenes is realized.

[0272] Step 602: Execute a corresponding positioning mode based on the detected occlusion condition of the outdoor environment, which specifically includes: when it is detected that the outdoor environment where the user is located is unobstructed, positioning is performed by adopting the Beidou positioning mode; when it is detected that the outdoor environment where the user is located is partially occluded, the above-mentioned 5G+Beidou fusion enhanced positioning method is adopted; when it is detected that the outdoor environment where the user is located is fully occluded, positioning is performed by adopting the 5G positioning mode.

[0273] Specifically, Figure 7 the present invention provides an outdoor multi-mode switching strategy according to an embodiment, as Figure 7 shown, in the outdoor multi-mode switching strategy provided by the embodiment of the present invention, the multiple modes include three modes: Beidou real-time kinematic (RTK) positioning, 5G Observed Time Difference of Arrival (OTDOA) positioning, and Beidou+5G fusion enhanced positioning.

[0274] Furthermore, in order to achieve a reasonable and seamless switching between the three positioning modes, this invention introduces an outdoor multi-mode positioning seamless switching mechanism. In outdoor scenarios, mobile terminals can reasonably select one of the following modes—BeiDou RTK positioning, 5G OTDOA positioning, and BeiDou+5G fusion positioning—based on the number of satellites receiving positioning signals at the current moment and the required positioning accuracy.

[0275] Specifically, according to the aforementioned method for determining occlusion, when the user's outdoor environment is determined to be unobstructed, the BeiDou positioning mode is used; when the user's outdoor environment is determined to be partially obstructed, the 5G+BeiDou fusion enhanced positioning mode is used; and when the user's outdoor environment is determined to be completely obstructed, the 5G positioning mode is used.

[0276] Figure 8 This is an implementation scheme of the multi-mode fusion positioning method under the outdoor multi-mode switching strategy provided in the embodiments of the present invention, such as... Figure 8 As shown, the BeiDou RTK positioning mode is executed when only BeiDou is available, and the 5G positioning mode is executed when satellites are blocked and only 5G positioning is available. In OTDOA positioning mode, when both BeiDou RTK positioning and 5G ultra-dense network-assisted OTDOA positioning are available, to meet the high-precision positioning needs of the terminal, a BeiDou RTK positioning algorithm based on a federated Kalman filter and an integer ambiguity fixed algorithm, and an OTDOA high-precision positioning enhancement algorithm based on 5G ultra-dense network are used. The data obtained from the two positioning algorithms are input into BeiDou and 5G local filters for filtering, respectively. Due to the structural characteristics of the federated Kalman filter algorithm, when a subsystem fails, it will affect the calculation of optimal fusion, and the filtering result will have a larger error, which will pollute the data filtering accuracy of other subsystems. In order to avoid the failure of the federated Kalman filter algorithm subsystem and thus affect the final fused positioning result, a local filter fault self-checking module is added based on the general federated Kalman filter model. Finally, the processed data from the two positioning methods are input into the main filter for optimal fusion and time update, thereby obtaining the location information of the fused positioning mode, which can effectively improve the reliability of the mobile terminal's positioning service in outdoor environments with obstructions and other environmental degradation conditions.

[0277] The present invention also provides a 5G+BeiDou fusion enhanced positioning device for outdoor scenarios. The 5G+BeiDou fusion enhanced positioning device for outdoor scenarios described below can be referred to in correspondence with the 5G+BeiDou fusion enhanced positioning method for outdoor scenarios described above.

[0278] Figure 9 This is a schematic diagram of the structure of a 5G+BeiDou fusion enhanced positioning device for outdoor scenarios provided in an embodiment of the present invention, as shown below. Figure 9 As shown, the device includes:

[0279] The acquisition module 91 is used to acquire BeiDou high-precision positioning data through the BeiDou RTK positioning method based on the integer ambiguity fixed algorithm;

[0280] The acquisition module 91 is also used for the OTDOA high-precision positioning method based on 5G ultra-dense networking to acquire 5G high-precision positioning data;

[0281] The filtering module 92 is used to input the acquired BeiDou positioning data and 5G positioning data into the BeiDou local filter and the 5G local filter respectively for filtering, and to perform fault self-checks respectively. The fault self-checks are used to filter out invalid positioning information acquired due to obstruction by obstacles.

[0282] The fusion positioning module 93 is used to input the BeiDou positioning data and 5G positioning data after self-testing into the main filter BeiDou data processing channel and 5G data processing channel respectively, and perform information fusion according to the information allocation factor to obtain the 5G+BeiDou fusion enhanced positioning result. The main filter BeiDou data processing channel and 5G data processing channel are respectively set with information allocation factors, which are preset according to the number of available satellites and positioning accuracy requirements.

