Bluetooth-based positioning navigation system and method

Abstract

The invention discloses a Bluetooth-based positioning navigation system and method, and belongs to the technical field of wireless communication, and the method comprises the steps: constructing a three-dimensional structure model containing floor spacing, floor thickness and floor crossing channel information, deploying Bluetooth beacons, building a beacon library, receiving a signal intensity value set uploaded by a mobile terminal, and transmitting the received signal intensity value set to the mobile terminal; calculating two-dimensional positioning coordinates based on a path loss model; further, evaluating the layer crossing probability of each signal in combination with the structure model, and constructing a layer crossing feature vector; when floor crossing interference is detected, floor correction is carried out according to the floor where the maximum floor crossing probability signal is located, and a three-dimensional positioning coordinate is generated; otherwise, expanding the two-dimensional coordinates according to the default floor; finally, an optimal path is generated through a three-dimensional path planning algorithm, a semantic navigation instruction is output, and dynamic deviation correction of positioning and navigation is achieved. According to the invention, the problem that the floor is easily misjudged in the vertical direction by traditional Bluetooth positioning is effectively solved, and the positioning precision and the navigation reliability in the multi-story building are improved.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and more specifically to a Bluetooth-based positioning and navigation system and method. Background Technology

[0002] Currently, Bluetooth positioning technology is widely used in scenarios such as indoor navigation, personnel tracking, and asset management. Especially in complex buildings such as hospitals, subway stations, airports, and exhibition halls, Bluetooth beacons, in conjunction with mobile terminals, enable positioning and navigation, becoming an effective alternative to solving the problem that GPS signals cannot penetrate building obstacles.

[0003] However, existing Bluetooth positioning and navigation systems have significant problems in scenarios involving diagonal crossings between multi-story buildings, especially inaccurate or incorrect vertical positioning, leading to serious deviations in navigation paths. For example, in large general hospitals, users often experience signal penetration through floor slabs, causing the system to mistakenly believe they have reached the upper / lower floor, resulting in misaligned navigation paths that lead users to the wrong departments or operating rooms, and even causing delays in patient visits or surgeries, severely impacting efficiency and medical safety.

[0004] Further analysis revealed that the root cause of the problem lies in the fact that traditional RSSI-based positioning algorithms struggle to accurately distinguish the user's floor in scenarios where adjacent floors have thin floor slabs, dense Bluetooth beacon layouts, and frequent vertical transmission structures such as elevator shafts and pipe shafts. The RSSI values ​​overlap significantly, resulting in fuzzy positioning in the vertical direction. Summary of the Invention

[0005] The purpose of this invention is to provide a Bluetooth-based positioning and navigation system and method to address the shortcomings in the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a Bluetooth-based positioning and navigation method, comprising: S100. Obtain the structural parameters of multi-story buildings within the navigation area, including floor spacing, floor slab thickness, elevator shaft and pipe shaft distribution information, and construct a vertical structural model V. S200: Deploy multiple Bluetooth beacons at designated locations on each floor within the navigation area, record the preset floor number L, deployment coordinates P, and signal power reference value R0 for each Bluetooth beacon, and construct a Bluetooth beacon library B; S300: Receive the current signal strength value set RSSIset={r1,r2,...,ri,...,rn} uploaded by the mobile terminal, where each ri corresponds to a Bluetooth beacon bi∈B; S400: Based on the signal strength, the spatial distance between each Bluetooth beacon is calculated, and combined with the beacon deployment coordinates P, a two-dimensional positioning coordinate Pos2D is constructed. S500. Based on the signal strength and the floor penetration path in the structural model V, calculate the vertical floor penetration probability value Pcrossi corresponding to each signal ri, and construct the floor penetration feature vector F={Pcross1,Pcross2,...,Pcrossi,...,Pcrossn}. S600. If any Pcrossi in F is greater than the preset threshold T, it is determined that there is interlayer interference and proceeds to S700; otherwise, proceeds to S800. S700: Based on the floor where the beacon bmax corresponding to the largest value in the layer-crossing feature vector F is located, compare it with the floor number L' corresponding to the current Pos2D. If the floor number difference ΔL is greater than or equal to 1, then perform vertical floor correction on Pos2D, generate the corrected positioning coordinates Pos3D, and proceed to S900. S800, Expand Pos2D to the three-dimensional positioning coordinates Pos3D of the default floor number L; The S900 uses Pos3D for path planning and outputs navigation commands to achieve dynamic correction of the Bluetooth navigation path.

[0007] Preferably, constructing the vertical structural model V includes the following steps: S101. Collect the building structure information of each floor in the target building, including floor number, floor spacing, floor slab material and thickness data, and generate the floor structure parameter set LSP; S102. Based on the floor structure parameter set LSP, extract the spatial distribution information including elevator shafts, pipe shafts and ventilation shafts, and establish a set of through-floor passages PCP. S103. Based on the floor number and the set of passageways PCP, calculate the signal propagation path weight of each penetrating component in the vertical direction, and construct the signal penetration factor matrix M in three-dimensional space. S104. The floor structure parameter set LSP is fused with the signal penetration factor matrix M to generate a structural model V that reflects the vertical structure and signal propagation characteristics.

[0008] Preferably, the construction of the two-dimensional positioning coordinates Pos2D includes the following steps: S401. Based on each signal strength value ri in the Bluetooth signal strength value set RSSIset and its corresponding signal power reference value R0i, calculate the spatial distance di between the mobile terminal and the Bluetooth beacon bi using the path loss model. S402. Based on the deployment coordinates Pi=(xi, yi) of each Bluetooth beacon bi, the corresponding spatial distance di is used as a weight parameter to construct a weighted geometric positioning model. S403. Solve for all spatial distances di and deployment coordinates Pi using the weighted least squares method to obtain the two-dimensional positioning coordinates Pos2D=(x, y) of the mobile terminal on the current floor.

