An indoor three-dimensional positioning system and method based on UWB equipment

Abstract

The invention discloses an indoor three-dimensional positioning system based on UWB equipment, including a communication module; a data analysis module; an algorithm module; a three-dimensional module rendering module and an Internet of Things module; the communication includes a module PoE switch and a router, the data analysis module includes a time synchronization node and at least four UWB base stations, and positioning tags corresponding to the UWB base stations, and any three of the UWB base stations are not co-linear, and any four base stations are not co-planar; the UWB tag is installed on the positioning object, and multiple UWB base stations are connected to a PC terminal as a server through a PoE switch and a router, and the positioning tag sends the UWB signal to the UWB base station through a wireless communication module; and also includes a power separator as a base station power supply terminal. The system combines the corresponding three-dimensional positioning method to realize the three-dimensional positioning of a specific building, and displays the relevant information in a three-dimensional form, presenting a real, three-dimensional living world, solving the problems of poor positioning accuracy and lack of interaction and linkage in the existing indoor positioning system.

Description

Technical Field

[0001] The present invention relates to the field of indoor positioning technology, and in particular to an indoor three-dimensional positioning system and method based on UWB equipment. Background Art

[0002] At present, the positioning industry at home and abroad is developing rapidly, and related technologies and related businesses are growing continuously. However, looking at the current applications and services related to positioning, they are basically stuck in the two-dimensional plane, that is, they can only provide X and Y coordinates, and related information can only be presented in a flat way. Lack of interaction, lack of linkage, and most importantly, it is far from people's actual life and cannot present a real, three-dimensional world of life. There are many reasons for this situation. Generally speaking, the main reasons are as follows: 1) Insufficient market drive: According to research information, the current market demand is all based on the 2D plane, resulting in insufficient R&D investment by various companies in three-dimensional positioning, and no mature equipment and systems have been launched to the market. 2) Insufficient hardware support: For example, in terms of Bluetooth positioning, there are only a handful of SoCs in the world that can support the Bluetooth 5.1 protocol. Foreign companies that produce Bluetooth 5.1 chips include: TI Texas Instruments, Silicon Labs, Dialog, Nordic and a few other companies. UWB positioning devices face the same shortcomings. 3) Insufficient algorithm research and development: The current mainstream positioning methods include Bluetooth and UWB technologies. In actual applications, the production and testing of hardware equipment will produce certain errors, which will affect the positioning accuracy and stability. How to reduce the impact of errors requires specific algorithms to deal with. The research of related algorithms requires research units to invest a certain amount of funds and manpower. 4) Insufficient experience in multi-technology integration solutions: Positioning perception, as a terminal device of the Internet of Things, provides location-based services. How to integrate location services with third parties to establish an ecological solution. This is one of the problems facing the current positioning service industry. Various application scenarios such as smart campuses, smart cities, and smart construction sites have their own focus. Location-based services need to be able to integrate applications in various environments in order to develop in the long run. Summary of the invention

[0003] The purpose of the present invention is to provide an indoor three-dimensional positioning system and method based on UWB devices to solve the problem that the current indoor positioning technology proposed in the above background technology basically remains in a two-dimensional plane, cannot present a real three-dimensional living world, and lacks interaction and linkage.

[0004] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an indoor three-dimensional positioning system based on UWB equipment, characterized in that it includes a communication module for communicating with a positioning base station; a data parsing module responsible for parsing, analyzing and filtering positioning data; an algorithm module for calculating three-dimensional coordinates according to the parsed data; a three-dimensional module rendering module for constructing a three-dimensional scene and an Internet of Things module for publishing location information to a third party based on the MQTT protocol; the communication includes a module PoE switch and a router, the data parsing module includes a time synchronization node and at least four UWB base stations, and positioning tags corresponding to the UWB base stations one by one, and any three of the UWB base stations are not in the same line, and any four base stations are not in the same plane; the UWB tag is installed on the positioning object, and the multiple UWB base stations are connected to a PC terminal as a server through the PoE switch and the router, and the positioning tag sends the UWB signal to the UWB base station through the wireless communication module; and it also includes a power separator as a base station power supply terminal.

[0005] Preferably, an antenna for signal enhancement is also included.

[0006] An indoor three-dimensional positioning method based on UWB equipment, using a mountain mouse indoor three-dimensional positioning system based on UWB equipment, characterized in that it includes the following steps:

[0007] Step 1: UWB equipment installation: Install at least four UWB base stations around the target building to be located, and place the positioning tag within the base station signal coverage range. There should be no walls, metal, glass or any other buildings that can block the signal between the positioning base station, synchronization base station and positioning tag.

