A UWB positioning method based on virtual nodes in NLOS environment

Abstract

The present application discloses a UWB positioning method based on virtual nodes in an NLOS environment, which has the following effects: by setting virtual anchor nodes and physical anchor nodes to form an anchor node group, the number of anchor nodes required is less than that of a traditional positioning solution, which not only reduces the cost but also reduces the overall power consumption; the extended Kalman filter algorithm is integrated with the positioning of the virtual anchor nodes, which effectively realizes the identification of NLOS errors and reduces the influence of NLOS errors on the positioning results; the position of the virtual anchor node is not fixed, and the combination of the anchor point group and the virtual node is also not fixed. During the judgment process, when an NLOS state exists between the physical anchor node and the mobile target, the virtual anchor nodes that do not meet the requirements are eliminated and the virtual anchor nodes are regenerated to update the anchor node group, thereby optimizing the output result. The method is simple and improves the flexibility of the positioning system without adding additional physical devices, thereby further improving the positioning efficiency.

Description

Technical Field

[0001] The present invention mainly relates to the field of positioning technology, and in particular to a UWB positioning method based on virtual nodes in an NLOS environment. Background Art

[0002] At present, people's demand for indoor positioning services is increasing, and there are many positioning methods to choose from, such as fingerprint positioning technology, triangulation and triangulation. However, these technologies are not enough to quickly respond to the positioning of people in complex indoor environments, and they all require the pre-deployment of a large number of nodes, pre-calibration, and channel configuration. For large indoor spaces, the above technologies significantly increase the deployment cost. Moreover, in emergency situations such as firefighting, security, and rescue, we do not have enough time to install a large number of nodes. How to design and develop a positioning method that can quickly adapt to environmental changes and does not require a large number of nodes as support is an urgent problem to be solved in the field of indoor positioning.

[0003] Ultra-wideband positioning (UWB) technology is considered to be the first choice for indoor positioning technology. UWB technology can provide centimeter-level distance estimation and has the advantages of strong resistance to multipath effects, low power consumption, and large information load. In indoor environments, signal propagation channels can be divided into line-of-sight channels (LOS) and non-line-of-sight channels (NLOS). UWB signals can accurately measure distance in LOS channels, but in NLOS channels, due to repeated refraction of signals, the propagation time of signals will be significantly increased, increasing the distance measurement error.

[0004] Therefore, how to design a UWB positioning method with high positioning efficiency, simple operation and high efficiency is a technical problem to be solved. Summary of the invention

[0005] Based on this, it is necessary to provide a UWB positioning method based on virtual nodes in a NLOS environment to address the existing problems, including the following steps:

[0006] S1: obtaining the current physical anchor nodes, and grouping the physical anchor nodes to obtain multiple physical anchor node groups;

[0007] S2: generating a virtual anchor node for each physical anchor node group based on the multiple physical anchor node groups, wherein the multiple physical anchor nodes and the correspondingly generated virtual anchor nodes constitute multiple current anchor node groups;

[0008] S3: Calculate the first current distances between the multiple virtual anchor nodes and the mobile target using the first distance calculation model and the second current distances between all the physical anchor nodes and the mobile target using the second distance calculation model, and obtain first current distance data consisting of the multiple first current distances and the position coordinates of all the virtual anchor nodes and second current distance data consisting of the multiple second current distances and the position coordinates of all the physical anchor nodes;

[0009] S4: using an extended Kalman filter algorithm to process the first current distance data and the second current distance data, and determining whether there is an NLOS state between the physical anchor nodes in the plurality of current anchor node groups and the mobile target;

[0010] S5: in response to a NLOS state between the physical anchor node in the current anchor node group and the mobile target, removing the virtual anchor node in the current anchor node group and repeating the above steps, outputting the first current distance data and the second current distance data and entering the next moment;

[0011] S6: Using the least square method to perform positioning processing on the first current distance data and the second current distance data to obtain the final position coordinates of the moving target.

[0012] Preferably, obtaining the physical anchor nodes at the current moment and grouping the physical anchor nodes to obtain a plurality of physical anchor node groups includes:

[0013] Get the current time The physical anchor node 、 、 … 、 ;

[0014] Will The physical anchor node 、 、 … 、 According to the two-by-two grouping, we get The physical anchor node group[ ; ]、[ ; ], …, [ ; ];

[0015] in, , Greater than or equal to 4.

