A system for quickly solving tag coordinates using multiple UWB base stations

Abstract

The application discloses a system for quickly solving tag coordinates by using multiple UWB base stations, which comprises multiple (more than 3) UWB base stations, and the multiple base stations are arranged as equidistant squares; a layout schematic diagram of 9 base stations is shown in the drawing, and the distance between every two adjacent base stations is 8 meters; the steps of the new method for solving tag coordinates are as follows: S1, first, the ranging values TD[i] (i=0, 1, 2, … n, n=4, 9, 16, 25, 36…) of a tag T to each base station are acquired; the method for solving tag coordinates by using two base stations and three base stations in the conventional technology has some problems, such as no solution, conjugate coordinate solution, etc.; and by using the positioning system and the quick solving method, the positioning accuracy and stability are improved by simultaneously positioning by using multiple base stations; and because the tag position is estimated and tracked, the uncertainty and change of the tag in motion can be better handled, so that better tag motion tracking effect is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of UWB positioning system, and particularly relates to a system for quickly solving tag coordinates by using multiple UWB base stations BACKGROUND

[0002] The UWB positioning system technology is a technology for positioning through Ultra-WideBand (UWB) signals. The UWB signal is a kind of radio signal with extremely high bandwidth and short pulse width, which can transmit a large amount of data in a wide frequency band. The positioning system based on UWB signals utilizes the propagation characteristics of signals in space, and measures the propagation time, amplitude, phase and other parameters of signals in space to determine the position of objects.

[0003] The main components of the UWB positioning system include tags, base stations, signal processors and positioning algorithms. The tag is a device carrying a UWB transceiver on the object to be positioned, which can transmit and receive UWB signals. The base station is the control center of the UWB positioning system, which can transmit UWB signals and receive signals returned by the tag. The signal processor processes and analyzes the received UWB signals to extract key positioning parameters. The positioning algorithm is the core part of the UWB positioning system, which uses the ranging information between the tag and the base station to calculate the three-dimensional coordinates of the tag.

[0004] The UWB positioning system technology has the following advantages: high precision, high stability, strong anti-interference ability, large capacity data transmission and low power consumption, etc. It is widely used in indoor positioning, vehicle navigation, personnel tracking, logistics management and other fields.

[0005] At present, more and more UWB ranging and positioning systems are applied. Since the ranging accuracy provided by UWB can only reach about ±100mm, it cannot meet the requirements of systems with higher positioning accuracy.

[0006] At the same time, based on the two base stations commonly used in traditional technology, when solving the tag coordinates (TX, TY) by using two 2-element 2-order equation groups, two conjugate coordinate solutions will be generated. Because only the information of two base stations is used, such solution cannot uniquely determine the position of the tag, and it is not easy to determine which solution is correct.

[0007] Based on the three base stations commonly used in the conventional technology, three 2-element 2-equation sets are used to solve the tag coordinate T[TX, TY], although a unique solution can be obtained, but in practical application, the situation of no solution may be encountered. Although the current "angle of arrival" TOA (Angle-of-Arrival) and "time difference of arrival" TDOA (Time Difference of Arrival) and other methods can be solved, there are still problems such as solution selection and precision in actual engineering application.

[0008] Therefore, a system for quickly solving the tag coordinate by using multiple UWB base stations is proposed. SUMMARY

[0009] Therefore, the embodiments of the present application hope to provide a system for quickly solving the tag coordinate by using multiple UWB base stations, to solve or alleviate the technical problems existing in the prior art, and at least provide a beneficial choice;

[0010] The technical scheme of the embodiments of the present application is as follows:

[0011] In a first aspect, a system for quickly solving the tag coordinate by using multiple UWB base stations is provided, which comprises using multiple (more than 3) UWB base stations, and arranging the multiple base stations into a square or rectangular diagram, which is shown in the layout schematic diagram using 9 base stations, and the distance between each adjacent 2 base stations is 8 meters.

[0012] The new method for solving the tag coordinate is as follows:

[0013] S1, first, obtain the ranging values TD[i] (i=0, 1, 2, … n, n=4, 9, 16, 25, 36…) of the tag T to each base station;

[0014] S2, find out 2 base stations (for example, A[i] and A[j]) with equal Y coordinates and unequal X coordinates in the X direction;

[0015] S3, determine that the line connecting the 2 base stations forms a triangle with the distances TD[i] and TD[j] of the tag to the 2 base stations;

[0016] S4, calculate the height H corresponding to the side of the line connecting the 2 base stations by the formula for calculating the height of a triangle with known three sides;

[0017] S5, calculate the distances tmp1 and tmp2 of the tag TX coordinate point to the 2 base stations A[i] and A[j] respectively:

[0018] tmp1=sqrt(TD[i]*TD[i]-H*H);