[0283] Optionally, the filtering module 92 further includes a federated Kalman filter, which is used to input the BeiDou high-precision positioning data and 5G high-precision positioning data acquired by the acquisition module into the federated Kalman filter for filtering, and to perform fault self-check. The fault self-check is used to filter out invalid positioning information acquired due to obstruction.

[0284] The present invention also provides an outdoor multi-mode switching device, which can be referred to in correspondence with the outdoor multi-mode switching method described above.

[0285] Figure 10 This is a schematic diagram of the structure of the outdoor multi-mode switching device provided in an embodiment of the present invention, as shown below. Figure 10 As shown, the device includes:

[0286] The occlusion determination module 1001 is used to determine the occlusion based on the current BeiDou positioning accuracy GDOP value and the 5G positioning accuracy P value. 5G The value detects the occlusion status of the user's outdoor environment, which includes unobstructed, partially obstructed, and completely obstructed environments;

[0287] The positioning mode switching module 1002 is used to execute the corresponding positioning mode based on the detected obstruction of the outdoor environment, specifically including:

[0288] When the user's outdoor environment is unobstructed, the BeiDou positioning mode is used for positioning.

[0289] When the outdoor environment where the user is located is partially obstructed, the 5G+BeiDou fusion enhanced positioning mode is adopted. The 5G+BeiDou fusion enhanced positioning mode is realized by the above-mentioned 5G+BeiDou fusion enhanced positioning device for outdoor scenarios.

[0290] When the outdoor environment where the user is located is completely obstructed, the 5G positioning mode is used for positioning.

[0291] In this embodiment, the positioning mode switching module 1002 further includes a BeiDou RTK positioning local filter, a 5G OTDOA positioning local filter, a detection module, and a main filter. Specifically, the BeiDou RTK positioning local filter is used to process BeiDou RTK positioning data; the 5G OTDOA positioning local filter is used to process 5G ultra-dense network OTDOA positioning data; the detection module is used to detect the local filters; and the main filter is used to input the BeiDou RTK positioning data and 5G ultra-dense network OTDOA positioning data processed by the local filters into the main filter to complete data fusion.

[0292] Figure 11 This is a schematic diagram of the physical structure of an electronic device provided in an embodiment of the present invention, such as... Figure 11 As shown, the electronic device may include: a processor 1110, a communications interface 1120, a memory 1130, and a communications bus 1140, wherein the processor 1110, the communications interface 1120, and the memory 1130 communicate with each other through the communications bus 1140. The processor 1110 can call logic instructions in the memory 1130 to execute a 5G+BeiDou fusion enhanced positioning method for outdoor scenarios. This method includes: acquiring BeiDou positioning data using a BeiDou RTK positioning method based on an integer ambiguity fixed algorithm; acquiring 5G positioning data using an OTDOA high-precision positioning method based on 5G ultra-dense networking; inputting the acquired BeiDou positioning data and 5G positioning data into a BeiDou local filter and a 5G local filter respectively for filtering, and performing fault self-checks on each, wherein the fault self-checks are used to filter invalid positioning information acquired due to obstruction; inputting the self-checked BeiDou positioning data and 5G positioning data into the main filter BeiDou data processing channel and the 5G data processing channel respectively, and performing information fusion according to an information allocation factor to obtain a 5G+BeiDou fusion enhanced positioning result. The main filter BeiDou data processing channel and the 5G data processing channel are respectively set with information allocation factors, which are preset according to the number of available satellites and positioning accuracy requirements.

[0293] Processor 1110 can call logic instructions in memory 1130 to execute an outdoor multi-mode handover method, the method including: based on the current BeiDou positioning accuracy GDOP value and 5G positioning accuracy P... 5G The system detects the occlusion status of the user's outdoor environment, including unobstructed, partially obstructed, and completely obstructed environments. Based on the detected occlusion status, it executes the corresponding positioning mode, specifically: when the user's outdoor environment is unobstructed, it uses the BeiDou positioning mode for positioning; when the user's outdoor environment is partially obstructed, it uses the 5G+BeiDou fusion enhanced positioning method; and when the user's outdoor environment is completely obstructed, it uses the 5G positioning mode for positioning.

[0294] Furthermore, the logical instructions in the aforementioned memory 1130 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0295] On the other hand, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described 5G+BeiDou fusion enhanced positioning method and outdoor multi-mode switching method for outdoor scenarios.