[0016] Preferably, the The virtual anchor nodes are represented as: 、 、 … 、 ;

[0017] The current anchor node group is represented as: ; ; ]、[ ; ; ], …, [ ; ; ].

[0018] Preferably, the first preset distance calculation model is expressed by the following formula:

[0019] ;

[0020] The second preset distance calculation model is expressed by the following formula:

[0021] ;

[0022] in,( , ) is the The current position coordinates of the physical anchor node, ( , ) is the current position coordinate of the moving target, For the The current distance between the virtual anchor node and the moving target, , For the The current distance between the physical anchor node and the mobile target, For the The physical anchor node to the The current distance between the virtual anchor nodes, For the The virtual anchor node and the mobile target are relative to the The third current angle of the physical anchor node is expressed by the following formula:

[0023] ;

[0024] ;

[0025] in,( , ) is the The current position coordinates of the virtual anchor node, For the the virtual anchor node and the The physical anchor node is relative to the a first current angle of the physical anchor node, For the The physical anchor node and the mobile target are relative to the The second current angle of the physical anchor node is expressed by the following formula:

[0026] ;

[0027] ;

[0028] in, For the +1 the current distance between the physical anchor node and the mobile target, which is obtained by formula (2), For the The physical anchor node to the The current distance between the virtual anchor nodes is obtained by formula (4): For the The physical anchor node to the The current distance between the physical anchor nodes is expressed by the following formula:

[0029] ;

[0030] in,( , ) is the The current position coordinates of the physical anchor node.

[0031] Preferably, the extended Kalman filter algorithm is used to process the first current distance data and the second current distance data to determine whether there is an NLOS state between the physical anchor nodes in the multiple current anchor node groups and the mobile target, including:

[0032] Calculate the current time The prior state estimate of the moving target is ;

[0033] Calculate the current time according to the first current distance data and the second current distance data Down The target posterior estimate of the current anchor node group , ,……, ;

[0034] Calculate the posterior state estimate of the mobile target respectively , ,……, With the prior state estimate The difference value of Difference data consisting of difference values;

[0035] Compare each difference value of the difference data with a preset threshold value to determine whether the difference value is greater than the preset threshold value;

[0036] In response to the difference value being greater than a preset threshold, there is an NLOS state between the physical anchor node in the current anchor node group corresponding to the difference value and the mobile target;

[0037] Get the next moment according to the preset calculation method The prior state estimate of the moving target is .

[0038] Preferably, the posterior state estimate of the mobile target is calculated by the following formula: , ,……, With the prior state estimate The difference value is:

[0039] ;

[0040] in, , and For the The horizontal and vertical coordinates of the posterior state estimate calculated by the current anchor node group, For the The Mahalanobis distance of the current anchor node group is R, and R is the mean square error of the Euclidean distance between the prior state estimation coordinates and the posterior state estimation coordinates in the LOS state.

[0041] Preferably, the time is obtained according to a preset calculation method Prior state estimation of moving targets ,include:

[0042] According to the time The prior state estimate of the moving target is , obtain the posterior state estimate of the mobile target ;

[0043] According to the posterior state estimate Get the moment The prior state estimate of the moving target is .

[0044] Preferably, the a posteriori state estimate of the mobile target It is expressed by the following formula:

[0045] = + ;

[0046] in, is the Kalman gain, is the measurement equation of the moving target, is the posterior state estimate Substituting the a posteriori measurement value obtained by the measurement equation, is the prior state estimate Substituting the a priori measurement value obtained into the measurement equation, it is obtained by the following formula:

[0047] ;

[0048] ;

[0049] in, , is subject to mean zero and variance The measurement noise vector of

[0050] in, is the prediction covariance, is the Jacobian matrix, which is obtained by the following formula:

[0051] ;

[0052] ;

[0053] ;

[0054] in, is the identity matrix.

