An optimized direction finding and ranging positioning method based on UWB

Abstract

The present invention relates to the field of positioning technology, and in particular, to an optimized direction finding and ranging positioning method based on UWB. The method is applied to a measuring device, the measuring device includes at least m base stations and tags, each base station includes an antenna array consisting of a main antenna and n slave antennas; the method includes: obtaining the final angle data between the tag and the base station; obtaining the first distance data from the tag to each base station through a preset ranging algorithm; optimizing the first distance data to obtain the second distance data; optimizing the second distance data again through a least squares estimation model to obtain the final distance data; and finally obtaining the location of the tag according to the final distance data and the final angle data and the preset base station position. This solves the problem of how to obtain more accurate measurement angles and distances in a complex environment for more accurate positioning of tags.

Description

Technical Field

[0001] The present invention relates to the field of positioning technology, and in particular to an optimized direction-finding and ranging positioning method based on UWB. Background Art

[0002] The traditional UWB-TDOA / AOA (TODA, Time Difference of Arrival, a method of positioning using time difference; AOA, Angle of Arrival, a positioning algorithm based on ranging) method has the problem of high base station consumption and poor positioning in areas with obstructions in complex environments. UWB-TODA can determine the distance of the signal source by measuring the time it takes for the signal to arrive at the monitoring station; UWB-AOA senses the arrival direction of the signal from the transmitting node through certain hardware devices, calculates the relative orientation or angle between the receiving node and the anchor node, and then uses triangulation or other methods to calculate the position of the unknown node. Both have defects in this regard. For example, large factories have high shelves, high ground piles, cargo storage areas blocked by walls, and separately separated houses. The traditional method of laying base stations is costly and has low measurement accuracy. Summary of the invention

[0003] In order to solve the problem of how to obtain more accurate measurement angles and distances in complex environments for more accurate positioning of tags, the present invention provides an optimized direction-finding and ranging positioning method based on UWB.

[0004] In a first aspect, a UWB-based optimized direction finding and ranging positioning method is applied to a measuring device, the measuring device comprising at least m base stations and tags, each of the base stations comprising an antenna array consisting of a main antenna and n slave antennas;

[0005] The method comprises:

[0006] Acquire final angle data between the tag and the base station;

[0007] Obtaining first distance data from the tag to each base station by a preset distance measurement algorithm;

[0008] Optimizing the first distance data to obtain second distance data;

[0009] Obtaining an estimated value of the tag position according to the final angle data, the preset position of the base station, the second distance data, and a pre-constructed least squares estimation model, wherein the pre-constructed least squares estimation model represents a mapping relationship between the angle between the tag and the base station, the distance between the tag and the base station, the tag position, and the base station position;

[0010] Obtaining third distance data from the tag to each base station according to the estimated value of the tag position and the base station position;

[0011] Compare the third distance data with the second distance data to obtain a first dynamic threshold;

[0012] Obtaining final distance data from the tag to each base station according to the first dynamic threshold and the third distance data, wherein the final distance data is the portion of the third distance data that does not exceed the first dynamic threshold;

[0013] The tag position is obtained according to the final angle data, the final distance data, and the base station position.

[0014] In some embodiments, obtaining final angle data between the tag and the base station as described includes:

[0015] Acquire the measurement signal from the tag to each slave antenna and the main antenna, and calculate and obtain the first phase difference data between each slave antenna and the main antenna;

[0016] Optimizing the first phase difference data to obtain final phase difference data;

[0017] Obtaining first angle data according to the final phase difference data;

[0018] The first angle data is mean filtered to obtain final angle data.

[0019] In some embodiments, the first phase difference data is optimized as described to obtain final phase difference data, including:

[0020] Divide [-180°~180°] into 360 / n intervals;

[0021] A first threshold th1 and a second threshold th2 are determined according to the first phase difference data, wherein the first threshold th1 and the second threshold th2 are:

[0022] th1=sin(pi / 2+pi / n)

[0023] th2=sin(3*pi / 2+pi / n)

[0024] The final phase difference data is determined according to the first threshold and the second threshold, wherein a sine value of the final phase difference data is between the first threshold and the second threshold.