[0019] tmp2=sqrt(TD[j]*TD[j]-H*H);

[0020] S6, if tmp1 >= tmp2, then label coordinate:

[0021] TX = TD[i] + tmp1;

[0022] Otherwise, label coordinate TX = TD[j] - tmp2;

[0023] S7, using two base stations with equal Y coordinates in the X direction, a total of m triangles that satisfy the above conditions can be found, and m coordinate values X of the label T are solved:

[0024] TX[0] ~ TX[m-1];

[0025] m = n * (sqrt(n) - 1) / 2, where n = 4, 9, 16, 25, 36, …;

[0026] Similarly, using two base stations with equal X coordinates in the Y direction, 9 Y coordinate values of the label T can also be solved: TY[0] ~ TY[8];

[0027] In the above embodiment: the above mode is not limited to this; as a preferred technical solution, it can also be preferred to select: arranging multiple base stations as equidistant squares; also including non-equidistant squares, but the calculation accuracy will be affected.

[0028] In one embodiment: because there are errors and fluctuations in the distance from the detected label to each base station. When the label is stationary, the 9 label coordinates X and Y solved at a certain time are not the same as the 9 label coordinates X and Y solved at the next time. Therefore, the coordinates X and Y of the 9 labels at a certain time can be processed by filtering, averaging, etc. to obtain more accurate label coordinates TX and TY. At the same time, due to the errors and fluctuations in the distance from the detected label to each base station, it is also possible to obtain less than 9 label coordinates X or Y, but still can be processed by filtering, averaging, etc. to obtain more accurate label coordinates TX and TY;

[0029] In the above embodiment: the above mode is not limited to this; as a preferred technical solution, it can also be preferred to select: filtering or averaging processing by Kalman filtering; wherein, combining the prediction model of the label movement and the statistical characteristics of the measurement error, the label coordinate values obtained in the current time period are comprehensively filtered.

[0030] Wherein in an embodiment: the system for quickly solving the coordinates of the tag by using multiple UWB base stations only needs to ensure the size and error of the installation of the coordinates AX and AY of each base station, without considering the installation size and error of the tag and the base station in the Z coordinate direction (vertical direction). At the same time, the solving process of the method is simple and clear, which is conducive to the engineering application of the method.

[0031] On the other hand, based on the above-mentioned system, the technical solution also provides a terminal for quickly solving the coordinates of the tag by using UWB base stations, in addition to the above-mentioned system, the terminal is composed of a display, a memory and a processor, wherein the display and the memory are connected with the processor respectively; the memory is used to store the system and perform work according to the running mode of the system.

[0032] Compared with the prior art, the beneficial effects of the present application are:

[0033] I. The method for solving the coordinates of the tag by using 2 base stations and 3 base stations in the conventional technology has some problems, such as no solution, conjugate coordinate solution, etc.; and through the positioning system and the fast solving method proposed in the present application, the positioning accuracy and stability are improved by using multiple base stations for simultaneous positioning; and because the position of the tag is estimated and tracked, the uncertainty and change of the tag in motion can be better handled, so that better tag motion tracking effect is realized.

[0034] II. Compared with the conventional technology, the filter positioning technology based on multiple base stations in the present application can be applied to a wider range of application scenarios, because it can flexibly add or reduce the number of base stations according to actual needs to adapt to different application scenarios. DETAILED DESCRIPTION

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0036] Figure 1 Schematic diagram of the new method for quickly solving the coordinates TX and TY of the tag by using 9 UWB base stations;

[0037] Figure 2 Flowchart of the new method for quickly solving the coordinates TX and TY of the tag by using multiple UWB base stations. DETAILED DESCRIPTION

[0038] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below;

[0039] It is important to note that terms such as "first," "second," "symmetric," and "array" are used only to distinguish between descriptive and positional descriptions and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, features specified with terms such as "first" or "symmetric" may explicitly or implicitly include one or more of that feature; similarly, when the quantity of certain features is not limited by words such as "two" or "three," it should be noted that such features also explicitly or implicitly include one or more features.

[0040] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "below" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0041] In this invention, unless otherwise explicitly specified and limited, terms such as "installation," "connection," and "fixation" should be interpreted broadly; for example, they can refer to a fixed connection, a detachable connection, or an integral molding; they can refer to a mechanical connection, a direct connection, a welding connection, or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the accompanying drawings and specific circumstances.

[0042] In existing technologies, when solving for the tag coordinates (TX, TY) using two quadratic equations based on two base stations commonly used in traditional technologies, two conjugate coordinate solutions are generated. Since only information from two base stations is used, this solution cannot uniquely determine the tag's location, and determining which solution is correct is not easy.