[0009] Preferably, the calculation of the vertical cross-layer probability value Pcrossi corresponding to each signal ri includes the following steps: S501. Calculate the signal propagation distance di based on the signal strength value ri and the corresponding beacon's signal power reference value R0i, combined with the path loss model. S502. Project the signal propagation distance di onto the structural model V, and establish a hypothetical layer-crossing path from the current positioning coordinates Pos2D along the vertical direction. S503. Based on the thickness of each floor slab along the penetration path, the set of penetration channels, and the signal penetration factor matrix M, calculate the attenuation matching degree of the signal along the path. S504. Normalize and compare the signal propagation distance di with the cumulative attenuation value corresponding to each layer-crossing path in the model, fit the error probability using a Gaussian distribution function, and output the layer-crossing probability value Pcrossi of the signal in the vertical direction.

[0010] Preferably, the vertical floor correction of Pos2D includes the following steps: S701. Select the element Pcrossmax with the largest cross-layer probability value in the cross-layer feature vector F, and extract the corresponding floor number Lmax of its corresponding beacon bmax. S702. Calculate the floor number difference based on the floor number L′ corresponding to the current two-dimensional positioning coordinates Pos2D. ; S703. If ΔL is greater than or equal to 1, it is determined that there is a floor misjudgment. Based on L, the original positioning coordinates Pos2D are projected to the corresponding floor to generate the corrected three-dimensional positioning coordinates Pos3D = (x, y, Lmax).

[0011] Preferably, the dynamic correction of the Bluetooth navigation path includes the following steps: S901: Receive the target location coordinates Postarget set by the user, and combine them with the three-dimensional positioning coordinates Pos3D to determine the spatial relationship between the navigation start point and the end point. S902. Construct a path map model based on the internal spatial topology of the building, where nodes represent the center point of the functional area, edges represent the path, and edge weights are weighted according to the travel distance, congestion level, and accessibility. S903. The three-dimensional Dijkstra algorithm is used to calculate the shortest reachable path from Pos3D to Postarget, and a structured path sequence Pathseq is generated. S904. Parse the orientation, turning, and layer-changing actions corresponding to each node in Pathseq into navigation semantic commands and output them to realize dynamic correction and real-time guidance of positioning offset during path guidance.

[0012] The present invention also provides a Bluetooth-based positioning and navigation system, comprising: The building structure modeling module obtains multi-story building structure parameters within the navigation area, including floor spacing, floor slab thickness, elevator shaft and pipe shaft distribution information, and constructs a vertical structural model V. The Bluetooth beacon deployment module deploys multiple Bluetooth beacons at predetermined locations on each floor within the navigation area, records the preset floor number L, deployment coordinates P, and signal power reference value R0 for each Bluetooth beacon, and constructs a Bluetooth beacon library B. The signal acquisition and uploading module receives the current signal strength value set RSSIset={r1,r2,...,ri,...,rn} uploaded by the mobile terminal, where each ri corresponds to a Bluetooth beacon bi∈B; The two-dimensional positioning calculation module calculates the spatial distance between each Bluetooth beacon based on the signal strength and combines it with the beacon deployment coordinates P to construct the two-dimensional positioning coordinates Pos2D. The floor penetration interference analysis module calculates the vertical floor penetration probability value Pcrossi corresponding to each signal ri based on the signal strength and the floor penetration path in the structural model V, and constructs the floor penetration feature vector F={Pcross1,Pcross2,...,Pcrossi,...,Pcrossn}. The inter-floor interference judgment module determines that inter-floor interference exists if any Pcrossi in F is greater than the preset threshold T, and then proceeds to the floor correction module; otherwise, it proceeds to the floor supplementation module. The floor correction module compares the floor where the beacon bmax, which has the largest value in the floor feature vector F, is located with the floor number L' corresponding to the current Pos2D. If the floor number difference ΔL is greater than or equal to 1, the vertical floor correction is performed on Pos2D, and the corrected positioning coordinates Pos3D are generated and then the module enters the instruction output module. The floor supplement module expands Pos2D to the three-dimensional positioning coordinates Pos3D of the default floor number L. The command output module performs path planning based on Pos3D and outputs navigation commands to achieve dynamic correction of the Bluetooth navigation path.

[0013] The technical effects and advantages provided by the present invention in the above technical solution are as follows: 1. This invention provides a Bluetooth-based positioning and navigation method. By constructing a vertical structural model that includes floor structure information and penetration characteristics, and combining Bluetooth signal strength-based positioning with floor penetration probability calculation, it can effectively identify floor misjudgments caused by signal penetration through vertical channels such as floor slabs and elevator shafts in multi-story buildings. Compared with existing methods that rely solely on RSSI signal strength for planar positioning, this invention introduces spatial structural features and a probability inference mechanism, enabling proactive identification and correction of floor misjudgments, and greatly improving the accuracy of three-dimensional spatial positioning.

[0014] 2. This invention combines 3D path planning with semantic navigation command output mechanisms, enabling it to automatically generate optimal navigation paths across floors after positioning correction and dynamically adjust guidance content based on real-time location, adapting to navigation needs in complex indoor environments. This technical solution offers advantages such as accurate positioning, intelligent navigation, and strong adaptability, significantly improving user navigation experience and spatial service efficiency. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0016] Figure 1 This is a flowchart of the method of the present invention.

[0017] Figure 2 This is a flowchart of the system modules of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1, please refer to Figure 1 As shown in this embodiment, a Bluetooth-based positioning and navigation method includes: S100. Obtain the structural parameters of multi-story buildings within the navigation area, including floor spacing, floor slab thickness, and distribution information of elevator shafts and pipe shafts, and construct a vertical structural model V.

