An Indoor Positioning Method for Suppressing Environmental and Hardware Errors

Abstract

The present invention discloses an indoor positioning method for suppressing environmental and hardware errors. It measures the distance information from the base station to the tag under the environmental conditions of using a UWB module to simulate a multi-base-station environment, and then transmits the distance information to the data processing terminal through a Bluetooth adapter. The positioning solution algorithm is used in the data processing terminal to calculate the measured distance. Then, the calibration method is used to optimize the values of multiple measured distances to eliminate part of the errors of the UWB module itself and the indoor environment, further improving the positioning accuracy of indoor positioning. Finally, real-time positioning tests are carried out under the same environmental conditions. Since the present invention realizes real-time positioning through existing equipment and only needs to be updated and optimized on the basis of the original equipment, there is no need to lay a large number of additional hardware devices. Compared with the prior art, the present invention has higher positioning accuracy and has great advantages and commercial prospects in application environments where high-precision measurement is required indoors.

Description

Technical Field

[0001] The present invention relates to the technical field of high-precision indoor positioning and navigation, and particularly to an indoor positioning method that suppresses environmental and hardware errors. Background Art

[0002] With the continuous improvement of the scientific and technological level, the current era is constantly developing, and various fields are showing a booming development trend. People's demand for location services is continuously increasing. Therefore, high-precision indoor positioning methods have become one of the current research hotspots. At present, through the Global Navigation Satellite System (GNSS), people can achieve sub-meter outdoor positioning accuracy outdoors, which has greatly enriched social daily life such as outdoor driving navigation and drone positioning. Therefore, positioning technology is used in all aspects of life. However, due to the occlusion of high-rise buildings, trees, etc. and the barrier of walls, the outdoor satellite signals can hardly propagate into the indoor. Therefore, the Global Navigation Satellite System cannot be used indoors for accurate positioning. According to relevant research data, people generally spend 70% - 90% of their time indoors, and people's demand for indoor positioning has increased sharply. For example, in geographical environments such as airports, stations, shopping malls, and large supermarkets, where the floors, walls, and decorations are relatively numerous, high-precision and highly reliable indoor positioning technology is needed to obtain accurate location information in these places. These demands have promoted the further development of indoor positioning technology.

[0003] Currently, the mainstream indoor technologies in China include WiFi, Bluetooth, inertial navigation, and Ultra-Wide Band (UWB). Among them, WiFi is based on triangulation positioning of signal field strength. Because the indoor environment is complex and changeable, and there is more non-line-of-sight information obtained at the same time, it is impossible to accurately establish a signal strength attenuation model, resulting in not very high positioning accuracy. The positioning technology of Bluetooth is easily interfered by external noise, and the signal stability is poor. The inertial navigation technology based on the dead reckoning method has cumulative drift errors, which affects the positioning accuracy. The positioning technology of Ultra-Wide Band (UWB) has a low power spectral density, narrow pulse width, and high time resolution for the pulse signal used to transmit data. Therefore, it can obtain sub-meter positioning accuracy in indoor positioning.

[0004] Nowadays, in the field of high-precision indoor positioning technology research, both intensity attenuation positioning and autonomous positioning have encountered bottlenecks at the meter-level accuracy and are difficult to break through. One of the main reasons for the bottleneck is the uncertainty of the intensity attenuation and distance empirical relationship and the susceptibility to indoor environment, as well as the non-linear growth of the error caused by the need for time integration in autonomous positioning, which accumulates over time. This is a weakness of the positioning technology itself. In-depth research on indoor positioning technology based on two-way ranging can also provide support for individual technologies to break through this bottleneck. However, due to the complex and variable indoor environment and the different environmental states in different scenarios, there are errors caused by hardware and environmental problems in the two-way ranging positioning method. In the existing indoor positioning technology based on two-way ranging, eliminating the influence and errors of hardware and environment has become the primary focus of solution. Only by eliminating the interference of hardware and different environments on positioning can the positioning accuracy of the indoor positioning system be improved. Summary of the Invention