[0008] Step 2: Positioning data collection; custom protocol, according to which the original positioning data is assembled on the client side and then sent to the PC terminal as the server;

[0009] Step 3: Parsing and filtering positioning data: According to the message obtained in step 2, parse it according to the custom format, write code based on the object-oriented method, store the parsed data in the TagEntity class, and then group and store the data based on the tag ID + data sequence;

[0010] Step 4: Calculate the three-dimensional coordinates according to the UWB algorithm; specifically including:

[0011] 1) Use the TDOA method, i.e., the method based on the time difference of received signals, for positioning; first, select a reference base station. As shown in step 1, this device sets the reference base station as the origin of the spatial coordinate system. Secondly, synchronize all base stations through synchronization nodes, and measure the time difference between the signal of the positioning tag to the reference base station and to other base stations. Finally, according to the fixed coordinates of the base station and the required TDOA value, the three-dimensional coordinates of the positioning tag can be obtained by simultaneous equations. Its hyperbolic mathematical model is: Assuming that the tag coordinates are Tag (x, y, z), the coordinates of the positioning base station are S1 (x1, y1, z1), S2 (x2, y2, z2), S3 (x3, y3, z3), S4 (x4, y4, z4). The time when the positioning tag sends the positioning signal is Tstart, and Ti is the time when the base station Si receives the signal (i is 1, 2, 3, 4). The base station numbered 1 is taken as the reference base station, and the distance difference from the i-th positioning base station to the reference base station is Di1 (i is 2, 3, 4). Based on the above information, we can get the hyperbolic equations:

[0012]

[0013] Where c is the propagation speed of the signal in the air, which is the speed of light. By combining the above equations, the three-dimensional coordinates of the tag can be obtained;

[0014] 2) Clock synchronization; the time synchronization node periodically sends synchronization information to two of the at least four UWB base stations, the two base stations are base station A and base station B, assuming that the timestamp of the first synchronization message sent by the time synchronization node is Tx1, the timestamp of base station A receiving the synchronization node is ARx1, and the timestamp of base station B receiving the synchronization node is BRx1. The timestamp of the second synchronization message sent by the synchronization node is Tx2, the timestamp of base station A receiving the synchronization node is ARx2, and the timestamp of base station B receiving the synchronization node is BRx2. Similarly, the tag also periodically sends positioning information to base station A and base station B, assuming that the timestamp of the positioning signal arriving at base station A is Ta, and the timestamp of arriving at base station B is Tb. At this point, the sending time difference / clock number can be obtained: Tx2-Tx1, and the receiving time difference / clock number at base station A is ARx2-ARx1. The time difference between the time when base station A receives the tag positioning signal and the time when the base station first receives the synchronization information is: Ta-ARx1. According to the above three time differences, the tag positioning signal can be mapped to the time of the synchronization node to achieve time clock synchronization, then:

[0015] Ta'=(ARx2-ARx1) / (Tx2-Tx1)*(Ta-ARx1), similarly

[0016] Tb'=(BRx2-BRx1) / (Tx2-Tx1)*(Tb-BRx1)

[0017] All base stations organize the information according to the received timestamps and send them to the host computer in order. The host computer then performs unified calculations and finally solves the distance difference.

[0018] 3) Use the TDOA algorithm and weighted least squares method to achieve accurate positioning solution; the distance from the positioning tag to the i-th base station is Di. According to the principle of geometry, the following expression can be obtained:

[0019]

[0020] According to the UWB hardware, the distance difference Di1 from the i-th tag to the reference base station can be obtained. That is:

[0021] D i1 =D i -D1 (2)

[0022]

[0023] By transforming formula (2), we can get:

[0024] D i1 +D1=D i (4)

[0025]

[0026] Combining expressions (3) and (6), we can obtain:

[0027]

[0028] in:

[0029] Substituting the values ​​of i as 2, 3, and 4 into equation (7), we can obtain:

[0030]

[0031] According to formula (8), x, y, z can be replaced by formula (1) of x, y, z to obtain the value of D1. By eliminating illegal values ​​based on prior estimates, the solution of x, y, z can be obtained.