[0020] Step S101: Collect structural information of each floor in the target building, including the following four types of data: floor number, floor spacing, floor slab material, and floor slab thickness. Floor number is used to establish the vertical sequence of the building space; floor spacing is the vertical distance between any two adjacent floors, in meters (m); floor slab material data includes reinforced concrete, precast slabs, steel structures, etc., which affect the signal penetration capability; floor slab thickness is recorded in centimeters (cm) and used to calculate the medium length of the penetration path.

[0021] The above four types of structural information are summarized by floor to construct a floor structure parameter set (LSP). This parameter set is represented in the form of a two-dimensional array, where each row corresponds to a floor, and the columns represent the floor number, spacing, material code (which can be converted into dielectric constant or attenuation factor), and thickness value, respectively.

[0022] Step S102: Based on the constructed floor structure parameter set LSP, further extract the vertical information of the through-floor passages. Specifically, this includes three types of components with penetrating characteristics: elevator shafts, pipe shafts, and ventilation shafts. By analyzing the architectural design drawings, obtain the specific coordinate positions of the above three types of components in the three-dimensional space of the building, including their start and end ranges, cross-sectional areas, and spatial continuity on each floor.

[0023] The spatial distribution information is categorized according to component type and location to establish a per-floor channel set (PCP). This set is a structured dataset, where each element represents a penetrating component and includes fields such as component type, starting floor, ending floor, cross-sectional center coordinates, penetration length, and area, which are used for subsequent signal propagation path calculations.

[0024] Step S103: Based on the floor number in the floor structure parameter set and the spatial extension range of each component in the floor passage set, calculate the influence of each penetrating component on the propagation path of the Bluetooth signal in the vertical direction, and construct the signal penetration factor matrix M.

[0025] The specific calculation method is as follows: For any pair of vertically adjacent or non-adjacent floors i and j, if there is a penetrating component k connecting the two floors, the propagation path weight Wijk is calculated. The calculation method is as follows: First, based on the cross-sectional area Ak, dielectric constant εk, and penetration length Lk of component k, the unit propagation loss value Dk of the path is calculated; second, combined with the center frequency f of the Bluetooth signal (in MHz), the penetration loss is represented by an exponential attenuation model, i.e., the propagation path weight. αk is the signal attenuation coefficient determined by the material εk and frequency f; if multiple components penetrate the same floor pair, the total weight is the weighted average of the weights of all components. The final constructed signal penetration factor matrix M is a three-dimensional matrix with dimensions of floor number × floor number × component number, used to represent the signal transmission capability between any floor pair through different component propagation paths.

[0026] Step S104: The floor structure parameter set LSP obtained in step S101 is fused with the signal penetration factor matrix M constructed in step S103 to generate a complete structural model V. This model uses each floor as a basic node to construct a graph structure of vertical propagation paths. The weight of each edge is provided by the value in matrix M to express the ease or difficulty of signal propagation through each penetration path between different floors.

[0027] The specific fusion method is as follows: When constructing the 3D graph model, the floor number is used as the node number, and each effective weight Wijk in M ​​forms a directed edge from floor i to floor j. This structural graph is the structural model V, which can be used to calculate the layer-crossing probability in subsequent steps. The layer-crossing probability is the cumulative propagation probability of a signal crossing at least one edge outside the current floor in V, obtained by normalizing the sum of the path weights from all nodes on the current floor to other nodes in the graph.

[0028] The structural model V constructed in the above manner can accurately reflect the propagation characteristics of Bluetooth signals in vertical building structures, providing a quantitative basis for subsequent assessment of positioning error risk.

[0029] S200: Deploy multiple Bluetooth beacons at designated locations on each floor within the navigation area, record the preset floor number L, deployment coordinates P, and signal power reference value R0 corresponding to each Bluetooth beacon, and construct a Bluetooth beacon library B.

[0030] In this embodiment, a hospital outpatient building with a 5-story structure is selected as the deployment target. Its plan structure is rectangular, with a length of 60 meters, a width of 40 meters, and a floor height of 3.8 meters.

[0031] Within each floor, beacon deployment locations are selected based on pedestrian activity density, spatial complexity, and the distribution of main navigation paths (such as elevator lobbies, main corridors, and waiting areas). Priority is given to beacon deployment in the following three types of areas: At the intersection of elevator shaft and stairwell, ensure the integrity of the vertical floor change path signal; Improve the accuracy of planar positioning at main corridors and intersections; Improve navigation guidance accuracy around special function rooms (such as emergency rooms, operating rooms, and information desks).

[0032] Taking the deployment of 12 Bluetooth beacons on each floor as an example, ensure that the average spacing between the beacons is between 6 and 8 meters to cover the main passage areas of the entire floor, and uniformly deploy them at a height of 2.5 meters above the ground to avoid obstruction.

[0033] After each beacon deployment is completed, record the following three key parameters: Preset floor number L: This number corresponds to the actual floor where the beacon is deployed. It is numbered from L=1 to L=5 from bottom to top and is used for subsequent signal source attribution determination. Deployment coordinate position P: Represented by a two-dimensional coordinate system, with the origin set at the lower left corner of each floor plan, in meters (m). Each beacon position is recorded in the form of P=(x,y), with an accuracy of no less than 0.1 meters, to ensure accurate spatial reference in the navigation path; Signal power reference value R0: This refers to the average transmit power of the Bluetooth beacon measured at a straight-line distance of 1 meter in an unobstructed environment, measured in decibels per milliwatt (dBm). The measurement method involves recording signal strength data over 10 consecutive seconds using professional receiving equipment (such as a Bluetooth RSSI tester), calculating the average value, and denoting it as R0. This value will be used in practical applications to estimate the spatial distance between the user and the beacon.

[0034] The three parameters mentioned above are stored in a structured format to construct a Bluetooth beacon library B. Each beacon record is a triple: Bi = {Li, Pi, R0i}, where i is the beacon number, Li represents the floor, Pi is the deployment coordinate, and R0i is the signal power reference value. The entire beacon library B is an ordered set, represented as: B = {B1, B2, ..., Bn}, where n is the total number of deployed beacons, which in this embodiment is 5 floors × 12 = 60 Bluetooth beacons.