[0005] The object of the present invention is to propose an indoor positioning method for suppressing environmental and hardware errors in view of the fact that indoor positioning signals based on two-way ranging are easily affected by errors existing in the hardware system itself and errors in different scenario environments. The method is to measure the distance information from the base station to the tag under the environmental conditions of multiple base stations, and then transmit the distance information to the data processing terminal through a Bluetooth adapter. The positioning solution algorithm is used in the data processing terminal to calculate the measured distance; then the calibration method is used to optimize the values of multiple measured distances obtained to eliminate part of the errors of the UWB module itself and the indoor environment, and further improve the positioning accuracy of indoor positioning hardware devices; finally, real-time positioning tests are carried out under the same environmental conditions. Since the present invention realizes real-time positioning through existing devices and only needs to be updated and optimized on the basis of the original devices, there is no need to lay a large number of additional hardware devices. Compared with the prior art, the present invention has higher positioning accuracy and has great advantages and commercial prospects in application environments where high-precision measurement is required indoors.

[0006] The object of the present invention is achieved as follows:

[0007] An indoor positioning method for suppressing environmental and hardware errors, the method comprising:

[0008] Step 1: Obtain prior information; First, set the UWB module as the corresponding positioning base station and mobile tag; then construct a positioning experimental environment composed of a positioning base station, a mobile tag, a Bluetooth adapter, and a data processing terminal; the positioning base station consists of several UWB modules set to "anchor"; the mobile tag consists of one UWB module set to "tag"; the Bluetooth adapter is the Bluetooth adapter ble112; in the positioning experimental environment, place the mobile tag "tag" at a point where both los and nlos are included during the signal transmission between the positioning base station and the mobile tag, and within the range surrounded by multiple base stations, and call this point the selected calibration point; after placement, the UWB module uses the TWR positioning engine in the "tag" mode. Under this engine condition, information is transmitted between the mobile tag and the positioning base station, and the time difference of information transmission between the positioning base station and the mobile tag is first calculated through the two-way two-way ranging method, and then the distance information obtained by the two-way two-way ranging method is calculated. At this time, hundreds of groups of test distance data are sampled, and finally, the distance data is transmitted to the data processing terminal through Bluetooth by the Bluetooth adapter, and the distance information from the mobile tag to each positioning base station at the calibration point is calculated;

[0009] Step 2: Solve the indoor positioning coordinates; Measure and calculate the actual distance from the mobile positioning tag to each positioning base station in the real environment; by comparing the distance information obtained by the data processing terminal with the measured actual distance information, and using the difference between the distance information and the actual distance information to compensate the distance information in the data processing terminal to eliminate the environmental and hardware errors in the indoor environment; the data processing terminal obtains the coordinates of the mobile tag by performing positioning calculation on the data, that is, obtains the coordinates of the calibration point where the mobile tag is located.

[0010] The time difference of information transmission between the positioning base station and the mobile tag is first calculated through the two-way two-way ranging method, and is specifically calculated by the following (1):

[0011]