[0032] Continue to use 5 or more base stations to achieve accurate positioning

[0033] Generally, weighted least squares method is used to make full use of redundant information. The specific steps are as follows:

[0034] Let i = 1 and substitute into equation (1), we get:

[0035]

[0036] Subtracting (9) from (1) and combining (6) yields:

[0037]

[0038] make is an unknown vector, and a linear equation system with Za as a variable is established from equation (10):

[0039] h=GaZa(11)

[0040] Then the error vector of MS is: ψ=hG a z′ a .in,

[0041]

[0042] By performing WLS calculation on formula (11), we can obtain:

[0043]

[0044] Where φ=c 2 BQB is the covariance matrix of the error vector, c is the propagation speed of the signal in the air, which is the speed of light, Q is the TDOA covariance matrix, B = diag (D1, D2, ..., D M ). D1,D2,…,D M is an unknown quantity, so φ is also an unknown quantity. At this time, z cannot be directly calculated. a . Use the covariance matrix Q to approximate φ. We get:

[0045]

[0046] At this point, we can get the first approximate estimate of za. Using this estimate, we can reconstruct the error equations for WLS solution. Because of the correlation between za and x, y, z and Di, we have:

[0047] z a1 =x′+e1; z a2 =y′+e2; z a3 =z′+e3; z a4 =D′1+e4;

[0048] The linear equations are re-established as follows:

[0049]

[0050] in, The calculation method is similar to the first WLS, and the final result is as follows:

[0051]

[0052] Based on the prior information, the position of the positioning tag can be obtained;

[0053] Step 5: Iterative optimization of positioning accuracy; specifically including:

[0054] 1) Assume that the timestamp of the tag information number arriving at each base station is Ti (i is 1, 2, ...N);

[0055] 2) According to step 1, the location of each positioning base station and synchronization base station is known, according to the distance formula between two points in space:

[0056]

[0057] The distance difference between each positioning base station and the synchronization base station can be obtained, which is recorded as (i is 1, 2...N);

[0058] 3) Given the clock cycle of the hardware, the flight distance of the signal in one time cycle is: D = c* (c is the propagation speed of the signal in the air, taking the speed of light)

[0059] 4) Combining the information of steps 2 and 3, the number of clock cycles required for the signal of the synchronization base station to reach each positioning base station can be obtained:

[0060] (i=1,2…N)

[0061] 5) Assuming that base station 1 is the reference base station, the distance difference between the tag positioning signal reaching the reference base station and other base stations is:

[0062] T1+-(i=2,3…N)

[0063] Substituting this group into the positioning algorithm in step 4, a positioning coordinate can be obtained;

[0064] 6) Using different base stations as reference points, repeat step 5) to obtain N positioning coordinates, perform mean filtering, and finally obtain more accurate coordinates;

[0065] 7) Step 5: 3D scene rendering and control, using the open source OpenSceneGraph 3D rendering engine, using the scene tree method to manage the 3D scene, using logical groups to build the scene tree, and constructing the corresponding 3D scene.

[0066] Preferably, the positioning data uses the "$" symbol as a segment separator and ":" as an intra-segment separator, and assembles the positioning message identifier, base station number, message byte length, timestamp when the base station receives the first message sent by the synchronization node, timestamp when the synchronization node sends the first message, timestamp when the base station receives the second message sent by the synchronization node, timestamp when the synchronization node sends the second message, a sending identifier, a self-increasing unique sequence of tag sending data, tag ID, timestamp when the base station receives the tag, a check bit and a positioning message terminator.

[0067] Preferably, in step three, the positioning data filtering mainly includes 1) timestamp: when the positioning data received by the system exceeds the set time threshold, it is regarded as expired data and discarded; 2) number of positioning data: when performing three-dimensional positioning calculation, at least positioning data of 4 base stations are required. If the data reception is incomplete due to various reasons, this group of data should be discarded.

[0068] Compared with the prior art, the present invention has the following beneficial effects:

[0069] The indoor three-dimensional positioning system based on UWB equipment includes a communication module for communicating with a positioning base station; a data parsing module responsible for parsing, analyzing and filtering positioning data; an algorithm module for calculating three-dimensional coordinates based on the parsed data; a three-dimensional module rendering module for constructing three-dimensional scenes and an Internet of Things module for publishing location information to a third party based on the MQTT protocol; the system is used in combination with corresponding three-dimensional positioning methods to achieve three-dimensional positioning of specific buildings, and the relevant information is displayed in three-dimensional form, presenting a real, three-dimensional living world, which solves the problems of poor positioning accuracy and lack of interaction and linkage in existing indoor positioning systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 This is the overall architecture diagram of the indoor three-dimensional positioning system based on UWB equipment of the present invention;

[0071] Figure 2 This is a flow chart of an indoor three-dimensional positioning method based on a UWB device according to the present invention;

[0072] Figure 3 A schematic diagram of the connection structure of the indoor three-dimensional positioning system based on UWB equipment of the present invention;

[0073] Figure 4 Schematic diagram of communication connection of indoor 3D positioning system based on UWB equipment;

[0074] Figure 5 The figure is a schematic diagram of the TDOA algorithm principle of an indoor three-dimensional positioning method based on UWB equipment of the present invention.