[0035] The Bluetooth beacon library B will serve as the reference information for signal feature matching and spatial location inference during the subsequent positioning process. It will be used to construct the correspondence between the actual signal received value and the preset signal source, and provide data support for subsequent two-dimensional positioning coordinate calculation and inter-layer interference judgment.

[0036] S300: Receive the current signal strength value set RSSIset={r1,r2,...,ri,...,rn} uploaded by the mobile terminal, where each ri corresponds to a Bluetooth beacon bi∈B.

[0037] After the deployment and construction of Bluetooth beacon library B are completed, in order to achieve real-time positioning of the user within the navigation area, it is necessary to receive and upload the currently detected Bluetooth signal strength data through the mobile terminal device. This step is the signal acquisition stage of this invention, which directly affects the subsequent positioning accuracy and layer recognition capability.

[0038] When a user's mobile terminal (such as a smartphone or wearable device equipped with a Bluetooth module) enables the Bluetooth scanning function, it periodically searches for signals of broadcast Bluetooth beacons in its vicinity and listens to the broadcast channel in a passive receiving mode.

[0039] In this embodiment, the signal sampling period is set to 1 second, meaning that signal data is received once per second, and each scan lasts for 300 milliseconds. Within each sampling period, the mobile terminal will receive signals from multiple Bluetooth beacons, each signal corresponding to a unique beacon number.

[0040] For each received signal, the mobile terminal extracts its signal source identifier (i.e., Bluetooth beacon number bi) and the corresponding received signal strength value ri. This signal strength value is expressed in the form of Received Signal Strength Indication (RSSI), with the unit being decibel-milliwatt (dBm). The value is usually negative, representing the degree of signal attenuation; the larger the absolute value, the weaker the signal.

[0041] All received signal strength values ​​are aggregated to construct the signal strength value set for the current sampling period: RSSIset={r1,r2,...,ri,...,rn}, where: ri represents the actual received signal strength value corresponding to the i-th beacon bi; bi∈B indicates that the signal strength comes from the beacon registered in the Bluetooth beacon library B; n is the number of Bluetooth beacons successfully received in the current sampling period, which is usually between 8 and 20, depending on the deployment density and environmental complexity.

[0042] To improve the stability of signal strength data, each ri is the average of multiple instantaneous values ​​received within the current sampling period. Specifically, a weighted average is performed on the m consecutive RSSI instantaneous values ​​received by each beacon within that period, calculated using the following formula: Where RSSIij is the instantaneous RSSI value received by the i-th beacon in the j-th sampling, and m is the number of samplings in a single cycle (e.g., 10 times). This processing method effectively reduces signal fluctuation interference caused by environmental transients and improves the reliability of signal input data.

[0043] After generating RSSIset, the mobile terminal uploads the set as positioning input parameters to the positioning calculation server or application processing unit. Each ri is mapped one-to-one with its corresponding beacon number bᵢ, forming a set of signal pairs: Spair={(b1,r1),(b2,r2),...,(bn,rn)}; this set will serve as the basic input data for subsequent steps such as two-dimensional positioning coordinate calculation (step S400), vertical floor crossing judgment (step S500), and final floor correction (step S700).

[0044] By implementing this step, we can achieve real-time perception and structured representation of the Bluetooth signal field in the user's current environment, providing reliable data support for accurate positioning and navigation path adjustment.

[0045] S400: Based on signal strength, the spatial distance to each Bluetooth beacon is calculated, and combined with the beacon deployment coordinates P, a two-dimensional positioning coordinate system Pos2D is constructed. The specific process includes the following steps: Step S401: For each signal strength value ri in the signal strength set RSSIset, there is a corresponding Bluetooth beacon bi in the Bluetooth beacon library B, which has a known signal power reference value R0i, that is, the transmission power value of the beacon at the standard distance (1 meter), in decibels milliwatts (dBm). In order to determine the spatial distance di between the mobile terminal and the Bluetooth beacon bi, the present invention uses the following path loss model for calculation: Where R0i is the reference signal strength value of the i-th Bluetooth beacon; ri is the actual signal strength of the beacon received by the mobile terminal; n is the path loss factor of the signal propagation environment, which is usually between 2 and 4. In this embodiment, n=3 is set according to the characteristics of building materials and experimental environment. This value has a good fit in actual tests in hospital buildings.

[0046] Using the above model, the received RSSI values ​​are converted into spatial distances, forming a distance set D={d1,d2,...,dn}, where each di is the estimated spatial distance between the Bluetooth beacon bi and the mobile terminal, in meters.

[0047] Step S402: Given the deployment coordinates Pi=(xi,yi) of each Bluetooth beacon bi, and combining them with the corresponding spatial distance di, a weighted geometric positioning model is constructed. This model draws a circular region centered on each beacon with radius di. The actual position of the mobile terminal should be near the intersection of these circular regions. To reduce the impact of measurement errors, this embodiment introduces a distance-inverse weighting mechanism, defining the positioning weight wi of each beacon as: This weighting function has the characteristic that the closer the distance, the higher the weight, which helps to enhance the positioning contribution of near-range signals and reduce the interference of far-range or weak signals.

[0048] Step S403: Based on the coordinate positions Pi=(xi,yi) and weight values ​​wi, the two-dimensional coordinate position of the mobile terminal is solved using the weighted least squares method. The solution process is as follows: Construct an objective function to minimize the sum of squared errors between the estimated location Pos2D=(x,y) and the actual distance di between the Euclidean distance to each beacon location Pi and the actual distance di. The objective function is expressed as: The gradient descent method is used to iteratively optimize and solve the above objective function, with the initial coordinates being the weighted average of all beacon coordinates. The iteration termination condition is: the coordinate change is less than 0.01 meters for two consecutive iterations, or the maximum number of iterations reaches 100.