[0055] Preferably, the time The prior state estimate of the moving target is It is expressed by the following formula:

[0056] ;

[0057] in, , is the acceleration noise, , for Directional acceleration noise, for Directional acceleration noise, and They have mean 0 and variance and Gaussian distribution of

[0058] Among them, the matrix and matrix It is expressed by the following formula:

[0059] ;

[0060] ;

[0061] in, The positioning interval time.

[0062] Preferably, the least square method is used to perform positioning processing on the first current distance data and the second current distance data to obtain the final position coordinates of the moving target, including:

[0063] Determine that the first current distance data includes the position coordinates of all virtual anchor nodes ( ), ),……,( ) and the distances from all virtual anchor nodes to the mobile target , ,……, The second current distance data includes the position coordinates of all physical anchor nodes ( ), ),……,( ) and the distances from all physical anchor nodes to the mobile target , ,……, ;

[0064] According to the distance calculation formula (2) of each physical anchor node and virtual anchor node and the distance calculation formula (2) of the first physical anchor node, a subtraction operation and matrix conversion are performed to obtain a matrix equation;

[0065] The matrix equation is operated by the least square method to obtain the final position coordinates of the moving target. ;

[0066] The final position coordinates It is expressed by the following formula:

[0067] ;

[0068] Among them, the matrix and matrix It is expressed by the following formula:

[0069] ;

[0070] ;

[0071] Where T represents the transposition of the matrix.

[0072] Compared with the prior art, the present invention has the following beneficial effects:

[0073] (1) The solution of the present invention forms an anchor node group by setting virtual anchor nodes and physical anchor nodes. Compared with the traditional positioning solution, the number of anchor nodes required is less, which can not only reduce the deployment cost but also reduce the overall power consumption;

[0074] (2) The present invention integrates the extended Kalman filter algorithm with the positioning solution combined with virtual nodes, effectively realizing the identification of NLOS errors, thereby reducing the impact of NLOS errors on positioning results;

[0075] (3) The position of the virtual node of the present invention is not fixed, and the combination of the actual anchor point group and the virtual node is also not fixed. During the judgment process, when there is an NLOS state between the physical anchor node and the mobile target, the virtual anchor node that does not meet the requirements is eliminated, the virtual anchor node is regenerated, and the anchor node group is updated. The calculation process is completed in the central processing unit without consuming a lot of solution time. In addition, the flexibility of the positioning system is improved without adding additional physical devices, and the NLOS error in the system measurement value is effectively eliminated, further improving the positioning efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] By referring to the following drawings, the exemplary embodiments of the present invention can be more completely understood. The drawings are used to provide a further understanding of the embodiments of the present application, and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present invention and do not constitute a limitation of the present invention. In the drawings, the same reference numerals generally represent the same parts or steps.

[0077] Figure 1 A flowchart of a UWB positioning method based on a virtual node in a NLOS environment provided by an exemplary embodiment of the present application is shown;

[0078] Figure 2 A flowchart of a UWB positioning system based on virtual nodes in a NLOS environment provided by an exemplary embodiment of the present application is shown;

[0079] Figure 3 A schematic diagram of trigonometric function calculation provided by an exemplary embodiment of the present application is shown;

[0080] Figure 4 A schematic diagram of NLOS positioning provided by an exemplary embodiment of the present application is shown. DETAILED DESCRIPTION

[0081] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0082] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0083] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0084] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0085] Example 1

[0086] Reference Figure 1 The embodiment of the present application provides a UWB positioning method based on a virtual node in an NLOS environment, comprising the following steps:

[0087] S1: Obtain the current physical anchor nodes, and group the physical anchor nodes to obtain multiple physical anchor node groups;

[0088] The method provided in this embodiment can be applied to Figure 2 According to the positioning system architecture, to achieve accurate three-dimensional positioning of a mobile node, at least three anchor nodes are required, which is the minimum number of anchor nodes. In order to ensure that there are enough anchor node groups to choose from in the positioning space, this application sets the number of physical anchor nodes involved in positioning to indivual( The number of anchor nodes involved in positioning can be adjusted according to the actual positioning space size. as an example).

[0089] Specifically, the four physical anchor nodes are: 、 、 、 , whose position coordinates are 、 、 、 Then, we group them into two groups, and get a total of 6 physical anchor node groups: ; ]、[ ; ]、[ ; ]、[ ; ]、[ ; ]、[ ; ].