[0296] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0297] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An outdoor multi-mode switching method, characterized in that, include: Based on the current BeiDou positioning accuracy (GDOP) and 5G positioning accuracy... The value detects the occlusion status of the user's outdoor environment, which includes unobstructed, partially obstructed, and completely obstructed environments; Based on the detected outdoor environmental obstructions, the corresponding positioning mode is executed, specifically including: When the user's outdoor environment is unobstructed, the BeiDou positioning mode is used for positioning. When the outdoor environment where the user is located is partially obstructed, a 5G+BeiDou fusion enhanced positioning method is adopted, which includes: BeiDou positioning data is obtained using a BeiDou RTK positioning method based on an integer ambiguity fixing algorithm. A high-precision OTDOA positioning method based on 5G ultra-dense networking is used to acquire 5G positioning data. The acquired BeiDou positioning data and 5G positioning data are respectively input into the BeiDou local filter and the 5G local filter for filtering, and fault self-checks are performed respectively. The fault self-checks are used to filter out invalid positioning information acquired due to obstruction by obstacles. The BeiDou positioning data and 5G positioning data after self-testing are respectively input into the main filter BeiDou data processing channel and 5G data processing channel. Information is fused according to the information allocation factor to obtain the 5G+BeiDou fusion enhanced positioning result. The main filter BeiDou data processing channel and 5G data processing channel are respectively set with information allocation factors, which are preset according to the number of available satellites and positioning accuracy requirements. When the outdoor environment where the user is located is completely obstructed, the 5G positioning mode is used for positioning. Based on the current BeiDou positioning accuracy (GDOP) and 5G positioning accuracy... The value detects the occlusion of the user's outdoor environment. The determination of the local occlusion specifically includes: Monitor the current BeiDou positioning accuracy (GDOP) and 5G positioning accuracy. At the current moment, the BeiDou positioning accuracy (GDOP) is greater than a first threshold and less than a second threshold, while the 5G positioning accuracy... When the value is greater than the third threshold and less than the fourth threshold, the count is accumulated to obtain the count value at the current time, and it is determined whether the count value at the current time is greater than the counting threshold. If the current count value is determined to be no greater than the count threshold, then the BeiDou positioning accuracy (GDOP) and 5G positioning accuracy at the current time will continue to be monitored. If the current count value is greater than the count threshold, the occlusion is determined to be partial occlusion. The first threshold, second threshold, third threshold, and fourth threshold are preset, with the first threshold being less than the second threshold and the third threshold being less than the fourth threshold; the initial value of the count value is 1, and the count threshold is preset according to different application scenarios.

2. The outdoor multi-mode switching method according to claim 1, characterized in that, The BeiDou local filter, 5G local filter, and main filter are all federal Kalman filters.

3. The outdoor multi-mode switching method according to claim 1, characterized in that, The BeiDou RTK positioning method based on the integer ambiguity fixing algorithm specifically includes: S31. Calculate the floating-point solution of the position coordinates of each epoch and the floating-point solution of all single-difference integer ambiguities using the EKF recursive formula; S32. Convert the single-difference integer ambiguity floating-point solution into a double-difference integer ambiguity floating-point solution; S33. Based on the LAMBDA algorithm, fix the double-difference integer ambiguity. If the Ratio value is not less than the predetermined threshold, use a specific correction formula to correct the floating-point solution of the position coordinates and output the fixed solution of the position coordinates. The positioning of this epoch ends; otherwise, go to step S34. S34. Delete the ambiguity with the largest variance value in the set of ambiguities to be fixed in step S33. If the number of remaining ambiguities to be fixed is not less than the sum of the dimensions of the coordinate vector and velocity vector of the terminal device in the geocentric coordinate system, go to step S33; otherwise, output the floating-point solution of the position coordinates and the positioning of this epoch ends.

4. The outdoor multi-mode switching method according to claim 1, characterized in that, The OTDOA high-precision positioning method based on 5G ultra-dense networking includes: S41: Set a specific threshold for all measured TOA values, and perform preliminary screening on the TOA values ​​within the threshold, deleting TOA values ​​that show obvious errors. Let N be the TOA measurement values ​​after preliminary screening and the number of corresponding base stations. S42: Select a specific number of TOA values ​​from the N TOA measurement values ​​after initial screening, randomly select a reference base station, calculate the TDOA value, and substitute it into the OTDOA algorithm to obtain the corresponding estimated location; S43: For all estimated locations obtained in step S52, perform clustering using the K-means clustering algorithm. Assume there are M categories. Count the number of estimated locations in each category. This represents the class with the highest estimated number, and the statistics are as follows. The system is used to calculate the estimated TOA value and the corresponding base station; the statistical results are sorted from largest to smallest according to the number of uses, the top K TOA values ​​and the corresponding base stations are taken, and reference base stations are reselected to obtain the filtered K-1 TDOA values; S44: Using the filtered K-1 TDOA values ​​and their corresponding base station locations, re-evaluate the location according to the basic algorithm to obtain the optimized location estimation result.