[0049] The final converged coordinates are the two-dimensional positioning coordinates of the mobile terminal on the current floor, Pos2D=(x,y), in meters, with the origin of the coordinates corresponding to the lower left corner of the floor plan.

[0050] S500. Based on the signal strength and the floor penetration path in the structural model V, calculate the vertical floor penetration probability value Pcrossi corresponding to each signal ri, and construct the floor penetration feature vector F={Pcross1,Pcross2,...,Pcrossi,...,Pcrossn}.

[0051] To address the issue of vertical floor-penetration interference in Bluetooth signals within multi-story buildings, leading to mis-floor positioning, this invention establishes a structural model V, constructs a penetration path, and combines signal strength data to calculate the vertical floor-penetration probability value Pcrossi for each signal. Furthermore, it constructs a floor-penetration feature vector F for subsequent floor misidentification and location correction. Specifically, it includes the following steps: Step S501: Obtain the received Bluetooth signal strength value ri within the current positioning period, and combine it with the signal power reference value R0i of the corresponding Bluetooth beacon bi, to calculate the signal propagation distance di based on the path loss model. The path loss model used is defined as follows: Where n is the environmental path loss factor, the value of which is based on empirical parameters of the building environment. In this embodiment, n=3 is set, which is suitable for reinforced concrete structures in hospitals. The model calculates the propagation distance by comparing the difference between the reference signal and the actual received signal, and the result is in meters.

[0052] Step S502: Project each propagation distance di into the spatial frame of the structural model V, and establish a hypothetical floor-crossing path upward or downward along the vertical direction (Z-axis) starting from the current mobile terminal's two-dimensional positioning coordinates Pos2D=(x,y). The path is set as follows: in the vertical direction of Pos2D, it sequentially passes through the floor sequence defined by the building structural model V, simulating the path of other floor beacons that the signal may reach.

[0053] In each hypothetical path, the specific floor number, floor thickness, and whether it passes through the set of cross-floor passages (PCP) defined in V are recorded. This path serves as the basis for subsequent signal attenuation analysis.

[0054] Step S503: In the established hypothetical floor-crossing path, sequentially traverse the structural elements of each floor, and calculate the cumulative attenuation value Ai corresponding to the path by combining the material penetration loss value, channel penetration gain value, and other parameters recorded in the signal penetration factor matrix M. The specific calculation method is as follows: if the path crosses a conventional floor slab segment, a fixed attenuation coefficient α is introduced for each floor slab segment (for example, 10 cm of concrete causes a signal attenuation of 5 dB); if the path crosses a channel component in the floor-crossing channel set PCP, compensation or correction is introduced for this segment of the path according to the penetration gain factor γⱼ recorded in M; finally, the cumulative attenuation value Ai = ∑(α × thickness) – ∑(γj × path segment length), in decibels.

[0055] Step S504: Convert the signal propagation distance di calculated in step S501 into a theoretical propagation attenuation value Ti (in decibels). The calculation method is the same as in step S501, i.e. Then, the theoretical value is compared with the cumulative attenuation value Ai obtained in step S503. The error probability is fitted using a Gaussian distribution function to obtain the vertical penetration probability value Pcrossi of the signal. The probability calculation formula is: Where σ is the empirical standard deviation, which is set according to the actual fluctuation range of signal attenuation in multi-story buildings, and the unit is decibels. In this embodiment, σ = 6 dB.

[0056] The function takes the form of a standard normal distribution kernel function, reflecting the consistency between theoretical propagation and actual path attenuation. The higher the consistency, the closer Pcrossi approaches 1, indicating that the signal is highly likely to be a layer-crossing signal. Finally, the layer-crossing probability values ​​Pcrossi corresponding to each Bluetooth signal are combined to form a layer-crossing feature vector: F={Pcross1,Pcross2,...,Pcrossi,...,Pcrossn}; where n is the number of valid received signals in the current period, and F will serve as the key basis for subsequent judgment of layer-crossing interference and floor correction.

[0057] Through the above steps, this invention not only constructs a mechanism for evaluating the probability of each signal penetrating layers in the vertical direction, but also quantifies and structures spatial interference information through the penetrating feature vector F, providing reliable technical support for layer error detection and path correction.

[0058] S600. If any Pcrossi in F is greater than the preset threshold T, it is determined that there is interlayer interference and proceeds to S700; otherwise, proceeds to S800.

[0059] After constructing the layer-crossing feature vector F={Pcross1,Pcross2,...,Pcrossi,...,Pcrossn}, this invention further introduces an interference determination mechanism to identify whether there is vertical layer-crossing interference of Bluetooth signals within the current positioning period, thereby determining whether to perform floor correction processing on the positioning results. This determination process includes the following: To achieve quantitative judgment of inter-floor interference, this invention sets a preset threshold T as the identification standard for the signal's inter-floor probability value. This threshold indicates that if the Pcrossi corresponding to a certain signal exceeds this value, it means that the signal is likely not a Bluetooth beacon originating from this floor, but rather an interference signal received after penetrating other floors. The value of the threshold T is set according to the following principles: Statistical analysis of the average Pcrossi value of signals outside the current floor in multi-story building field tests; To balance the false positive rate and the false negative rate, a reasonable range is set to ensure that location correction is triggered only when necessary.

[0060] In this embodiment, referencing the actual deployment environment of a hospital setting, the threshold is set to T=0.75. This value indicates that when the probability of perforation is greater than 75%, the signal is considered to have a high probability of being a perforation signal.

[0061] Iterate through all probability values ​​Pcrossi in the layer-crossing feature vector F and perform the following judgment logic: If any Pcrossi>T exists, meaning a signal is identified as a floor-crossing interference signal, then it is considered that the current positioning status may have a risk of floor misjudgment, and the process immediately proceeds to step S700 to perform floor correction operation. If all Pcrossi≤T, then the current positioning result is considered to be unaffected by vertical floor crossing interference, the original floor judgment is maintained, and the process proceeds directly to step S800 to generate the final positioning coordinates.