[0090] S2: Generate a virtual anchor node for each physical anchor node group based on multiple physical anchor node groups, and each physical anchor node and its corresponding generated virtual anchor node constitute a current anchor node group;

[0091] Specifically, as mentioned above, at least three anchor nodes are required for three-dimensional positioning of the target, so the missing anchor nodes can be replaced by virtual anchor nodes. Since virtual nodes mainly play an auxiliary role, the coordinates of virtual anchor nodes can be set arbitrarily. For ease of explanation, we configure a virtual anchor node for each physical anchor node group, and the number of virtual anchor nodes is , but in actual applications, the number of virtual anchor nodes can be set arbitrarily without any limit. Assume that the current anchor node group consisting of virtual anchor nodes and physical anchor nodes is: [ ; ; ]、[ ; ; ]、[ ; ; ]、[ ; ; ]、[ ; ; ]、[ ; ; ], the position coordinates of the virtual anchor node are .

[0092] S3: Calculate the first current distances between multiple virtual anchor nodes and the mobile target using the first distance calculation model and the second current distances between all physical anchor nodes and the mobile target using the second distance calculation model, and obtain first current distance data consisting of multiple first current distances and position coordinates of all virtual anchor nodes and second current distance data consisting of multiple second current distances and position coordinates of all physical anchor nodes;

[0093] Specifically, since the virtual anchor node does not have any physical properties, the only information we know about it in advance is the coordinates. Figure 3 (Only the current anchor node group is shown [ ; ; ] and the distance and angle calculation between the mobile target. The calculation method of other anchor node groups is similar. The distance between the virtual anchor node and the mobile target is calculated by trigonometric function, so that the information of the actual anchor node can be integrated.

[0094] Reference Figure 3 , the first preset distance calculation model is expressed by the following formula:

[0095] ;

[0096] The second preset distance calculation model is expressed by the following formula:

[0097] ;

[0098] in,( , )、( , ) are respectively The current position coordinates of the first and second physical anchor nodes, ( , ) is a moving target MS The current location coordinates, is the current distance between the virtual anchor node and the moving target, and Respectively The current distance between the first physical anchor node and the second physical anchor node and the moving target, For the The current distance between the physical anchor node and the virtual anchor node, is the virtual anchor node and the mobile target relative to the The third current angle of the physical anchor node, the above parameters are expressed by the following formula:

[0099] ;

[0100] ;

[0101] in,( , ) is the current position coordinate of the virtual anchor node, is the first current angle between the virtual anchor node and the second physical anchor node relative to the first physical anchor node, is the second physical anchor node and the mobile target relative to the The second current angle of the physical anchor node is expressed by the following formula:

[0102] ;

[0103] ;

[0104] in, is the current distance between the second physical anchor node and the virtual anchor node, which is obtained by formula (4): is the current distance between the first physical anchor node and the second physical anchor node, expressed by the following formula:

[0105] ;

[0106] From the above principle, it can be seen that the positioning solution combined with the virtual anchor node effectively utilizes the distance measurement information of the actual physical anchor node to the mobile target. If the actual anchor node is in the NLOS state with the target, its measurement information will be effectively fed back to This will cause a large deviation in the calculated position of the entire anchor point group. However, there are multiple anchor point groups in the positioning space. We can set an error threshold. For anchor point groups that exceed the threshold, it is determined that there may be an NLOS state between the anchor node in the anchor node group and the target, and the anchor point group is removed. For anchor node groups that do not exceed the threshold, they are retained. The specific NLOS identification method will be described in detail in the next section.