[0075] Figure 6 A basic principle diagram of a synchronization node of an indoor three-dimensional positioning method based on a UWB device of the present invention;

[0076] Figure 7 A flow chart of the method for three-dimensional scene rendering and control of the present invention;

[0077] Figure 8 A schematic diagram of the arrangement of four base stations of an indoor three-dimensional positioning system based on a UWB device according to the present invention;

[0078] Fig. 9 The figure is a flowchart of positioning data parsing and filtering for an indoor three-dimensional positioning method based on UWB equipment. DETAILED DESCRIPTION

[0079] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0080] See also Figure 1 The present invention provides a technical solution: the system consists of five core modules: (1) communication module: responsible for communication with the positioning base station; (2) data parsing module: responsible for parsing, analyzing and filtering positioning data; (3) algorithm module: calculating three-dimensional coordinates based on the parsed data; (4) three-dimensional module rendering module: this module includes rendering of the three-dimensional model and real-time update rendering of the tag position; (5) Internet of Things module: based on the MQTT protocol, publishing location information to a third party.

[0081] The corresponding method includes the following steps: Step 1: UWB device installation. Step 2: Positioning data collection. Step 3: Positioning data analysis and filtering. Step 4: Three-dimensional positioning algorithm. Step 5: Iterative optimization of positioning accuracy. Step 6: Three-dimensional scene rendering and control.

[0082] Specifically: Step 1: UWB device installation

[0083] The positioning device is composed of UWB base station, UWB tag, PoE switch, power separator, router and some auxiliary materials. The equipment list is as follows:

[0084] Name Quantity Description

[0085]

[0086]

[0087] To expand the range of positioning, the positioning base station should be arranged as close to the perimeter of the building as possible. The positioning tag is placed within the coverage range of the base station signal. The synchronization base station can communicate with the positioning base station in all directions. The UWB positioning method is easily affected by environmental factors. Therefore, there should be no walls, metals, glass or other buildings between the positioning base station, the synchronization base station and the positioning tag to block the signal. This device is a three-dimensional positioning device, so at least 4 base stations are required. When actually laying out the base station positions, it is required that any three base stations are not in the same line and any four base stations are not in the same plane.

[0088] This device has 4 base stations, and the base station coordinates are: BS1 (0, 0, 0), BS2 (3.0, 0, 0), BS3 (0, 3.0, 0), BS4 (3.375, 3.90, 1.5), SyncBS1 (2.5, 2.0, 0), the unit is meter. Figure 8 .

[0089] The UWB base station and PC communicate via the network, and each base station is equipped with a network module. Before installation, you need to set the IP address of each base station, the server IP address, and the server port number in the code. The IP settings of this device are as follows:

[0090] Number IP address Short address

[0091] serial number IP address Short URL Base Station-1 192.168.21.10 0x0001 Base Station-2 192.168.21.11 0x0002 Base Station-3 192.168.21.12 0x0003 Base Station-4 192.168.21.13 0x0004 Synchronous base station 0x6666

[0092] The device connection diagram is shown in Figure 3.

[0093] Step 2: Positioning data collection

[0094] The positioning base station and the upper system of the PC use the connection-oriented TCP / IP protocol and the SOCKET communication method. The positioning base station is the client and the upper system of the PC is the server. The IP address and port number of the server must be defined in the embedded program of the positioning base station in advance. The communication connection diagram is shown in the figure below. Figure 4 shown.

[0095] The original positioning data is assembled on the client side according to the custom protocol and then sent. The positioning data uses the "$" symbol as a segment separator and the ":" symbol as a segment separator. The specific field definitions are shown in the following table.

[0096] Take “&&&:0002:76$B030CD689A:E4E1108400$B0EF3C9D13:E59F7E8400$T:27:1001$B0BD88B361$1A###” as an example for analysis.

[0097]

[0098]

[0099] Step 3: Location data analysis and filtering

[0100] According to the message obtained in step 2, parse it according to the custom format. Write the code based on the object-oriented method, store the parsed data in the TagEntity class, and then group and store the data based on the tag ID + data sequence.