[0025] In some embodiments, obtaining the first angle data according to the final phase difference data includes:

[0026] Performing weighted calculation according to the final phase difference data and a preset weight corresponding to the final phase difference data to obtain the first angle data;

[0027] The closer the target phase difference data is to 0°, the greater the weight of the target phase difference data is, and the target phase difference data is any data in the final phase difference data.

[0028] In some embodiments, after performing mean filtering on the first angle data to obtain final angle data, PI filtering may be performed on the final angle data.

[0029] In some embodiments, the optimizing the first distance data to obtain the second distance data includes:

[0030] According to a preset distance measurement algorithm, the distance values ​​between the tag and each base station are measured multiple times to obtain multiple distance values;

[0031] calculating a variance of the plurality of distance values;

[0032] obtaining a second dynamic threshold according to the variance of the plurality of distance values ​​and the plurality of distance values;

[0033] Optimizing the first distance data according to the second dynamic threshold to obtain first optimized distance data;

[0034] According to a preset ranging algorithm, multiple measurements are performed to obtain frequency deviation values ​​between the tag and each base station, thereby obtaining multiple frequency deviation values;

[0035] Calculating the variance of the multiple frequency offset values;

[0036] Obtaining a third dynamic threshold according to the variance of the plurality of frequency offset values ​​and the plurality of frequency offset values;

[0037] Optimizing the first optimized distance data according to the third dynamic threshold to obtain second optimized distance data;

[0038] The second optimized distance data is mean filtered to obtain the second distance data.

[0039] In some embodiments, after the first distance data is optimized to obtain the second distance data, the second distance data may be subjected to EKF filtering.

[0040] In some embodiments, in the antenna array, with the main antenna as the center, n slave antennas are evenly distributed around the main antenna at 360 / n degrees.

[0041] The distance between each slave antenna and the main antenna is equal and less than or equal to half the wavelength of the measurement signal.

[0042] In some embodiments, the number m of base stations is greater than or equal to 3.

[0043] In order to solve the problem of how to obtain more accurate measurement angles and distances in a complex environment for more accurate positioning of tags, the present invention has the following advantages:

[0044] 1. Effectively solve the influence of unstable angle measurement boundary value and improve the angle measurement accuracy.

[0045] 2. Effectively optimize the static ranging stability and dynamic ranging speed and accuracy.

[0046] 3. Effectively eliminate NLOS interference and improve positioning stability and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic diagram of phase difference data from four slave antennas to the main antenna is shown;

[0048] Figure 2 A schematic diagram of the wrong label position at the same angle is shown;

[0049] Figure 3 A flow chart of a method for optimizing direction finding and ranging based on UWB is shown;

[0050] Figure 4 A flow chart for optimizing distance data is shown. DETAILED DESCRIPTION

[0051] The present disclosure will now be discussed with reference to several exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and thus implement the present disclosure, rather than implying any limitation on the scope of the present disclosure.

[0052] As used herein, the term "including" and its variants are to be interpreted as open-ended terms meaning "including but not limited to". The term "based on" is to be interpreted as "based at least in part on". The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment". The term "another embodiment" is to be interpreted as "at least one other embodiment". The orientation or position relationship indicated by the terms "upper", "lower", "left", "right", "front", "back", "top", "bottom", "inner", "outer", "vertical", "horizontal", "lateral", "longitudinal" and the like is based on the orientation or position relationship shown in the accompanying drawings. These terms are mainly for better describing the present application and its embodiments, and are not used to limit the indicated devices, elements or components to have a specific orientation, or to be constructed and operated in a specific orientation. In addition, in addition to being used to indicate an orientation or position relationship, some of the above terms may also be used to indicate other meanings, such as the term "upper" may also be used to indicate a certain dependency or connection relationship in some cases. For those of ordinary skill in the art, the specific meanings of these terms in this application can be understood according to the specific circumstances. In addition, the terms "install", "set", "provided with", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection, or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be an internal connection between two devices, elements or components. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to the specific circumstances. In addition, the terms "first", "second", etc. are mainly used to distinguish different devices, elements or components (the specific types and structures may be the same or different), and are not used to indicate or imply the relative importance and quantity of the indicated devices, elements or components. Unless otherwise specified, "plurality" means two or more.