[0012] The transmission is divided into two rounds. In the first round, UWB module A emits a pulse signal of request nature at time T on its timestamp, and UWB module B receives the signal at time T on its timestamp, and then processes the UWB signal. UWB module B emits signals of response nature and request nature simultaneously at time T, and this signal is received by UWB module A at its own timestamp T; among them, the time difference between UWB module B receiving and transmitting signals is denoted as Treply1; the time difference between the time when UWB module A receives the signal from UWB module B and the time when UWB module A sends the signal is Tround1; a1 moment, and UWB module B receives the signal at time T on its timestamp, and then processes the UWB signal. UWB module B emits signals of response nature and request nature simultaneously at time T, and this signal is received by UWB module A at its own timestamp T; among them, the time difference between UWB module B receiving and transmitting signals is denoted as Treply1; the time difference between the time when UWB module A receives the signal from UWB module B and the time when UWB module A sends the signal is Tround1; b1 moment, and then processes the UWB signal. UWB module B emits signals of response nature and request nature simultaneously at time T, and this signal is received by UWB module A at its own timestamp T; among them, the time difference between UWB module B receiving and transmitting signals is denoted as Treply1; the time difference between the time when UWB module A receives the signal from UWB module B and the time when UWB module A sends the signal is Tround1; b2 moment, and UWB module B emits signals of response nature and request nature simultaneously at time T, and this signal is received by UWB module A at its own timestamp T; among them, the time difference between UWB module B receiving and transmitting signals is denoted as Treply1; the time difference between the time when UWB module A receives the signal from UWB module B and the time when UWB module A sends the signal is Tround1; a2 moment; among them, the time difference between UWB module B receiving and transmitting signals is denoted as Treply1; the time difference between the time when UWB module A receives the signal from UWB module B and the time when UWB module A sends the signal is Tround1;

[0013] In the second round, the UWB module A processes the signal received at its own timestamp T a2 and then processes the UWB signal. The UWB module A simultaneously transmits signals of response nature and request nature at timestamp T a3 , and this signal is received by the UWB module B at its own timestamp T b3 . Among them, the time difference between the signal transmission and reception of the UWB module A is denoted as Trep1y2; the time difference between the time when the UWB module B receives the signal from the UWB module A and the time when the UWB module B transmits the signal is Tround2;

[0014] The calculated distance information obtained by using the two-way ranging method is specifically calculated by the following formula (2):

[0015] r = T * C (2)

[0016] where C is the speed of light, and r is the distance information from the mobile tag to a positioning base station calculated by using the two-way ranging method;

[0017] The data processing terminal obtains the coordinates of the mobile tag by performing positioning calculation on the data, which is calculated by the following formula (3):

[0018]

[0019] where (x, y) are the unknown coordinates of the mobile tag, and (x i , y i ) are the known coordinates of the positioning base station; among them, r i1 is the distance information from the mobile tag to the i-th positioning base station, which is known information;

[0020] Denote the left side of this system of equations as f i (x, y, x i , y i ), and the right side of the equation is the known quantity r i1 , denoted as m i , so the system of equations is abbreviated as the following formula (4)

[0021] f i (x, y, xi, y i ) = m i (4)

[0022] And let (x v , y v ) be the iterative initial value of the unknown coordinates (x, y) of the mobile tag, and (δ x , δ y ) be the difference between the unknown coordinates (x, y) of the mobile tag and the iterative value, that is, the following formula (5)

[0023] (x, y) = (x v , y v ) + (δ x , δ y ) (5)

[0024] Expand f i (x, y, x i , y i ) at (x v , y v ) to the second - order Taylor series and neglect the higher - order terms to obtain the following equation (6)

[0025]

[0026] Denote as a i1 , as a i2 , then the following equation (7) can be obtained

[0027]

[0028] After transposing equation (7) and writing it in matrix form, it is the following equation (8)

[0029]

[0030] where A, δ, z are respectively

[0031]

[0032] Use the weighted least - squares method to calculate δ

[0033] δ = [A T R -1 A] -1 A T R -1 z (9)

[0034] where R is the weight matrix of the weighted least - squares method. Here, the identity matrix is selected as the weight matrix; then add the values of the original (x v , y v ) to (δ x , δ y ) as the new (x v , y v ), repeat the above steps to solve for (δ x , δ y ), and iterate continuously until (x v , y v ) meets the accuracy requirements;

[0035] x v ← x v + δ x, y v ←y v +δ y (10)

[0036] That is, the uncompensated coordinate information is obtained through the above formula (10);

[0037] The difference between the distance information and the true distance information is represented by the following formula (11):

[0038] r i = r i1 - r i2 (11)

[0039] Where r i1 is the distance information of the mobile tag to the i-th positioning base station, and r i2 is the true distance information of the mobile positioning tag to the i-th positioning base station measured and calculated in the real environment; r i is the difference between the distance information and the true distance information;

[0040] Finally, the difference between the distance information and the true distance information obtained from formula (11) is added to the distance information in formula (3), and iterative calculations are continuously performed; finally, the coordinates of the calibration point where the mobile tag is located are obtained.