[0101] This device has a total of 4 positioning base stations. Due to network communication reasons, the arrival time of data from each base station may not be completely synchronized. In addition, due to network or other reasons, packets may even be lost at times, so the received data needs to be filtered. The filtering mainly consists of two parts: 1. Timestamp: When the positioning data received by the system exceeds the set time threshold, it is regarded as expired data and discarded; 2. Number of positioning data: When performing three-dimensional positioning calculations, positioning data from at least 4 base stations is required. If the data reception is incomplete due to various reasons, the group of data should be discarded. The specific process is as follows: Figure 7 shown.

[0102] Step 4: 3D positioning algorithm

[0103] This patent adopts the TDOA method, that is, positioning based on the time difference of the received signal. First, select the reference base station. As shown in step one, this device sets the reference base station as the origin of the spatial coordinate system. Secondly, through the synchronization node, all base stations are time synchronized to measure the time difference between the signal of the positioning tag to the reference base station and to other base stations. Finally, according to the fixed coordinates of the base station and the required TDOA value, the three-dimensional coordinates of the positioning tag can be obtained by solving the simultaneous equations. Its principle is as follows: Figure 5 As shown:

[0104] According to the implementation principle of TDOA, a hyperbolic mathematical model is established. Assume that the tag coordinates are Tag (x, y, z), and the coordinates of the positioning base stations are S1 (x1, y1, z1), S2 (x2, y2, z2), S3 (x3, y3, z3), and S4 (x4, y4, z4). The time when the positioning tag sends the positioning signal is Tstart, and Ti is the time when the base station Si receives the signal (i is 1, 2, 3, 4). Take the base station numbered 1 as the reference base station, and the distance difference from the i-th positioning base station to the reference base station is Di1 (i is 2, 3, 4). Based on the above information, the hyperbolic equation group can be obtained:

[0105]

[0106] Where c is the propagation speed of the signal in the air, which is the speed of light. By combining the above equations, the three-dimensional coordinates of the tag can be obtained. According to the above equations, it is also confirmed that at least 4 base stations are required to solve the three-dimensional coordinates of the tag.

[0107] 2Clock Synchronization

[0108] According to the positioning method of TDOA, it can be divided into uplink TDOA and downlink TDOA. The difference between the two is shown in the following table:

[0109] Positioning method Features Function / Application

[0110] Uplink TDOA positioning base station receives the signal positioning of the positioning tag

[0111] Downlink TDOA positioning tag receives positioning base station signal positioning + navigation

[0112] According to the UWB positioning principle introduced above, without considering the external environment, the positioning accuracy is mainly affected by the time error and the base station positioning coordinate error. According to calculations, 1ns can produce an error of 30cm, and the time error will accumulate over time, causing the error to gradually increase. This device introduces synchronization nodes to minimize the impact of time errors. The basic principles are as follows:

[0113] The synchronization node periodically sends synchronization information to base stations A and B. Assume that the timestamp of the synchronization node sending the synchronization message for the first time is Tx1, the timestamp of base station A receiving the synchronization node is ARx1, and the timestamp of base station B receiving the synchronization node is BRx1. The timestamp of the synchronization node sending the synchronization message for the second time is Tx2, the timestamp of base station A receiving the synchronization node is ARx2, and the timestamp of base station B receiving the synchronization node is BRx2. Similarly, the tag also periodically sends positioning information to base stations A and B. Assume that the timestamp of the positioning signal arriving at base station A is Ta, and the timestamp of arriving at base station B is Tb. So far, the sending time difference / clock number can be obtained: Tx2-Tx1, and the receiving time difference / clock number at base station A is ARx2-ARx1. The time difference between the time when base station A receives the tag positioning signal and the time when the base station first receives the synchronization information is: Ta-ARx1. According to the above three time differences, the tag positioning signal can be "mapped" to the time of the synchronization node to achieve time clock synchronization.

[0114] Ta′=(ARx2-ARx1) / (Tx2-Tx1)*(Ta-ARx1), similarly

[0115] Tb′=(BRx2-BRx1) / (Tx2-Tx1)*(Tb-BRx1)

[0116] All base stations will organize the information according to the received timestamps and send them to the host computer in sequence. The host computer will then perform unified calculations and ultimately solve the distance difference.

[0117] 3 Positioning solution

[0118] There are two main positioning algorithms for TDOA: the Fang algorithm and the Chan algorithm. The core idea of ​​the Fang algorithm is to linearize the hyperbolic equations and ultimately obtain the estimated position of the tag. The disadvantage of this algorithm is that the positioning accuracy cannot be improved by adding positioning base stations. The calculation principle of the Chan algorithm is the same as that of the Fang algorithm, both of which solve the hyperbolic equation. The advantage of the Chan algorithm is that the positioning accuracy is high and the calculation amount is small when the environmental noise follows a Gaussian distribution, and the positioning accuracy can also be improved by adding base stations.