[0043] Using three base stations, a common approach in traditional technology, to solve for the tag coordinates T[TX, TY] using a system of three quadratic equations can yield a unique solution, but in practical applications, there may be situations where no solution is found. Although methods such as Angle-of-Arrival (TOA) and Time Difference of Arrival (TDOA) have been proposed to solve this problem, issues such as solution selection and accuracy still exist in practical engineering applications.

[0044] For this purpose, please refer to Figures 1-2 The present invention provides a technical solution to solve the above-mentioned technical problems: a system for quickly solving tag coordinates using multiple UWB base stations;

[0045] Please refer to Figure 1 , Figure 1 A schematic diagram of a new method for quickly solving the tag coordinates TX and TY using 9 UWB base stations;

[0046] It is understood that, in this specific embodiment, nine base stations are used in the figure to assist in the explanation of this specific embodiment, but the number of UWB base stations in this specific embodiment is not limited, and it is preferred to include more than three base stations.

[0047] The base stations communicate with the receiver by transmitting short pulse signals, and interact with each other to establish three-dimensional positions. There are at least three base stations, and each base station is arranged in an array uniformly in the top-down projection view.

[0048] Preferably, based on actual needs, multiple base stations can be arranged in a square with equal spacing; however, squares with unequal spacing can also be included.

[0049] The base stations solve for the tag coordinates through the following steps:

[0050] S1. Use multiple base stations to send signals to the tag, and calculate the distance or position between the tag and each base station by measuring the signal propagation time or signal strength; based on the distance or position information, interactively realize the tag's positioning, tracking and navigation applications;

[0051] Understandably, the key to solving the tag coordinates is to find two base stations with equal Y coordinates and unequal X coordinates in the X direction, and two base stations with equal X coordinates and unequal Y coordinates in the Y direction.

[0052] In this scheme, the ranging values ​​TD[i] (i=0,1,2,…n,n=4,9,16,25,36…) of tag T to each base station are obtained.

[0053] S2. The location of the tag is determined by selecting two base stations located at different locations and calculating the azimuth parameters between them; wherein the base stations have the same Y coordinate in the plane, but different X coordinates;

[0054] In this scheme, find two base stations (A[i] and A[j]) with equal Y coordinates and unequal X coordinates in the X direction;

[0055] Understandably, in this specific embodiment, in order to determine the area where the tag is located, thereby narrowing down the possible location range of the tag, specifically, since when the tag is equidistant from the base station in the X direction, its possible location falls on a straight line perpendicular to the X-axis; and by finding two base stations with unequal X coordinates but equal Y coordinates, it can be determined that the area where the tag is located is a certain area on this straight line, thereby narrowing down the possible location range of the tag and improving the positioning accuracy.

[0056] S3. Based on the Y and X coordinate parameters of the base station in S2; construct a triangle using the distance between the tag and the base station, and the distance between the two base stations; calculate the height of the line connecting the two base stations using the formula for measuring the three sides of the triangle; this height is used to calculate the actual distance between the tag and the two base stations, thus obtaining the tag's position;

[0057] Specifically, in S3, the triangle formed by the line connecting the two base stations and the distances TD[i] and TD[j] from the tag to the two base stations is determined;

[0058] The height H of the line connecting the two base stations can be calculated using the formula for finding the height of a triangle given its three sides.

[0059] Understandably, in this specific implementation, the distance from the tag to the two base stations and the height difference between them are determined. Since two base stations with equal Y coordinates and unequal X coordinates have been identified in step 2, these two base stations can be considered as a straight line segment forming the distance between the tag and the base station. Using the known distance and the calculated height difference, the tag's coordinates can be deduced using the geometric relationships of triangles. The key to this step is determining the height difference H of the line connecting the two base stations, which can be calculated using the formula for finding the height of a triangle given its three sides. Finally, the coordinate position of the tag is determined.

[0060] Furthermore, the triangle formed by the line connecting the two base stations and the distance from the tag to the two base stations is determined, and the height corresponding to the side of the line connecting the two base stations is calculated.

[0061] It should be noted that in practical applications, this step may result in multipath effects: that is, the UWB signal may travel through multiple paths, which may lead to an increase in ranging error. Therefore, this step can be introduced as an additional technique to use a multipath attenuation model for error compensation, or an enhanced UWB antenna can be used to reduce the impact of multipath effects.

[0062] It should be noted that in practical applications, this step may be affected by the fact that in some areas, UWB signals may be blocked by objects such as buildings and obstacles, resulting in signal attenuation or loss, which may affect positioning accuracy. Therefore, this step can be introduced as an additional technology to increase the number of base stations so as to collect and process data in multiple locations, or to use a multipath attenuation model for error compensation.

[0063] It should be noted that in practical applications, this step may lead to signal interference and decreased positioning accuracy due to the existence of multiple tags in an area. Therefore, this step can be introduced as an additional technology to use multiple base stations to form a network in order to track multiple tags simultaneously and identify and distinguish them through the unique identifier of the tag.