[0107] S4: using an extended Kalman filter algorithm to process the first current distance data and the second current distance data, and determining whether there is an NLOS state between the physical anchor nodes in the multiple current anchor node groups and the mobile target;

[0108] Specifically, step S4 includes the following:

[0109] (1) Calculate the current time Prior state estimation of moving targets ;

[0110] (2) Calculate the current time based on the first current distance data and the second current distance data Down The target posterior estimate of the current anchor node group , ,……, ;

[0111] Specifically, the present invention proposes a positioning solution combining virtual nodes based on the traditional positioning system, which improves the overall flexibility of the system in complex environments. Then, the extended Kalman filter algorithm is combined with the proposed positioning solution to provide a precondition for identification in the NLOS state. At this moment, the six current anchor node groups can be combined with the EKF algorithm to obtain six posterior state estimates. We express these six posterior state estimates as: , , , , , It should be noted that the moving target The prior estimate of the moment is given by The posterior state estimate at time So no matter how many anchor groups there are, there is only one prior state estimate.

[0112] (3) Calculate the posterior state estimate of the moving target separately , , , , , With prior state estimate The difference value of The difference data consisting of the difference values;

[0113] The present invention calculates the Mahalanobis distance between the posterior state estimate and the prior state estimate. To determine the degree of difference between the two:

[0114] ;

[0115] in, , and For the The horizontal and vertical coordinates of the posterior state estimate calculated by the current anchor point group, For the The Mahalanobis distance of the current anchor point group is 0.2 m, and R is the mean square error of the Euclidean distance between the prior state estimated coordinates and the posterior state estimated coordinates in the LOS state. The present invention has obtained through multiple actual measurements that the Euclidean distance between the prior estimated position and the posterior estimated position calculated by the system in the LOS state is approximately 0.2 m, so R is 0.04.

[0116] (4) Compare each difference value of the difference data with a preset threshold value to determine whether the difference value is greater than the preset threshold value;

[0117] (5) In response to the difference value being greater than a preset threshold, there is an NLOS state between the physical anchor node in the current anchor node group corresponding to the difference value and the mobile target;

[0118] Specifically, combined with the chi-square distribution table, set the threshold is 9.21. If the calculated Greater than This means that the posterior state estimate calculated by the anchor group has a 99% probability of NLOS error, so it is discarded, otherwise it is accepted.

[0119] (6) Obtain the next moment according to the preset calculation method Prior state estimation of moving targets .

[0120] Specifically, this step includes:

[0121] According to the time Prior state estimation of moving targets , obtain the posterior state estimate of the moving target ;

[0122] Specifically, the posterior state estimate of the moving target It is expressed by the following formula:

[0123] = + ;

[0124] in, is the Kalman gain, is the measurement equation of the moving target, is the posterior state estimate Substituting the a posteriori measurement value obtained by the measurement equation, is the prior state estimate Substituting the a priori measurement value obtained into the measurement equation, it is obtained by the following formula:

[0125] ;

[0126] ;

[0127] in, , is subject to mean zero and variance The measurement noise vector of

[0128] in, is the prediction covariance, is the Jacobian matrix, which is obtained by the following formula:

[0129] ;

[0130] ;

[0131] ;

[0132] in, is the identity matrix.

[0133] According to the posterior state estimate Get the moment Prior state estimation of moving targets .

[0134] Specifically, the time Prior state estimation of moving targets It is expressed by the following formula:

[0135] ;

[0136] in, , is the acceleration noise, , for Directional acceleration noise, for Directional acceleration noise, and They have mean 0 and variance and Gaussian distribution of

[0137] Among them, the matrix and matrix It is expressed by the following formula:

[0138] ;

[0139] ;

[0140] in, The positioning interval time.

[0141] S5: In response to the NLOS state between the physical anchor node in the current anchor node group and the mobile target, the virtual anchor node in the current anchor node group is removed and the above steps are repeated to output the first current coordinate data and the second current coordinate data and enter the next moment;

[0142] Reference Figure 4 , a schematic diagram of NLOS positioning is given. It can be seen from the figure that only the current anchor node group [ ; ; ] are in LOS state with the target, and the rest of the current anchor node group [ ; ; ]、[ ; ; ]、[ ; ; ]、[ ; ; ]、[ ; ; ], some or all of the anchor points are in NLOS state with the target. Since the target posterior state estimation at the previous moment is ideal, the anchor point group containing NLOS measurement values ​​at this moment It must be greater than the threshold , thus the NLOS error can be eliminated. It is worth mentioning that the position of the virtual anchor node is not fixed, and the combination of the current anchor point group and the virtual anchor node is not fixed, so if the current moment all anchor node groups If all are greater than the threshold, we can regenerate virtual nodes and rematch until a result that meets the requirements appears. This calculation process is all completed in the central processor, without consuming a lot of solution time. Moreover, without adding additional physical devices, the flexibility of the positioning system is improved, and the NLOS error in the system measurement value is effectively eliminated.