5. The outdoor multi-mode switching method according to claim 1, characterized in that, Based on the current BeiDou positioning accuracy (GDOP) and 5G positioning accuracy... The value detects the obstruction of the user's outdoor environment. The determination of no obstruction specifically includes: When the BeiDou positioning accuracy GDOP is less than the first threshold at the current moment, the count value at the current moment is multiplied by the reduction rate to obtain the first judgment value, and it is determined whether the first judgment value is less than the count threshold. If the first determination value is not less than the counting threshold, then the BeiDou positioning accuracy (GDOP) and 5G positioning accuracy at the current time are considered again. The value detects the degree of obstruction in the user's outdoor environment; If the first determination value is less than the counting threshold, it is determined to be unobstructed; The first threshold is preset, and the counting threshold is preset according to different application scenarios.

6. The outdoor multi-mode switching method according to claim 1, characterized in that, Based on the current BeiDou positioning accuracy (GDOP) and 5G positioning accuracy... The value detects the occlusion status of the user's outdoor environment. The determination of total occlusion specifically includes: At the current moment, the BeiDou positioning accuracy (GDOP) is greater than the second threshold, while the 5G positioning accuracy... When the count value is less than the third threshold, the count value at the current time is multiplied by the reduction rate to obtain the second judgment value, and it is determined whether the second judgment value is less than the count threshold. If the second determination value is not less than the counting threshold, the occlusion determination step is executed again. If the second determination value is less than the counting threshold, it is determined to be a full occlusion. The first threshold, second threshold, third threshold, and fourth threshold are preset, with the first threshold being less than the second threshold and the third threshold being less than the fourth threshold; the initial value of the count value is 1, and different processing is applied according to different occlusion conditions; the count threshold is preset according to different application scenarios; the reduction rate is preset according to the sensor frequency of the positioning system used, and is within the range of 0 to 1.

7. An outdoor multi-mode switching device, characterized in that, include: The occlusion determination module is used to determine the occlusion based on the current BeiDou positioning accuracy (GDOP) and 5G positioning accuracy. The value detects the occlusion status of the user's outdoor environment, which includes unobstructed, partially obstructed, and completely obstructed environments; The positioning mode switching module is used to execute the corresponding positioning mode based on the detected outdoor environmental obstruction, specifically including: When the user's outdoor environment is unobstructed, the BeiDou positioning mode is used for positioning. When the outdoor environment where the user is located is partially obstructed, a 5G+BeiDou fusion enhanced positioning mode is adopted. The 5G+BeiDou fusion enhanced positioning mode is implemented through a 5G+BeiDou fusion enhanced positioning method, which includes: BeiDou positioning data is obtained using a BeiDou RTK positioning method based on an integer ambiguity fixing algorithm. A high-precision OTDOA positioning method based on 5G ultra-dense networking is used to acquire 5G positioning data. The acquired BeiDou positioning data and 5G positioning data are respectively input into the BeiDou local filter and the 5G local filter for filtering, and fault self-checks are performed respectively. The fault self-checks are used to filter out invalid positioning information acquired due to obstruction by obstacles. The BeiDou positioning data and 5G positioning data after self-testing are respectively input into the main filter BeiDou data processing channel and 5G data processing channel. Information is fused according to the information allocation factor to obtain the 5G+BeiDou fusion enhanced positioning result. The main filter BeiDou data processing channel and 5G data processing channel are respectively set with information allocation factors, which are preset according to the number of available satellites and positioning accuracy requirements. When the outdoor environment where the user is located is completely obstructed, the 5G positioning mode is used for positioning. Based on the current BeiDou positioning accuracy (GDOP) and 5G positioning accuracy... The value detects the occlusion of the user's outdoor environment. The determination of the local occlusion specifically includes: Monitor the current BeiDou positioning accuracy (GDOP) and 5G positioning accuracy. At the current moment, the BeiDou positioning accuracy (GDOP) is greater than a first threshold and less than a second threshold, while the 5G positioning accuracy... When the value is greater than the third threshold and less than the fourth threshold, the count is accumulated to obtain the count value at the current time, and it is determined whether the count value at the current time is greater than the counting threshold. If the current count value is determined to be no greater than the count threshold, then the BeiDou positioning accuracy (GDOP) and 5G positioning accuracy at the current time will continue to be monitored. If the current count value is greater than the count threshold, the occlusion is determined to be partial occlusion. The first threshold, second threshold, third threshold, and fourth threshold are preset, with the first threshold being less than the second threshold and the third threshold being less than the fourth threshold; the initial value of the count value is 1, and the count threshold is preset according to different application scenarios.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the outdoor multi-mode switching method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the outdoor multimode switching method as described in any one of claims 1 to 6.

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