[0041] The positioning base station, as a fixed node for routing data between the UWB network and the IP network in the positioning system, receives a group poll message sent by the mobile tag. The group poll message includes: a position period and a list of several addresses of the positioning base stations used by the mobile tag for positioning; the group poll message is a broadcast message, and all positioning base stations within the range can receive the group poll message.

[0042] The distance data is transmitted to the data processing terminal via Bluetooth through the Bluetooth adapter, and a configuration location data and visualization interface are provided via the Web.

[0043] The TWR positioning engine, that is, the mobile tag operates in a response mode and broadcasts an ultra-wideband pulse signal containing the mobile tag ID information as a TAG positioning packet to the positioning base station at a frequency of 10 Hz.

[0044] The true distance information of the mobile positioning tag to each positioning base station is measured and calculated using a millimeter-level laser rangefinder.

[0045] Since the present invention realizes real-time positioning through existing devices and only needs to be updated and optimized on the basis of the original devices, there is no need to lay a large number of additional hardware devices. Compared with the prior art, the present invention has higher positioning accuracy and has great advantages and commercial prospects in application environments that require high-precision measurement indoors. Description of the Drawings

[0046] Figure 1 Schematic diagram of the positioning experimental environment constructed for the present invention;

[0047] Figure 2 Two-dimensional layout schematic diagram of the positioning base station and the mobile tag placement;

[0048] Figure 3 Schematic diagram of the uncorrected error result of the present invention;

[0049] Figure 4 Schematic diagram of the result of suppressing environmental and hardware errors of the present invention. Detailed implementation manners

[0050] The present invention will be further described in detail below through specific embodiments.

[0051] Refer to the appendix Figure 1 For the present invention, refer to the appendix Figure 1 For the present invention, it is implemented in a positioning system (i.e., a positioning experimental environment) composed of a positioning base station (one main base station 11 and three slave base stations 12), a mobile tag 2, a Bluetooth adapter 3, and a data processing terminal 4.

[0052] The mobile tag 2 sends a group poll message about its location period and a list of 4 addresses of the positioning base stations it hopes to locate. The group poll message is a broadcast message, so all positioning base stations (one main base station 11 and three slave base stations 12) within the range will receive it. Each positioning base station (one main base station 11 and three slave base stations 12) listed in each group poll will respond by sequentially sending a response message, and the sending time is determined by its position in the list. Then the mobile tag 2 collects information about the positioning base station 1 by listening to the beacon information. Once the mobile tag 2 receives an answer from the positioning base station (one main base station 11 and three slave base stations 12) and follows the IOT uplink / downlink sub-frame, it will continue to calculate the range from each positioning base station (one main base station 11 and three slave base stations 12) to it. If the mobile tag 2 obtains 3 or more valid ranges, it will use its internal position engine to calculate its distance. The positioning packets encapsulated in the data packets sent bilaterally and bidirectionally between the mobile tag 2 and the positioning base station (one main base station 11 and three slave base stations 12) are forwarded to the data processing terminal 4 through the Bluetooth adapter 3 by the mobile tag 2, and the data processing terminal 4 solves the linear equations to obtain the initial distance of the mobile tag 2. The actual precise distance is calculated by a laser rangefinder, and the difference is calculated between the two. The error is removed in the program, and finally the coordinates of the positioning tag 2 are obtained by using the positioning algorithm, and the final precise coordinates are obtained.

[0053] Embodiment

[0054] Refer to Figure 2, before the positioning process in this embodiment, four positioning base stations are installed indoors in advance. The positioning base stations are located at the four corners respectively. Among them, the main base station 11 is at the lower left vertex with a height of 1.817 m, and the three slave base stations 12 are at the other three corners with heights of 1.685 m, 2.521 m, and 1.754 m respectively. There are several desks and chairs placed in the middle of the area, and the acquisition height of the positioning tag is 0.758 m.