[0119] 3.14 Three-dimensional positioning of base stations

[0120] Refer to the setting of the base station location in the first section of the positioning principle in step 4. At the same time, assume that the distance from the positioning tag to the i-th base station is Di. According to the principle of geometry, the following expression can be obtained:

[0121]

[0122] According to the UWB hardware, the distance difference Di1 from the i-th tag to the reference base station can be obtained. That is:

[0123] D i1 =D i -D1 (2)

[0124]

[0125] By transforming formula (2), we can get:

[0126] D i1 +D1=D i (4)

[0127]

[0128] Combining expressions (3) and (6), we can obtain:

[0129]

[0130] in:

[0131] Substituting the values ​​of i as 2, 3, and 4 into equation (7), we can obtain:

[0132]

[0133] According to formula (8), x, y, z can be replaced by formula (1) of x, y, z to obtain the value of D1. By eliminating illegal values ​​based on prior estimates, the solution of x, y, z can be obtained.

[0134] 3.25 or more base stations for three-dimensional positioning

[0135] According to the information in Section 3.1, 4 base stations can just calculate the coordinates of the positioning tag. In actual applications, errors cannot be avoided, but certain technical means can be used to eliminate the impact of errors as much as possible. Using 5 base stations or more can achieve accurate positioning.

[0136] Generally, weighted least squares method is used to make full use of redundant information. The specific mathematical model is as follows:

[0137] Let i = 1 and substitute into equation (1) in Section 3.1, we get:

[0138]

[0139] Subtracting (9) from (1) and combining (6) yields:

[0140]

[0141] Let be the unknown vector, and establish a linear equation system with za as the variable from equation (10):

[0142] h=Gaza(11)

[0143] Then the error vector of MS is: ψ = h-Ga. Among them,

[0144]

[0145] By performing WLS calculation on formula (11), we can obtain:

[0146]

[0147] Where φ=c 2 BQB is the covariance matrix of the error vector, c is the propagation speed of the signal in the air, which is the speed of light, Q is the TDOA covariance matrix, B = diag (D1, D2, ..., D M ). D1,D2,…,D M is an unknown quantity, so φ is also an unknown quantity. At this time, z cannot be directly calculated. a , use the covariance matrix Q to approximate φ. We get:

[0148]

[0149] At this point, we can get the first approximate estimate of za. Using this estimate, we can reconstruct the error equations for WLS solution. Because of the correlation between za and x, y, z and Di, we have:

[0150] z a1 =x′+e1; z a2 =y′+e2; z a3 =z′+e3; z a4 =D′1+e4;

[0151] The linear equations are re-established as follows:

[0152]

[0153] in, The calculation method is similar to the first WLS, and the final result is as follows:

[0154]

[0155] Based on the prior information, the position of the positioning tag can be obtained.

[0156] Step 5: Iterative optimization of positioning accuracy

[0157] According to step 4, the timestamp from the tag to each base station can be solved. Combined with the previously known relevant information, N groups (N is the number of base stations) of positioning coordinates can be obtained with different base stations as reference points. The positioning accuracy can be further improved by weighting the coordinates. The detailed process is as follows.

[0158] 1. Assume that the timestamp when the tag information number arrives at each base station is Ti (i is 1, 2, ...N).

[0159] 2. According to step 1, the location of each positioning base station and synchronization base station is known, according to the distance formula between two points in space:

[0160]

[0161] The distance difference from each positioning base station to the synchronization base station can be obtained, which is recorded as (i is 1, 2...N).

[0162] 3. The clock cycle of the known hardware is recorded as, the flight distance of the signal in one time cycle:

[0163] D = c* (c is the propagation speed of the signal in the air, which is the speed of light)

[0164] 4. Combining the information of steps 2 and 3, we can get the number of clock cycles required for the signal of the synchronization base station to reach each positioning base station:

[0165] (i=1,2…N)

[0166] 5. Assuming that base station 1 is the reference base station, the distance difference between the tag positioning signal reaching the reference base station and other base stations is:

[0167] T1+-(i=2,3…N)

[0168] Substituting this group into the positioning algorithm, a positioning coordinate can be obtained.

[0169] 6. Using different base stations as reference points, repeat step 5 to obtain N positioning coordinates, perform mean filtering, and finally obtain more accurate coordinates.