[0064] It should be noted that in practical applications, this step may lead to increased positioning errors due to the low signal-to-noise ratio. Therefore, this step can be introduced as an additional technique to enhance signal quality using signal processing techniques, or to improve signal reception sensitivity using an enhanced UWB antenna.

[0065] S4. After determining the height parameters corresponding to the connection between the two base stations, calculate the distance from the tag to the two base stations; calculate the position of the tag relative to the two base stations using the spacing parameters.

[0066] Specifically, the distance from the tag to the first base station is calculated and named tmp1;

[0067] Calculate the distance from the tag to the second base station and name it tmp2;

[0068] For example, tmp1 ≥ tmp2;

[0069] If the tag position moves tmp1 distance along the direction of the first base station, then the tag position moves tmp2 distance along the direction of the second base station.

[0070] Specifically, calculate the distances tmp1 and tmp2 from the tag TX coordinate point to the two base stations A[i] and A[j], respectively, using the following formula:

[0071] tmp1=sqrt(TD[i]*TD[i]-H*H);

[0072] tmp2=sqrt(TD[j]*TD[j]-H*H);

[0073] Where tmp1 is greater than or equal to tmp2, then the tag coordinates are:

[0074] TX = TD[i] + tmp1;

[0075] Otherwise, label coordinates:

[0076] TX = TD[j] - tmp2.

[0077] For example, suppose that in the current environment, there are two base stations A[i] and A[j], with coordinates (x[i], y[i], z[i]) and (x[j], y[j], z[j]) respectively;

[0078] Assume the coordinates of tag T are (x[T], y[T], z[T]); base stations A[i] and A[j] receive the arrival times TD[i] and TD[j] of tag T, respectively; according to the formula, we first need to calculate the distances tmp1 and tmp2 from the coordinates of tag T to the two base stations A[i] and A[j], respectively:

[0079] tmp1=sqrt((x[T]-x[i])^2+(y[T]-y[i])^2+(z[T]-z[i])^2)-H

[0080] tmp2=sqrt((x[T]-x[j])^2+(y[T]-y[j])^2+(z[T]-z[j])^2)-H

[0081] If tmp1 is greater than or equal to tmp2, then the tag coordinates are:

[0082] TX = TD[i] + tmp1;

[0083] Otherwise, label coordinates:

[0084] TX = TD[j] - tmp2.

[0085] Let's assume again:

[0086] TD[i]=10, TD[j]=11, H=3;

[0087] The coordinates of label T can be calculated using the following steps:

[0088] tmp1=sqrt((x[T]-x[i])^2+(y[T]-y[i])^2+(z[T]-z[i])^2)-3

[0089] tmp2=sqrt((x[T]-x[j])^2+(y[T]-y[j])^2+(z[T]-z[j])^2)-3

[0090] Based on the calculated values ​​of tmp1 and tmp2, determine the formula for calculating TX:

[0091] If tmp1 >= tmp2, then TX = TD[i] + tmp1;

[0092] Otherwise, TX = TD[j] - tmp2

[0093] Substituting the calculated TX value into the formula, we obtain the coordinate X value of label T:

[0094] X = TX

[0095] Specifically, using the two height values ​​obtained in step 3 above, the three-dimensional coordinates (TX, TY, TZ) of the tag are calculated. Specifically, using the distances TD from the two base stations to the tag and the height difference H between the two base stations, two spherical equations can be constructed, thereby solving for the two possible coordinate points of the tag.

[0096] For example, assuming the distances between the two base stations A[i] and A[j] calculated in step 3 are TD[i] and TD[j], and the heights corresponding to the two edges are H1 and H2 respectively, the coordinates TX and TY of the tag can be calculated using the following formula:

[0097] TX=(H1^2-H2^2+d^2) / (2*d)TY=sqrt(H1^2-TX^2)

[0098] Where d is the distance between A[i] and A[j], which can be obtained through the location information between base stations. Thus, the tag's location coordinates can be calculated based on the ranging results and the base station location information.

[0099] It is understood that in this specific embodiment, in actual applications, factors such as noise and errors may affect the ranging results and position calculations. Therefore, filtering, averaging, and other processing may be required to improve accuracy and precision.

[0100] S5. On the X-axis, find base stations with the same Y-coordinate but different X-coordinates; for each base station, use the distance between the two corresponding base stations and the distance from the tag to these two base stations to calculate the tag's position;

[0101] Specifically, on the Y-axis, base stations with the same X coordinate but different Y coordinates are found, and the Y coordinate of the tag is calculated using the same method to determine the tag's position in the network by combining its X and Y coordinates.