[0062] This judgment process is implemented in the program using a loop comparison method, and the specific steps are as follows: Initialize the boolean variable CrossFlag to False; Iterate through each Pcrossi in vector F. If Pcrossi > T, set CrossFlag to True and break the loop. Determine the next processing path based on the state of CrossFlag: True: jump to step S700; False: jump to step S800.

[0063] Through this step, the present invention can identify potential inter-layer interference signals based on a probabilistic statistical mechanism and provide triggering conditions for subsequent floor correction, effectively improving the stability and accuracy of the positioning system in complex multi-layer environments.

[0064] S700: Based on the floor where the beacon bmax corresponding to the largest value in the layer-crossing feature vector F is located, compare it with the floor number L' corresponding to the current Pos2D. If the floor number difference ΔL is greater than or equal to 1, then perform vertical floor correction on Pos2D, generate the corrected positioning coordinates Pos3D, and proceed to S900.

[0065] Step S701: In the layer penetration feature vector F, traverse all elements and select the layer penetration probability element Pcrossmax with the maximum value. Its value reflects the Bluetooth signal that is most likely to be a layer penetration signal in the current cycle.

[0066] Simultaneously, the corresponding Bluetooth beacon bmax is obtained, and its preset deployment floor number Lmax in the Bluetooth beacon library B is read. This floor number represents the actual installation floor of the beacon and is used for subsequent vertical comparison and judgment.

[0067] Step S702: Based on the calculated two-dimensional positioning coordinates Pos2D=(x,y) within the current period, query the floor number L′ to which these coordinates belong. In this embodiment, a region mapping table is used to divide the building structure plane into two-dimensional spatial ranges of different floors, realizing the mapping from Pos2D to L′. Subsequently, the floor number difference ΔL is calculated, and the calculation method is as follows: Where Lmax represents the floor to which the interfering signal points, and L′ represents the floor where the current positioning result is located. If ΔL is less than 1, it means that the current positioning floor is the same as or adjacent to the floor where the maximum interference signal is located, which is considered normal; if ΔL is greater than or equal to 1, there may be a floor misjudgment.

[0068] Step S703: When the condition ΔL≥1 is met, the system determines that the current positioning result may be affected by the floor interference signal and the floor shift may occur, and the positioning coordinates need to be corrected.

[0069] The correction method is as follows: retain the original two-dimensional coordinate values ​​(x,y) and project them vertically into the three-dimensional space onto the floor plane represented by Lmax, thus generating three-dimensional positioning coordinates: Pos3D=(x,y,Lmax); where Lmax replaces the original positioning floor number L′ and is used to express the correction result of the current coordinates in the vertical direction.

[0070] The revised 3D coordinates Pos3D will serve as the starting point for subsequent navigation path planning and spatial guidance logic, improving the accuracy of floor identification and the continuity of navigation paths. This is particularly suitable for building structures with severe floor signal intersections.

[0071] S800, expand Pos2D to the three-dimensional positioning coordinates Pos3D of the default floor number L.

[0072] The two-dimensional positioning coordinates Pos2D=(x,y) are planar position data calculated by the weighted least squares method. The corresponding floor number L needs to be determined based on its spatial range.

[0073] To this end, this invention pre-establishes a floor space mapping table, defining the planar projection range of each floor as a two-dimensional coordinate region and assigning it a unique floor number. By finding the spatial region where the coordinates (x, y) of Pos2D fall, the corresponding default floor number L is retrieved. If Pos2D is simultaneously located at the boundary of two regions, the floor to which it belongs is determined using a signal-weighted average method.

[0074] After confirming the default floor number L, this value is used as the Z-axis coordinate and combined with the existing two-dimensional coordinates to generate a three-dimensional positioning coordinate: Pos3D=(x,y,L); where (x,y) represents the planar position within the floor, and L represents the default floor number to which the position belongs.

[0075] The generated 3D positioning coordinates Pos3D will be used as the starting positioning point input for the navigation engine to construct the path planning between the user's current location and the target location. Since no inter-layer interference was detected in the current cycle, Pos3D is considered a valid positioning result without signal interference and can be directly used for navigation rendering and path optimization.

[0076] Through this step, the present invention maintains positioning accuracy and processing efficiency while ensuring a simple and stable positioning process in the absence of inter-floor interference, effectively reducing unnecessary floor switching and improving the user's navigation experience in multi-story environments.

[0077] The S900 uses Pos3D for path planning and outputs navigation commands to achieve dynamic correction of the Bluetooth navigation path.

[0078] Step S901: Receive the target location coordinates Postarget=(xt,yt,Lt) set by the user in the navigation application. These coordinates are obtained from the preset location database after the user selects the destination (such as clinic, waiting area, entrance / exit, etc.) in the interface.

[0079] By comparing the spatial coordinates of Pos3D and Postarget, the horizontal and vertical distance relationship between them is determined, and it is determined whether cross-floor passage is involved, which serves as the basis for whether to introduce nodes such as elevators and stairs in subsequent path planning.

[0080] Step S902: Based on the structured design drawings inside the building, this invention constructs a spatial topology model G=(V,E), where: V is a set of nodes, representing the central reference coordinates of each functional area within the building, such as department entrances, elevator lobbies, corridor intersections, etc.; E is a set of edges, representing the walkable paths connecting the nodes, and each edge contains the following weight attributes: D: Euclidean distance between nodes, in meters; C: The congestion level of the current path segment is calculated by real-time pedestrian flow detection equipment, and the unit is a dimensionless value between 0 and 1; A: Path reachability factor, indicating whether the passage is passable (e.g., whether it is closed or temporarily prohibited).