[0143] S6: Using the least square method to perform positioning processing on the first current distance data and the second current distance data to obtain the final position coordinates of the moving target.

[0144] Specifically, the anchor node and the mobile node use bilateral two-way ranging (TWR) to measure the distance. We first assume that the physical anchor node The coordinates of ,in ， Moving Target MS The initial coordinates are After obtaining the relative distance between each physical anchor node and the mobile target Afterwards, the solution equation for the mobile node is established in combination with the least squares method.

[0145] The specific process is as follows:

[0146] (1) Determine the first current distance data including the position coordinates of all virtual anchor nodes ( ), ), ), ), ), ) and the distance from all virtual anchor nodes to the moving target , ,……, ; The second current distance data includes the location coordinates of the physical anchor node ( ), ), ), ) and the distance from all physical anchor nodes to the mobile target , , , ;

[0147] (2) performing a subtraction operation and matrix conversion based on the distance calculation formula (2) of each physical anchor node and virtual anchor node and the distance calculation formula (2) of the first physical anchor node to obtain a matrix equation;

[0148] (3) Use the least squares method to calculate the matrix equation and obtain the final position coordinates of the moving target ;

[0149] The final position coordinates It is expressed by the following formula:

[0150] ;

[0151] Among them, the matrix and matrix It is expressed by the following formula:

[0152] ;

[0153] ;

[0154] Where T represents the transposition of the matrix.

[0155] The UWB positioning solution provided by the present invention can be applied in the following two scenarios and provide corresponding effects:

[0156] (1) Emergency rescue scenarios

[0157] Based on the traditional UWB positioning solution, an innovative UWB positioning solution combining virtual anchor point groups was eliminated. This solution effectively improves the positioning efficiency and flexibility of the entire positioning system without adding additional physical devices. In most emergency rescue situations, people do not have enough time to deploy a large number of nodes. Virtual nodes can effectively solve this problem and ensure the timeliness and accuracy of information.

[0158] (2) Efficient indoor positioning scenarios

[0159] By designing a mathematical model of the target's motion state, the extended Kalman filter is combined with the UWB positioning system combined with virtual nodes. By comparing the difference between the prior estimate and the posterior estimate, the anchor node group containing NLOS information is effectively eliminated and the optimal estimate is retained. Similarly, without adding hardware devices, efficient positioning is achieved in complex indoor environments such as offices, basements, and shopping malls.

[0160] Compared with the prior art, the present invention has the following beneficial effects:

[0161] (1) The solution of the present invention forms an anchor node group by setting virtual anchor nodes and physical anchor nodes. Compared with the traditional positioning solution, the number of anchor nodes required is less, which can not only reduce the deployment cost but also reduce the overall power consumption;

[0162] (2) The present invention integrates the extended Kalman filter algorithm with the positioning solution combined with virtual nodes, effectively realizing the identification of NLOS errors, thereby reducing the impact of NLOS errors on positioning results;

[0163] (3) The position of the virtual node of the present invention is not fixed, and the combination of the actual anchor point group and the virtual node is also not fixed. During the judgment process, when there is an NLOS state between the physical anchor node and the mobile target, the virtual anchor node that does not meet the requirements is eliminated, the virtual anchor node is regenerated, and the anchor node group is updated. The calculation process is completed in the central processing unit without consuming a lot of solution time. In addition, the flexibility of the positioning system is improved without adding additional physical devices, and the NLOS error in the system measurement value is effectively eliminated, further improving the positioning efficiency.

[0164] It should be noted that the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0165] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0166] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0167] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0168] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0169] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0170] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and they should all be included in the scope of the claims and specification of the present application.