[0102] Specifically, by using two base stations with equal Y coordinates in the X direction, a total of m triangles that satisfy the above conditions can be found and the m coordinate values ​​X of the tag T can be solved: TX[0]~TX[m-1];

[0103] m = n * (sqrt(n) - 1) / 2, where n = 4, 9, 16, 25, 36, ...

[0104] For example, suppose there are 6 base stations (n=6) in the current environment, and their X-direction coordinates are equal; using these 6 base stations, m triangles that satisfy the conditions can be found, where:

[0105] m = 6 * (sqrt(6) - 1) / 2 = 9

[0106] Nine triangles can be found. Assuming the two base stations corresponding to the i-th triangle are numbered i and j, the coordinates X[i] and X[j] of tag T can be calculated using these two base stations. According to the above formula, a total of nine coordinate values ​​need to be calculated. The specific method is as follows:

[0107] For the first triangle: select the first and second base stations to calculate the coordinate value X[0] of tag T;

[0108] For the second triangle: select the first and third base stations to calculate the coordinate value X of tag T[1];

[0109] For the third triangle: select the first and fourth base stations to calculate the coordinate value X of tag T[2];

[0110] For the fourth triangle: select the first and fifth base stations to calculate the coordinate value X of tag T[3];

[0111] For the 5th triangle: select the 1st and 6th base stations to calculate the coordinate value X of tag T[4];

[0112] For the 6th triangle: select the 2nd and 3rd base stations to calculate the coordinate value X of tag T[5];

[0113] For the 7th triangle: select the 2nd and 4th base stations to calculate the coordinate value X of tag T[6];

[0114] For the 8th triangle: select the 2nd and 5th base stations to calculate the coordinate value X of tag T[7];

[0115] For the 9th triangle: select the 2nd and 6th base stations to calculate the coordinate value X of tag T[8];

[0116] In this way, the nine coordinate values ​​of tag T can be calculated using the given six base stations.

[0117] Similarly, by using two base stations with equal X coordinates in the Y direction, the m Y coordinate values ​​of tag T can also be calculated:

[0118] TY[0]-TY[m-1].

[0119] In this scheme, the possible locations of the tag are constrained by a straight line formed by two base stations with equal Y coordinates in the X direction, limiting the tag's possible location to this line. By selecting suitable base stations along this line, multiple triangles can be formed, thus solving for the tag's location. This approach improves the accuracy of tag positioning while reducing positioning errors caused by base station errors, multipath effects, and other factors.

[0120] Specifically, after determining two base stations A[i] and A[j], their coordinates in the X direction are different, but they are the same in the Y direction. Therefore, the distances TD[i] and TD[j] between these two base stations can form a triangle of height H. The base of this triangle is the distance between A[i] and A[j] (that is, the distance difference between the two base stations), and the distance from tag T to this base is half of the distance difference between the tag and the two base stations in the X direction.

[0121] Using the above method, the coordinate value X of tag T in the X direction can be solved using these two base stations; similarly, the coordinate value Y of tag T in the Y direction can also be solved using two other base stations with equal Y coordinates; in this way, by combining all base stations that meet the conditions, multiple sets of coordinate values ​​of tag T can be obtained.

[0122] For example, suppose there are three base stations A[1], A[2] and A[3] in the current environment, and their coordinates are (1,2,0), (4,2,0) and (3,5,0) respectively;

[0123] The distances from tag T to these three base stations are 3, 2, and 4, respectively. This information is used to calculate the coordinates of tag T.

[0124] The first step is to calculate the height H[1] of the line connecting A[1] and A[2] and the height H[2] of the line connecting A[1] and A[3] according to the formula:

[0125] H[1]=sqrt(3^2-((4-1)^2) / 4)=sqrt(23) / 2H[2]=sqrt(4^2-((3-1)^2+(5-2)^2) / 4)=sqrt(10) / 2

[0126] The second step is to use this information to calculate the coordinates of label T:

[0127] X=[(2*H[1]*H[2]) / (TD[1]sqrt(TD[2]^2-H[2]^2))]+[(2H[1]*H[2]) / (TD[2]sqrt(TD[1]^2-H[1]^2))]+[(TD[1]^2-TD[2]^2) / (2TD[1])]+(1+4) / 2

[0128] =(sqrt(23) / 10)+(sqrt(10) / 5)+1.5

[0129] ≈2.565

[0130] Therefore, the X coordinate of label T is approximately 2.565;

[0131] It is understandable that the Y and Z coordinates of label T can be calculated using A[1] and A[3], which have equal Y coordinates in the X direction, and A[2] and A[3], which have equal Y coordinates in the X direction. The final coordinates of label T are (2.565, 2.708, 0).

[0132] S6. Filter or average the obtained location information;

[0133] In this scheme, the detected distances from the tags to each base station contain errors and fluctuations. When the tags are stationary, the X and Y coordinates of the m tags calculated at a certain moment are not the same as those calculated at the next moment. Therefore, by filtering and averaging the X and Y coordinates of the m tags at a certain moment, more accurate tag coordinates TX and TY can be obtained for that moment.