[0055] First, set the UWB module as the corresponding positioning base station and mobile tag; then construct a positioning experimental environment composed of a positioning base station, a mobile tag, a Bluetooth adapter, and a data processing terminal. The positioning base station consists of several UWB modules set as "anchor"; the mobile tag consists of one UWB module set as "tag"; the Bluetooth adapter is the Bluetooth adapter ble112; in the positioning experimental environment, place the mobile tag "tag" at a point where the transmission signal between the positioning base station and the mobile tag simultaneously includes los and nlos and is within the range surrounded by multiple base stations. This point is called the selected calibration point. After placement, the UWB module uses the TWR positioning engine in the "tag" mode. Under this engine condition, information is transmitted between the mobile tag and the positioning base station, and the time difference of the information transmission between the positioning base station and the mobile tag is calculated first through the two-way ranging method, and then the distance information obtained by the two-way ranging method is calculated. At this time, hundreds of groups of test distance data are sampled, and finally, the distance data is transmitted to the data processing terminal through Bluetooth by the Bluetooth adapter, and the distance information from the mobile tag to each positioning base station at the calibration point is calculated;

[0056] The specific positioning process is as follows:

[0057] a. Take the main positioning base station as the origin to establish a two-dimensional coordinate system for the positioning area. Use a laser rangefinder to measure the true coordinates of the main and slave positioning base stations. Place the mobile tag at the calibration point, connect the Bluetooth adapter to the terminal data processor, and sample hundreds of groups of test data to obtain the distance information from the corresponding mobile positioning tag to each positioning base station.

[0058] b. The data processor will store the distance information from the mobile tag to each positioning base station in the corresponding excel table, that is, obtain the distance between the tag and the base station calculated by the original hardware (TWR1, TWR2, TWR3, TWR4).

[0059] c. Take the main positioning base station as the origin, use a laser rangefinder to measure the distance of the mobile tag in the actual environment in the established two-dimensional coordinate system, and convert it into coordinate form. Calculate the distances from the tag to each base station (DIS1, DlS2, DIS3, DIS4) through the measured and converted base station and tag coordinates, and calculate the difference between the distances obtained by the original hardware calculation.

[0060] d. Compensate the calculated difference to the data processing terminal. Move the positioning tag and calculate the position information of the positioning tag in real time.

[0061] r 1 = DIS1 - TWR1

[0062] r 2 = DIS2 - TWR2

[0063] r 3 = DIS3 - TWR3

[0064] r 4 = DIS4 - TWR4

[0065] Where r 1 is the deviation between the measured value from the master base station to the positioning tag in the actual environment and the calculated value after being transmitted to the data processing terminal through the hardware. r 2 , r 3 , r 4 are respectively the deviations between the measured values from other slave base stations to the positioning tag and the calculated values after being transmitted to the data processing terminal through the hardware.

[0066] e. 1) After processing the error, test the result. The distance information (R1, R2, R3, R4) transmitted by the positioning tag to the data processing terminal.

[0067]

[0068]

[0069]

[0070]

[0071] Where (x, y) are the unknown coordinates of the tag, and (x i , y i ) are the known coordinates of the base station. At the same time, abbreviate the system of equations as f i (x, y, x i , y i ) = m i

[0072] 2) Obtain (x, y) = (x v , y v ) + (δ x , δ y ) according to the iterative relationship.

[0073] Substitute f i (x, y, x i , y i ) at (xv , y v ) Second-order Taylor expansion at and ignoring higher-order terms gives

[0074]

[0075] Denote as a i1 , as a i2 , then we can get

[0076]

[0077] 3) Rearrange the equation into matrix form

[0078]

[0079] 4) Where A, δ, and z are respectively

[0080]

[0081] Calculate δ using the weighted least squares method

[0082] δ = [A T R -1 A] -1 A T R -1 z

[0083] Where R is the weight matrix of the weighted least squares. Here, the identity matrix is chosen as the weight matrix.