[0081] Taking all the above factors into consideration, the weighted value of the path edge is defined as: W=D×(1+C)÷A; where A is 0, which means the path is not passable and will be removed from the graph; and A is 1, which means it is passable.

[0082] Step S903: Use the 3D Dijkstra algorithm to perform path search on the topology graph G, taking the nearest graph node where the 3D positioning coordinates Pos3D are located as the starting point and the node where Postarget is located as the ending point, and calculate the path with the minimum weight.

[0083] This algorithm adds floor information as a third dimension to the traditional two-dimensional Dijkstra's algorithm. Path search allows cross-floor connections between nodes, provided that the connecting passages (such as elevators and stairs) have valid edges in the graph. The cost of each path segment is the weight W of its corresponding edge, and the total path cost is the sum of the weights of all segments. After the algorithm is completed, it outputs a structured path sequence: Pathseq={v1,v2,...,vi,...,vk}; where each vi represents the coordinates and attributes of a path node, arranged in the actual traversal order.

[0084] Step S904: Parse each consecutive node pair in Pathseq and calculate the following semantic navigation instructions based on their spatial relationships: Orientation commands: Generate directional prompts such as "forward", "left", and "right" based on the angle between the coordinates of adjacent nodes; Turning instructions: Identify points of change in the path, such as corridor corners, and provide prompts such as "Turn ahead" or "Go straight". Floor change instruction: Identify the presence of elevator or stair nodes in the path, and generate prompts such as "Please go up to floor X" or "Please go down to floor X" based on the difference between the starting and target floor numbers.

[0085] The aforementioned semantic instructions are output in the form of structured data, including text content, direction vectors, and target node identifiers. They are displayed in conjunction with the mobile terminal navigation interface and can recalculate the path after the user's location deviates, enabling real-time correction and continuous guidance for dynamic changes in location.

[0086] Through this process, the present invention can quickly complete path planning and navigation command output after positioning correction, adapting to the dynamic navigation needs in complex multi-story buildings, and significantly improving the real-time performance, accuracy and user experience of the navigation system.

[0087] Example 2, please refer to Figure 2 As shown in this embodiment, a Bluetooth-based positioning and navigation system includes: The building structure modeling module obtains multi-story building structure parameters within the navigation area, including floor spacing, floor slab thickness, elevator shaft and pipe shaft distribution information, and constructs a vertical structural model V. The Bluetooth beacon deployment module deploys multiple Bluetooth beacons at predetermined locations on each floor within the navigation area, records the preset floor number L, deployment coordinates P, and signal power reference value R0 for each Bluetooth beacon, and constructs a Bluetooth beacon library B. The signal acquisition and uploading module receives the current signal strength value set RSSIset={r1,r2,...,ri,...,rn} uploaded by the mobile terminal, where each ri corresponds to a Bluetooth beacon bi∈B; The two-dimensional positioning calculation module calculates the spatial distance between each Bluetooth beacon based on the signal strength and combines it with the beacon deployment coordinates P to construct the two-dimensional positioning coordinates Pos2D. The floor penetration interference analysis module calculates the vertical floor penetration probability value Pcrossi corresponding to each signal ri based on the signal strength and the floor penetration path in the structural model V, and constructs the floor penetration feature vector F={Pcross1,Pcross2,...,Pcrossi,...,Pcrossn}. The inter-floor interference judgment module determines that inter-floor interference exists if any Pcrossi in F is greater than the preset threshold T, and then proceeds to the floor correction module; otherwise, it proceeds to the floor supplementation module. The floor correction module compares the floor where the beacon bmax, which has the largest value in the floor feature vector F, is located with the floor number L' corresponding to the current Pos2D. If the floor number difference ΔL is greater than or equal to 1, the vertical floor correction is performed on Pos2D, and the corrected positioning coordinates Pos3D are generated and then the module enters the instruction output module. The floor supplement module expands Pos2D to the three-dimensional positioning coordinates Pos3D of the default floor number L. The command output module performs path planning based on Pos3D and outputs navigation commands to achieve dynamic correction of the Bluetooth navigation path.

[0088] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A Bluetooth-based positioning and navigation method, characterized in that: include: S100. Obtain the structural parameters of multi-story buildings within the navigation area, including floor spacing, floor slab thickness, elevator shaft and pipe shaft distribution information, and construct a vertical structural model V. S200: Deploy multiple Bluetooth beacons at designated locations on each floor within the navigation area, record the preset floor number L, deployment coordinates P, and signal power reference value R0 for each Bluetooth beacon, and construct a Bluetooth beacon library B; S300: Receive the current signal strength value set RSSIset={r1,r2,...,ri,...,rn} uploaded by the mobile terminal, where each ri corresponds to a Bluetooth beacon bi∈B; S400: Based on the signal strength, the spatial distance between each Bluetooth beacon is calculated, and combined with the beacon deployment coordinates P, a two-dimensional positioning coordinate Pos2D is constructed. S500. Based on the signal strength and the floor penetration path in the structural model V, calculate the vertical floor penetration probability value Pcrossi corresponding to each signal ri, and construct the floor penetration feature vector F={Pcross1,Pcross2,...,Pcrossi,...,Pcrossn}. S600. If any Pcrossi in F is greater than the preset threshold T, it is determined that there is interlayer interference and proceeds to S700; otherwise, proceeds to S800. S700: Based on the floor where the beacon bmax corresponding to the largest value in the layer-crossing feature vector F is located, compare it with the floor number L' corresponding to the current Pos2D. If the floor number difference ΔL is greater than or equal to 1, then perform vertical floor correction on Pos2D, generate the corrected positioning coordinates Pos3D, and proceed to S900. S800, Expand Pos2D to the three-dimensional positioning coordinates Pos3D of the default floor number L; The S900 uses Pos3D for path planning and outputs navigation commands to achieve dynamic correction of the Bluetooth navigation path.