[0134] Meanwhile, since the distance from the detected tag to each base station has errors and fluctuations, it is possible that fewer than m tag coordinates X or Y are obtained. However, the tag coordinates TX and TY can still be obtained by filtering and averaging the obtained tag coordinates X and Y respectively.

[0135] A novel method for rapidly calculating tag coordinates using multiple UWB base stations only requires ensuring the dimensions and errors of the coordinates AX[i] and AY[i] of each base station, without needing to consider the installation dimensions and errors of the tag and base station in the Z-coordinate direction (vertical direction). Furthermore, this method is simple and straightforward, facilitating its engineering applications.

[0136] In this scheme, Kalman filtering or averaging is preferred; in particular, the tag coordinate values ​​obtained in the current time period are comprehensively filtered by combining the tag movement prediction model and the statistical characteristics of measurement error.

[0137] Specifically, the state vector is set as follows:

[0138] X = [x,y,vx,vy]T;

[0139] Where x and y represent the coordinates of the tag, and vx and vy represent the velocities of the tag in the x and y directions;

[0140] The status is:

[0141] X(k)=AX(k-1)+BU(k)+w(k-1);

[0142] Where A is the state transition matrix, B is the input matrix, U is the input vector, and w is the process noise.

[0143] The observation is as follows:

[0144] Z(k) = HX(k) + v(k);

[0145] Where Z is the observation vector, H is the observation matrix, and v is the observation noise.

[0146] For example, suppose its position is x, its velocity is v, and its time step is dt:

[0147] Predicted status:

[0148]

[0149] Predicting covariance:

[0150]

[0151] Where Q represents the covariance matrix of the process noise, which can be determined according to the specific application; then, the observed value z is used for updating:

[0152] Calculate the Kalman gain:

[0153]

[0154] Update status:

[0155]

[0156] Update covariance:

[0157] P=(I-KH)P'

[0158] Where H is the observation matrix and R is the covariance matrix of the observation noise; the values ​​of these matrices can be determined according to the specific application and actual conditions.

[0159] This requires defining state variables and observation variables; therefore, in this example, the state variables are the tag's position and velocity in the X direction, and its position and velocity in the Y direction, totaling four. The observation variable is the distance difference between the tag and the two base stations.

[0160] When performing Kalman filtering for the first time, it is necessary to initialize the state variables, i.e., the initial values ​​of the tag's position and velocity, and the initial value of the covariance matrix P of the estimation error. In this example, it is assumed that the initial position of the tag is (0,0), the velocity is (0,0), and the covariance matrix P of the estimation error is the identity matrix;

[0161] Each Kalman filter operation requires a prediction step and an update step. In the prediction step, the state transition matrix A, control matrix B, and covariance matrix Q are used to predict the tag's state variables at the next time step and to estimate the covariance matrix of the error. In this example, it is assumed that the tag's velocity remains constant at each time step; therefore, the state transition matrix A is:

[0162] A=[1 1 0 0; 0 1 0 0; 0 0 1 1; 0 0 0 1]

[0163] The control matrix B is:

[0164] B = [0 0; 0 0; 0 0; 0 0]

[0165] The covariance matrix Q is:

[0166] Q=[1 0 0 0; 0 1 0 0; 0 0 1 0; 0 0 0 1]

[0167] In the update step, the tag's state variables and the estimated error covariance matrix need to be updated using the observed variables, the observation matrix H, and the covariance matrix R of the observation error. In this example, the covariance matrix R of the observation error is assumed to be an identity matrix. The choice of the observation matrix H is crucial; it needs to map the state variables to the observation space. In this example, it is assumed that the distance between the tag and the base station is measured using the TOA method, therefore the observation matrix H is:

[0168] H=[-1 0 1 0; 0 0 0 0; 0-1 0 1; 0 0 0 0]

[0169] It should be noted that the observation matrix H here is a 4x4 matrix, which represents the mapping relationship between state variables and observed variables; specifically, it can be represented as follows:

[0170] H=[1,0,0,0;0,1,0,0;0,0,1,0;0,0,0,0];

[0171] Each row in the H matrix corresponds to an observed variable, and each column corresponds to a state variable. Since only the label's position coordinates can be observed, the last row of the H matrix is ​​a vector of all zeros.

[0172] It is understandable that the advantages of the above filtering method are:

[0173] (1) High real-time performance: The formula has a small amount of computation, so it can quickly estimate and predict the position and speed of the tag in real time.

[0174] (2) High accuracy: Since the formula uses the Kalman filter algorithm, the current estimate can be adjusted based on previous observations and predictions, thereby improving the accuracy of the estimate.