[0084] 5) Add the values of the original (x v , y v ) to (δ x , δ y ) as the new (x v , y v ), and repeat the above steps to solve for (δ x , δ y ) and iterate continuously until (x v , y v ) meets the accuracy requirements.

[0085] x v ← x v + δ x , y v ← y v + δ y

[0086] f. Open the visualization interface to observe the movement status of the positioning label in real time.

[0087] The experimental results are as Figure 3 Figure 4As shown Figure 3 is the experimental trajectory diagram obtained without the present invention Figure 4 is the experimental trajectory diagram obtained after being processed by the present invention, and the number of experiments is 50 times Figure 3 The average value of the experimental positioning error shown is 23 cm Figure 3 The average value of the experimental positioning error shown is 11 cm, and the accuracy is improved by about 12 cm. It can be seen that the present invention uses an indoor positioning processing method that suppresses environmental and hardware errors to effectively alleviate the positioning errors caused by the environment and the hardware itself, and improves the positioning accuracy by using the processed TWR positioning solution, which is superior to the existing positioning technologies

[0088] The above is only a further description of the present invention and is not intended to limit the present invention. Equivalent implementations without departing from the spirit and scope of the present invention should be included within the scope of the claims of the present invention

Claims

1. An indoor positioning method for suppressing environmental and hardware errors, characterized in that, the method comprises: Step 1: Obtain prior information; first, set the UWB module as the corresponding positioning base station and mobile tag; then construct a positioning experimental environment composed of a positioning base station, a mobile tag, a Bluetooth adapter, and a data processing terminal; the positioning base station consists of several UWB modules set as "anchor"; the mobile tag consists of one UWB module set as "tag"; the Bluetooth adapter is the Bluetooth adapter ble112; in the positioning experimental environment, place the mobile tag "tag" at a point where both los and nlos are included during the signal transmission between the positioning base station and the mobile tag, and within the range surrounded by multiple base stations, and call this point the selected calibration point; after placement, the UWB module uses the TWR positioning engine in the "tag" mode. Under this engine condition, information is transmitted between the mobile tag and the positioning base station, and the time difference of information transmission between the positioning base station and the mobile tag is first calculated through the two-way two-way ranging method, and then the distance information obtained by the two-way two-way ranging method is calculated. At this time, hundreds of groups of test distance data are sampled, and finally, the distance data is transmitted to the data processing terminal through Bluetooth by the Bluetooth adapter, and the distance information from the mobile tag to each positioning base station at the calibration point is calculated; Step 2: Solve the indoor positioning coordinates; measure and calculate the actual distance from the mobile positioning tag to each positioning base station in the real environment; compare the distance information obtained by the data processing terminal with the measured actual distance information, and use the difference between the distance information and the actual distance information to compensate the distance information at the data processing terminal to eliminate the environmental and hardware errors in the room; the data processing terminal obtains the coordinates of the mobile tag by performing positioning calculation on the data, that is, obtains the coordinates of the calibration point where the mobile tag is located.