2. The Bluetooth-based positioning and navigation method according to claim 1, characterized in that: The construction of the vertical structural model V includes the following steps: S101. Collect the building structure information of each floor in the target building, including floor number, floor spacing, floor slab material and thickness data, and generate the floor structure parameter set LSP; S102. Based on the floor structure parameter set LSP, extract the spatial distribution information including elevator shafts, pipe shafts and ventilation shafts, and establish a set of through-floor passages PCP. S103. Based on the floor number and the set of passageways PCP, calculate the signal propagation path weight of each penetrating component in the vertical direction, and construct the signal penetration factor matrix M in three-dimensional space. S104. The floor structure parameter set LSP is fused with the signal penetration factor matrix M to generate a structural model V that reflects the vertical structure and signal propagation characteristics.

3. The Bluetooth-based positioning and navigation method according to claim 1, characterized in that: The construction of the two-dimensional positioning coordinates Pos2D includes the following steps: S401. Based on each signal strength value ri in the Bluetooth signal strength value set RSSIset and its corresponding signal power reference value R0i, calculate the spatial distance di between the mobile terminal and the Bluetooth beacon bi using the path loss model. S402. Based on the deployment coordinates Pi=(xi, yi) of each Bluetooth beacon bi, the corresponding spatial distance di is used as a weight parameter to construct a weighted geometric positioning model. S403. Solve for all spatial distances di and deployment coordinates Pi using the weighted least squares method to obtain the two-dimensional positioning coordinates Pos2D=(x, y) of the mobile terminal on the current floor.

4. The Bluetooth-based positioning and navigation method according to claim 1, characterized in that: The calculation of the vertical cross-layer probability value Pcrossi corresponding to each signal ri includes the following steps: S501. Calculate the signal propagation distance di based on the signal strength value ri and the corresponding beacon's signal power reference value R0i, combined with the path loss model. S502. Project the signal propagation distance di onto the structural model V, and establish a hypothetical layer-crossing path from the current positioning coordinates Pos2D along the vertical direction. S503. Based on the thickness of each floor slab along the penetration path, the set of penetration channels, and the signal penetration factor matrix M, calculate the attenuation matching degree of the signal along the path. S504. Normalize and compare the signal propagation distance di with the cumulative attenuation value corresponding to each layer-crossing path in the model, fit the error probability using a Gaussian distribution function, and output the layer-crossing probability value Pcrossi of the signal in the vertical direction.

5. The Bluetooth-based positioning and navigation method according to claim 1, characterized in that: The vertical floor correction of Pos2D includes the following steps: S701. Select the element Pcrossmax with the largest cross-layer probability value in the cross-layer feature vector F, and extract the corresponding floor number Lmax of its corresponding beacon bmax. S702. Calculate the floor number difference based on the floor number L′ corresponding to the current two-dimensional positioning coordinates Pos2D. ; S703. If ΔL is greater than or equal to 1, it is determined that there is a floor misjudgment. Based on L, the original positioning coordinates Pos2D are projected to the corresponding floor to generate the corrected three-dimensional positioning coordinates Pos3D = (x, y, Lmax).

6. The Bluetooth-based positioning and navigation method according to claim 1, characterized in that: The dynamic correction of the Bluetooth navigation path includes the following steps: S901: Receive the target location coordinates Postarget set by the user, and combine them with the three-dimensional positioning coordinates Pos3D to determine the spatial relationship between the navigation start point and the end point. S902. Construct a path map model based on the internal spatial topology of the building, where nodes represent the center point of functional areas, edges represent paths, and edge weights are weighted according to the travel distance, congestion level, and accessibility. S903. The three-dimensional Dijkstra algorithm is used to calculate the shortest reachable path from Pos3D to Postarget, and a structured path sequence Pathseq is generated. S904. Parse the orientation, turning, and layer-changing actions corresponding to each node in Pathseq into navigation semantic commands and output them to realize dynamic correction and real-time guidance of positioning offset during path guidance.

7. A Bluetooth-based positioning and navigation system for implementing the Bluetooth-based positioning and navigation method according to any one of claims 1-6, characterized in that: include: The building structure modeling module obtains multi-story building structure parameters within the navigation area, including floor spacing, floor slab thickness, elevator shaft and pipe shaft distribution information, and constructs a vertical structural model V. The Bluetooth beacon deployment module deploys multiple Bluetooth beacons at designated locations on each floor within the navigation area, records the preset floor number L, deployment coordinates P, and signal power reference value R0 for each Bluetooth beacon, and constructs a Bluetooth beacon library B. The signal acquisition and uploading module receives the current signal strength value set RSSIset={r1,r2,...,ri,...,rn} uploaded by the mobile terminal, where each ri corresponds to a Bluetooth beacon bi∈B; The two-dimensional positioning calculation module calculates the spatial distance between each Bluetooth beacon based on the signal strength and combines it with the beacon deployment coordinates P to construct the two-dimensional positioning coordinates Pos2D. The floor penetration interference analysis module calculates the vertical floor penetration probability value Pcrossi corresponding to each signal ri based on the signal strength and the floor penetration path in the structural model V, and constructs the floor penetration feature vector F={Pcross1,Pcross2,...,Pcrossi,...,Pcrossn}. The inter-floor interference judgment module determines that inter-floor interference exists if any Pcrossi in F is greater than the preset threshold T, and then proceeds to the floor correction module; otherwise, it proceeds to the floor supplementation module. The floor correction module compares the floor where the beacon bmax, which has the largest value in the floor feature vector F, is located with the floor number L' corresponding to the current Pos2D. If the floor number difference ΔL is greater than or equal to 1, the vertical floor correction is performed on Pos2D, and the corrected positioning coordinates Pos3D are generated and then the module enters the instruction output module. The floor supplement module expands Pos2D to the three-dimensional positioning coordinates Pos3D of the default floor number L. The command output module performs path planning based on Pos3D and outputs navigation commands to achieve dynamic correction of the Bluetooth navigation path.

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