[0170] Step 6: 3D scene rendering and control. The open source OpenSceneGraph 3D rendering engine is used. The engine uses a scene tree to manage 3D scenes and uses logical groups to build a scene tree for efficient rendering and traversal. It has the characteristics of high performance, portability, scalability, and rich data support. The update callback mechanism is used to control the nodes in the scene.

[0171] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An indoor three-dimensional positioning method based on UWB equipment uses an indoor three-dimensional positioning system based on UWB equipment, which includes a communication module for communicating with a positioning base station; a data parsing module responsible for parsing, analyzing, and filtering positioning data; and an algorithm module for calculating three-dimensional coordinates based on the parsed data; A three-dimensional module rendering module for constructing a three-dimensional scene and an Internet of Things module for publishing location information to a third party; the communication module includes a PoE switch and a router, the data analysis module includes a time synchronization node and at least four UWB base stations, and positioning tags corresponding to the UWB base stations one by one, and any three of the UWB base stations are not co-linear, and any four base stations are not co-planar. The UWB tags are installed on the positioning object, and the multiple UWB base stations are connected to the PC terminal as a server through the PoE switch and the router. The positioning tag sends the UWB signal to the UWB base station through the wireless communication module; it also includes a power separator as a base station power supply terminal, and also includes an antenna for signal enhancement, characterized in that, The following steps are involved: Step 1: UWB equipment installation: Install at least four UWB base stations around the target building to be located, and place the positioning tag within the base station signal coverage range. There should be no walls, metal, glass or buildings between the UWB base station, time synchronization node and positioning tag. Step 2: Positioning data collection; custom protocol, according to which the original positioning data is assembled on the client side and then sent to the PC terminal as the server; Step 3: Parsing and filtering positioning data: According to the message obtained in step 2, parse it according to the custom format, write the code based on the object-oriented method, store the parsed data in the TagEntity class, and then group and store the data based on the tag ID and data sequence; Step 4: Calculate the three-dimensional coordinates according to the UWB algorithm; specifically including: 1) Use the TDOA method, which is based on the time difference of received signals, for positioning; first, select a reference base station and set it as the origin of the spatial coordinate system. Second, synchronize all base stations through the time synchronization node, and measure the time difference between the signal of the positioning tag to the reference base station and to other base stations. Finally, according to the fixed coordinates of the base station and the required TDOA value, the three-dimensional coordinates of the positioning tag can be obtained by simultaneous equations. The hyperbolic mathematical model is: Assuming the tag coordinates are Tag (x, y, z), the coordinates of the positioning base station are They are S1(x1, y1, z1), S2(x2, y2, z2), S3(x3, y3, z3), S4(x4, y4, z4), then the time when the positioning tag sends the positioning signal is Tstart, Ti is the time when the base station Si receives the signal, where i is any value among 1, 2, 3, 4, and the base station numbered 1 is taken as the reference base station. The distance difference from the i-th positioning base station to the reference base station is Di1, where i is any value among 1, 2, 3, 4. Based on the above information, the hyperbolic equation group can be obtained: Where c is the propagation speed of the signal in the air. By taking the speed of light and combining the above equations, the three-dimensional coordinates of the tag can be obtained. 2) Clock synchronization; the time synchronization node periodically sends synchronization information to two of the at least four UWB base stations. Let the two base stations be base station A and base station B respectively. Assume that the timestamp of the first synchronization message sent by the time synchronization node is Tx1, the timestamp of base station A receiving the synchronization node is ARx1, the timestamp of base station B receiving the synchronization node is BRx1, the timestamp of the second synchronization message sent by the synchronization node is Tx2, the timestamp of base station A receiving the synchronization node is ARx2, and the timestamp of base station B receiving the synchronization node is BRx2. At the same time, the positioning tag also periodically sends positioning information to base station A and base station B. Assume that the timestamp of the positioning signal arriving at base station A is Ta, and the timestamp of arriving at base station B is Tb. At this point, the sending time difference / clock number can be obtained: Tx2-Tx1, the receiving time difference / clock number at base station A is ARx2-ARx1, and the time difference between the time when base station A receives the tag positioning signal and the time when the base station first receives the synchronization information is: Ta-ARx1; according to the above three time differences, the tag positioning signal can be mapped to the time of the synchronization node to achieve time clock synchronization, then: Ta'=(ARx2-ARx1) / (Tx2-Tx1)*(Ta-ARx1), Tb'=(BRx2-BRx1) / (Tx2-Tx1)*(Tb-BRx1) All base stations organize the information according to the received timestamps and send them to the host computer in order. The host computer then performs unified calculations and finally solves the distance difference. 