2. The indoor positioning method according to claim 1, characterized in that, the time difference of information transmission between the positioning base station and the mobile tag calculated first by using the two-way two-way ranging method is specifically calculated by the following (1): The transmission is divided into two rounds. In the first round, UWB module A emits a pulse signal of request nature at time T on its time stamp. a1 UWB module B receives the signal at time T on its time stamp, and then processes the UWB signal. UWB module B emits signals of both response nature and request nature at time T. b1 This signal is received by UWB module A at its own time stamp T. b2 Among them, the time difference between the signal transmission and reception of UWB module B is denoted as T. a2 The time difference between the time when UWB module A receives the signal from UWB module B and the time when UWB module A sends the signal is T. reply1 round1 ​ In the second round, the UWB module A processes the signal received at its own timestamp T a2 and then transmits signals of both response and request natures at timestamp T a3 which are received by the UWB module B at its own timestamp T b3 ; where the time difference between the signal transmission and reception of the UWB module A is denoted as T reply2 ; and the time difference between the time when the UWB module B receives the signal from the UWB module A and the time when the UWB module B transmits a signal is T round2 ; the distance information obtained by using the two-way two-way ranging method is specifically calculated by the following formula (2): 2.r = T * C (2) where C is the speed of light, and r is the distance information from the mobile tag to a positioning base station calculated by using the two-way two-way ranging method; the data processing terminal obtains the coordinates of the mobile tag by performing positioning calculation on the data, which is calculated by the following formula (3): where (x, y) are the unknown coordinates of the mobile tag, and (x i , y i ) are the known coordinates of the positioning base station; where r i1 is the distance information from the mobile tag to the i-th positioning base station, which is known information; Denote the left side of this system of equations as f i (x, y, x i , y i ), and the right side of the equation is the known quantity r i1 , denoted as m i , so the system of equations is abbreviated as the following formula (4) f i (x, y, x i , y i ) = m i (4) Let (x v , y v ) be the iterative initial value of the unknown coordinates (x, y) of the mobile tag, and (δ x , δ y ) be the difference between the unknown coordinates (x, y) of the mobile tag and the iterative value, which is the following formula (5) (x, y) = (x v , y v ) + (δ x , δ y ) (5) Let f i (x, y, x i , y i ) be second-order Taylor expanded at (x v , y v ), and neglecting the higher-order terms gives the following equation (6) Denote as a i1 , as a i2 , then the following formula (7) can be obtained After transposing formula (7) and writing it in matrix form, that is, the following formula (8) where A, δ, and z are respectively Calculate δ using the weighted least squares method δ = [A T R -1 A] -1 A T R -1 z (9) where R is the weight matrix of weighted least squares, and the identity matrix is selected as the weight matrix here; then add the values of the original (x v , y v ) to (δ x , δ y ) as the new (x v , y v ), and repeat the above steps to solve for (δ x , δ y ), and iterate continuously until (x v , y v ) meets the accuracy requirements; x v ←x v +δ x ,y v ←y v +δ y (10) That is, the uncompensated coordinate information is obtained through the above formula (10); The difference between the distance information and the actual distance information is represented by the following formula (11): r i ＝r i1 -r i2 (11) Among them, r i1 is the distance information of the mobile tag to the i-th positioning base station, and r i2 is the true distance information of the mobile positioning tag to the i-th positioning base station measured and calculated in the real environment; r i is the difference between the distance information and the true distance information; Finally, add the difference between the distance information and the actual distance information obtained by formula (11) to the distance information in formula (3), and continuously perform iterative operations; finally, obtain the coordinates of the calibration point where the mobile tag is located.

3. The indoor positioning method according to claim 1, characterized in that, The positioning base station, as a fixed node for routing data between the UWB network and the IP network in the positioning system, receives a group poll message sent by the mobile tag. The group poll message includes: a location period and a list of several addresses of the positioning base stations used by the mobile tag for positioning; the group poll message is a broadcast message, and all positioning base stations within the range can receive the group poll message.

4. The indoor positioning method according to claim 1, characterized in that the distance data is transmitted to the data processing terminal via Bluetooth through the Bluetooth adapter, and a configuration location data and visualization interface is provided via the Web.

5. The indoor positioning method according to claim 1, characterized in that the TWR positioning engine, that is, the mobile tag operates in a response mode, and broadcasts an ultra-wideband pulse signal containing the mobile tag ID information as a TAG positioning packet to the positioning base station at a frequency of 10 Hz.

6. The indoor positioning method according to claim 1, characterized in that the true distance information from the mobile positioning tag to each positioning base station is measured and calculated, and recorded by using a millimeter-level laser rangefinder.

Images