[0175] (3) Good stability: The formula adjusts the estimation error covariance matrix by predicting the error covariance matrix, so that the trend of the estimation error becomes stable, thereby improving the stability of the estimation.

[0176] (4) Wide applicability: This formula can be applied to various types of tag movement trajectories and can adapt to different environments and conditions, thus having high applicability.

[0177] It should be noted that, in this specific implementation, all the above-mentioned system processes and the standards for actual deployment and use of base stations are based on GB / T 15151-2014 "Electromagnetic Compatibility Requirements and Measurement Methods for Radio Equipment" and GB / T3100-2018 "Transmit Power Harmony Requirements and Measurement Methods for Radio Equipment and Systems" to determine the selection of parameters such as transmit power, frequency range, and compatibility.

[0178] It is understood that in this specific embodiment, in a real environment, factors such as base station location error, multipath effect of signal transmission, and signal noise may exist, all of which can lead to ranging errors. To reduce the impact of these errors, methods such as base station calibration and signal filtering can be used.

[0179] It is understandable that, in this specific embodiment, in a real environment, signals will experience reflection and scattering along multiple paths during propagation, resulting in multipath effects and increased distance measurement errors. Multipath suppression techniques or the introduction of multiple base stations can be used for positioning in multipath environments.

[0180] It is understood that, in this specific embodiment, interference signals from other wireless devices may exist in the actual environment. These interference signals can interfere with the positioning system, thereby increasing the positioning error. Interference suppression can be achieved using methods such as frequency-selective reception technology and spatial interference cancellation technology.

[0181] Example 1

[0182] To make the specific embodiments of the present invention more apparent and understandable, detailed exemplary descriptions of the specific embodiments of the present invention are provided below. The present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the embodiments disclosed below.

[0183] This embodiment is based on the relevant principles described in the above specific embodiments, and all related descriptions below are based on the scope defined by the above specific embodiments; wherein, in exemplary applications:

[0184] S1. Select an appropriate number of base stations to deploy in the area to be monitored, and accurately record their location information;

[0185] S2. Randomly move the tag within the area to be monitored and record the signal strength information between the tag and the base station;

[0186] S3. Using signal strength information and pre-recorded base station location information, determine the distance between the tag and each base station;

[0187] S4. Calculate the tag's location coordinates using the distance information between the tag and the two base stations. This can be achieved using techniques such as triangulation.

[0188] S5. For the calculated tag position coordinates, algorithms such as Kalman filtering can be used for smoothing to improve accuracy and stability.

[0189] S6. During the monitoring process, abnormal situations can be detected and dealt with in a timely manner by monitoring the location information of the tags in real time;

[0190] S7. If multiple tags need to be monitored, they can be distinguished by assigning unique tag IDs, thereby enabling simultaneous monitoring of multiple tags.

[0191] S8 can transmit monitoring data to the cloud for analysis and processing to further improve monitoring efficiency and accuracy.

[0192] The embodiments described above merely illustrate implementation methods for relevant practical applications of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

[0193] Example 2

[0194] To make the specific embodiments of the present invention more apparent and understandable, detailed exemplary descriptions of the specific embodiments of the present invention are provided below. The present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the embodiments disclosed below.

[0195] This embodiment is based on the specific implementation methods described above and the relevant principles described in Embodiment 1. All related descriptions below are based on the specific implementation methods described above and the scope defined in Embodiment 1; where exemplary applications are used:

[0196] S1. Determine the location and layout of the base stations: Determine the coordinate location and layout of the base stations. There can be 3 or more base stations, arranged along the X and Y coordinate directions to ensure the stability of coverage and signal strength.

[0197] S2, Receive base station signal: The tag receives the signal sent by the base station and records the arrival time;

[0198] S3. Calculate the distance between the tag and the base station: Calculate the distance between the tag and the base station using time of arrival (TOA) or Time-of-Flight (ToF) technologies.

[0199] S4. Kalman Filter: Based on historical data and current distance measurements, the Kalman filter algorithm is used to estimate and predict the tag position.

[0200] S5. Determine the label position: Based on the Kalman filter results, determine the position of the label in the two-dimensional plane;

[0201] S6. Tag identification and data processing: After receiving the base station signal, the tag determines its identity and status through identification and processing, and performs corresponding response operations as needed;

[0202] S7. Deployment and Maintenance: Deploy base stations and tags in appropriate locations and perform necessary maintenance and adjustments to ensure the stability and reliability of the system;

[0203] S8. Data Security and Privacy Protection: Take necessary security measures to protect the confidentiality, integrity and availability of data, and ensure that users' privacy is not violated;