Claims

1. A UWB positioning method based on virtual nodes in a NLOS environment, characterized in that: The steps include: S1: obtaining the current physical anchor nodes, and grouping the physical anchor nodes to obtain multiple physical anchor node groups; S2: generating a virtual anchor node for each physical anchor node group based on the multiple physical anchor node groups, wherein the multiple physical anchor nodes and the correspondingly generated virtual anchor nodes constitute multiple current anchor node groups; S3: Calculate the first current distances between the plurality of virtual anchor nodes and the mobile target using the first distance calculation model and calculate the second current distances between all physical anchor nodes and the mobile target using the second distance calculation model, and obtain first current distance data consisting of the plurality of first current distances and the position coordinates of all virtual anchor nodes and second current distance data consisting of the plurality of second current distances and the position coordinates of all physical anchor nodes; S4: using an extended Kalman filter algorithm to process the first current distance data and the second current distance data, and determining whether there is an NLOS state between the physical anchor nodes in the plurality of current anchor node groups and the mobile target; S5: in response to a NLOS state between the physical anchor node in the current anchor node group and the mobile target, removing the virtual anchor node in the current anchor node group and repeating the above steps, outputting the first current distance data and the second current distance data and entering the next moment; S6: using the least square method to perform positioning processing on the first current distance data and the second current distance data to obtain the final position coordinates of the moving target; The step of acquiring the current physical anchor node and grouping the physical anchor node to obtain a plurality of physical anchor node groups includes: Get the current time The physical anchor node The physical anchor nodes are grouped in pairs to obtain the physical anchor node groups; in, , Greater than or equal to 4; The first distance calculation model is represented by the following formula: ； The second distance calculation model is expressed by the following formula: ； in,( , ) is the The current position coordinates of the physical anchor node, ( , ) is the current position coordinate of the moving target, For the The current distance between the virtual anchor node and the moving target, , For the The current distance between the physical anchor node and the mobile target, For the The physical anchor node to the The current distance between the virtual anchor nodes, For the The virtual anchor node and the mobile target are relative to the a third current angle of the physical anchor node, and It is expressed by the following formula: ； ； in,( , ) is the The current position coordinates of the virtual anchor node; For the the virtual anchor node and the The physical anchor node is relative to the a first current angle of the physical anchor node, For the The physical anchor node and the mobile target are relative to the a second current angle of the physical anchor node, and It is expressed by the following formula: ； ； in, For the +1 the current distance between the physical anchor node and the mobile target, which is obtained by formula (2), For the The physical anchor node to the The current distance between the virtual anchor nodes is obtained by formula (4): For the The physical anchor node to the The current distance between the physical anchor nodes, It is expressed by the following formula: ； in,( , ) is the The current position coordinates of the physical anchor node.

2. The UWB positioning method according to claim 1, characterized in that: The first current distance data and the second current distance data are processed by using an extended Kalman filter algorithm to determine whether a NLOS state exists between the physical anchor nodes in the multiple current anchor node groups and the mobile target, including: Calculate the current time The prior state estimate of the moving target is ; Calculate the current time according to the first current distance data and the second current distance data Down The target posterior estimate of the current anchor node group , ,……, ; Calculate the posterior state estimate of the mobile target respectively , ,……, With the prior state estimate The difference value of Difference data consisting of difference values; Compare each difference value of the difference data with a preset threshold value to determine whether the difference value is greater than the preset threshold value; In response to the difference value being greater than a preset threshold, there is an NLOS state between the physical anchor node in the current anchor node group corresponding to the difference value and the mobile target; Get the next moment according to the preset calculation method The prior state estimate of the moving target is .

3. The UWB positioning method according to claim 2, characterized in that: The posterior state estimate of the mobile target is calculated by the following formula: , ,……, With the prior state estimate The difference value is: ； in, , and For the The posterior state estimate calculated by the current anchor node group Axis coordinates and Axis coordinates, For the The Mahalanobis distance of the current anchor node group is R, and R is the mean square error of the Euclidean distance between the prior state estimation coordinates and the posterior state estimation coordinates in the LOS state.

4. The UWB positioning method according to claim 3, characterized in that: Get the time according to the preset calculation method Prior state estimation of moving targets ,include: According to the time The prior state estimate of the moving target is , obtain the posterior state estimate of the mobile target ; According to the posterior state estimate Get the moment The prior state estimate of the moving target is .

Images