3) Use the TDOA algorithm and weighted least squares method to achieve accurate positioning solution; the distance from the positioning tag to the i-th base station is Di; according to the principle of geometry, the following expression can be obtained: According to the UWB hardware, the distance difference Di1 from the i-th tag to the reference base station can be obtained; that is: D i1 =D i -D1 (2) By transforming formula (2), we can get: D i1 +D1=D i (4) Combining expressions (3) and (6), we can obtain: in: Substituting the values ​​of i as 2, 3, and 4 into equation (7), we can obtain: According to formula (8), x, y, z can be replaced by formula (1) of x, y, z to obtain the value of D1. According to the prior estimate, the illegal values ​​can be eliminated, and the solution of x, y, z can be obtained. Continue to use 5 or more base stations to achieve accurate positioning Generally, weighted least squares method is used to make full use of redundant information. The specific steps are as follows: Let i = 1 and substitute into equation (1), we get: Subtracting (9) from (1) and combining (6) yields: make is an unknown vector, and a linear equation system with Za as a variable is established from equation (10): h=GaZa (11) Then the error vector of MS is: ψ=hG a z′ a ,in, By performing WLS calculation on formula (11), we can obtain: Where φ=c 2 BQB is the covariance matrix of the error vector, c is the propagation speed of the signal in the air, which is the speed of light, Q is the TDOA covariance matrix, B = diag (D1, D2, ..., D M ), D1, D2, …, D M is an unknown quantity, so It is also an unknown quantity and cannot be directly calculated. We can use the covariance matrix Q to approximate it and get: At this point, we can get the first approximate estimate of za. Using this estimate, we can reconstruct the error equations for WLS solution. Because of the correlation between za and x, y, z, and Di, we have: z a1 =x′+e1;z a2 [y′+e2\z a3 [z′+e3;z a4 =D′1+e4; Among them, e1, e2, e3, e4 are z a The estimated error The linear equations are re-established as follows: in The calculation method is similar to the first WLS, and the final result is as follows: Based on the prior information, the position of the positioning tag can be obtained; Step 5: Iterative optimization of positioning accuracy; specifically including: 1) Assume that the timestamp of the tag information number arriving at each base station is Ti, where i = 1, 2, ..., N; 2) According to step 1, the location of each positioning base station and synchronization base station is known, according to the distance formula between two points in space: The distance difference between each positioning base station and the synchronization base station can be obtained, denoted as R i,s , where i = 1, 2, ..., N; 3) The clock cycle of the known hardware is recorded as H clock , the flight distance of a time period signal: D=c*H clock , where c is the propagation speed of the signal in the air, which is the speed of light; 4) Combining the information of steps 2 and 3, the number of clock cycles required for the signal of the synchronization base station to reach each positioning base station can be obtained: T is =R is / D where i = 1, 2, ..., N 5) Assuming that base station 1 is the reference base station, the distance difference between the tag positioning signal reaching the reference base station and other base stations is: Dis 1i =T1+T is -T i , where i = 1, 2, ..., N Dis 1i Substituting into the positioning algorithm in step 4, a positioning coordinate can be obtained; 6) Using different base stations as reference points, repeat step 5) to obtain N positioning coordinates, perform mean filtering, and finally obtain more accurate coordinates; Step 5: 3D scene rendering and control, using the open source OpenSceneGraph 3D rendering engine, using the scene tree method to manage the 3D scene, using logical groups to build the scene tree, and building the corresponding 3D scene.

2. The indoor three-dimensional positioning method based on UWB equipment according to claim 1, characterized in that: The positioning data uses the "$" symbol as a segment separator and ":" as an intra-segment separator, and assembles the positioning message identifier, base station number, message byte length, timestamp when the base station receives the first message sent by the synchronization node, timestamp when the synchronization node sends the first message, timestamp when the base station receives the second message sent by the synchronization node, timestamp when the synchronization node sends the second message, a sending identifier, a self-increasing unique sequence of tag sending data, tag ID, timestamp when the base station receives the tag, a check bit and a positioning message terminator.

3. The indoor three-dimensional positioning method based on UWB equipment according to claim 1, characterized in that: In step three, the positioning data filtering mainly includes 1) timestamp: when the positioning data received by the system exceeds the set time threshold, it is regarded as expired data and discarded; 2) the number of positioning data: when performing three-dimensional positioning calculation, at least 4 base station positioning data are required, and incomplete data will be discarded.

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