[0204] The embodiments described above merely illustrate implementation methods for relevant practical applications of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A system for rapidly determining tag coordinates using multiple UWB base stations, comprising base stations that communicate with receivers by transmitting short pulse signals and interact with each other to establish three-dimensional positions, characterized in that: The number of base stations is at least three, and each base station is arranged in an array uniformly in a top-down projection view. The base stations solve for the tag coordinates through the following steps: S1. Use multiple base stations to send signals to the tag, and calculate the distance or position between the tag and each base station by measuring the signal propagation time or signal strength; based on the distance or position information, interactively realize the tag's positioning, tracking and navigation applications; S2. The location of the tag is determined by selecting two base stations located at different locations and calculating the azimuth parameters between them; The base stations have the same Y coordinate in the plane, but different X coordinates; S3. Based on the Y and X coordinate parameters of the base station in S2; construct a triangle using the distance between the tag and the base station, and the distance between the two base stations; calculate the height corresponding to the line connecting the two base stations using the formula for measuring the three sides of the triangle; this height is used to calculate the actual distance between the tag and the two base stations, thereby obtaining the position of the tag; S4. After the height parameter corresponding to the connection between the two base stations is determined, the distance from the tag to the two base stations is calculated; the position of the tag relative to the two base stations is calculated using the spacing parameter. Specifically, the distance from the tag to the first base station is calculated and named tmp1; Calculate the distance from the tag to the second base station and name it tmp2; For example, tmp1 ≥ tmp2; The tag position then moves a distance tmp1 along the direction of the first base station; otherwise, the tag position moves a distance tmp2 along the direction of the second base station. S5. On the X-axis, find the base stations that have the same Y coordinate but different X coordinates; for each base station, calculate the position of the tag using the distance between the two base stations and the distance from the tag to the two base stations; Specifically, on the Y-axis, base stations with the same X coordinate but different Y coordinates are located, and the Y coordinate of the tag is calculated using the same method to determine the tag's position in the network by combining its X and Y coordinates. S6. Filter or average the obtained location information; In S1, the ranging value TD[i] of the tag to each base station is obtained, i = 0, 1, 2, ..., n, n = 4, 9, 16, 25, 36...

2. The system for rapidly solving tag coordinates using multiple UWB base stations as described in claim 1, characterized in that: In S2, find two base stations A[i] and A[j] whose Y coordinates are equal and X coordinates are not equal in the X direction.

3. The system for rapidly solving tag coordinates using multiple UWB base stations according to any one of claims 1 to 2, characterized in that: In S3, a triangle is formed by the line connecting the two base stations and the distances TD[i] and TD[j] from the tag to the two base stations; Using the formula for finding the height of a triangle given its three sides, the height H corresponding to the side of the line connecting the two base stations is calculated.

4. The system for rapidly solving tag coordinates using multiple UWB base stations as described in claim 3, characterized in that: In step S4, the distances tmp1 and tmp2 from the tag coordinates to the two base stations A[i] and A[j] are calculated using the following formula: tmp1=sqrt(TD[i]*TD[i]-H*H); tmp2=sqrt(TD[j]*TD[j]-H*H); Where tmp1 is greater than or equal to tmp2, then the tag coordinates are: TX = TD[i] + tmp1; Otherwise, label coordinates: TX = TD[j] - tmp2.

5. The system for rapidly solving tag coordinates using multiple UWB base stations as described in claim 4, characterized in that: In step S5, using two base stations with equal Y coordinates in the X direction, a total of m triangles satisfying the above conditions can be found, and the m coordinate values ​​X of the tag can be solved: TX[0]~TX[m-1]; m = n * (sqrt(n) - 1) / 2, where n = 4, 9, 16, 25, 36, ...; At the same time, by using two base stations with equal X coordinates in the Y direction, the m Y coordinate values ​​of the tag can also be calculated: TY[0]~TY[m-1].

6. The system for rapidly solving tag coordinates using multiple UWB base stations as described in claim 5, characterized in that: In step S6, Kalman filtering is used for filtering or averaging; wherein, the tag coordinate values ​​obtained in the current time period are comprehensively filtered by combining the tag movement prediction model and the statistical characteristics of measurement error.

7. The system for rapidly solving tag coordinates using multiple UWB base stations as described in claim 6, characterized in that: The state vector is set as follows: X = [x, y, vx, vy]T; Where x and y represent the coordinates of the tag, and vx and vy represent the velocities of the tag in the x and y directions; The status is: X(k)=AX(k-1)+BU(k)+w(k-1); Where A is the state transition matrix, B is the input matrix, U is the input vector, and w is the process noise. The observation is as follows: Z(k) = HX(k) + v(k); Where Z is the observation vector, H is the observation matrix, and v is the observation noise.

8. A storage medium for rapidly solving tag coordinates in a UWB base station, comprising the system as described in any one of claims 1 to 7, characterized in that: It also includes a display, a memory, and a processor, wherein the display and the memory are respectively connected to the processor; The memory is used to store the system.

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