[0053] This embodiment discloses an optimized direction finding and ranging positioning method based on UWB, the method is applied to a measuring device, the measuring device includes at least m base stations and tags, each of the base stations includes an antenna array consisting of a main antenna and n slave antennas;

[0054] The method comprises:

[0055] Acquire final angle data between the tag and the base station;

[0056] Obtaining first distance data from the tag to each base station by a preset distance measurement algorithm;

[0057] Optimizing the first distance data to obtain second distance data;

[0058] Obtaining an estimated value of the tag position according to the final angle data, the preset position of the base station, the second distance data, and a pre-constructed least squares estimation model, wherein the pre-constructed least squares estimation model represents a mapping relationship between the angle between the tag and the base station, the distance between the tag and the base station, the tag position, and the base station position;

[0059] Obtaining third distance data from the tag to each base station according to the estimated value of the tag position and the base station position;

[0060] Compare the third distance data with the second distance data to obtain a first dynamic threshold;

[0061] Obtaining final distance data from the tag to each base station according to the first dynamic threshold and the third distance data, wherein the final distance data is the portion of the third distance data that does not exceed the first dynamic threshold;

[0062] The tag position is obtained according to the final angle data, the final distance data, and the base station position.

[0063] In this embodiment, a UWB-based optimized direction finding and ranging positioning method is provided. Figure 3 shown.

[0064] First, the measurement signals sent by the acquisition tag to the main antenna and each slave antenna of each base station are obtained by calculation, and then the phase difference data is obtained, and then the final angle data is obtained.

[0065] For example, a base station includes four slave antennas and one master antenna, and the collected measurement signals include measurement signals from the tag to the four slave antennas and measurement signals from the tag to the master antenna. Specifically, a switch chip is used to switch and select the master antenna and the four slave antennas according to the tag signal protocol distribution order to obtain the phase difference. The final angle data represents the angle between the tag and the base station. Since the distance from the tag to the base station is much greater than the distance between the antennas, it can be approximately considered that the angles between the tag and each antenna are equal, and the angle between the tag and the base station can be represented by the angle between the tag and any antenna.

[0066] Secondly, the first distance data from the tag to the base station is obtained through the preset DS-TWR (Double-Sided Two-Way Range) algorithm, and then the first distance data is optimized to obtain the second distance data. DS-TWR is used to measure the distance between devices.

[0067] Furthermore, the optimized second distance data is more accurate than the first distance data before optimization, and the tag position calculated using the optimized second distance data is more accurate.

[0068] Finally, a least squares estimation model is constructed with the angle between the tag and the base station, the distance between the tag and the base station, the tag position, and the base station position as parameters. The estimated value of the tag position is obtained through the final angle data, the preset base station position, and the second distance data. The third distance data is obtained through the estimated value of the tag position and the base station position. The third distance data is the estimated value of the distance from the tag to each base station obtained by the least squares estimation model; the third distance data and the second distance data are compared to obtain a first dynamic threshold. The first dynamic threshold is an empirical threshold. A more reliable and accurate distance threshold is obtained by comparing the estimated value of the distance obtained by the least squares estimation model with the actual measurement value obtained by the DS-TWR calculation. The distance data above the threshold in the third distance data is eliminated, and only the distance data below the threshold, that is, the final distance data, is used for calculation; finally, the tag position is obtained by the least squares estimation model using the final angle data, the final distance data, and the base station data.

[0069] For example, the second distance data includes four data of 67.1m, 64.9m, 65.8m, and 75.4m, and the third distance data includes four data of 76.9m, 65.7m, 65.4m, and 77.3m, then the first dynamic threshold range can be set to 65.5±2m, so the final distance data obtained is 67.1m, 64.9m, 65.8m, 65.7m, and 65.4m; 75.4m, 76.9m, and 77.3m are obviously interfered data and are eliminated.

[0070] Furthermore, the range of the first dynamic threshold can determine a basic value according to the actual situation of the data. Errors within 1 to 2 meters of the basic value are within the normal range. If the deviation from the basic value is more than 10 meters, it is severely interfered data and needs to be eliminated to improve data accuracy.

[0071] Furthermore, the present application obtains a dynamic threshold by comparing the estimated value obtained by using the least squares estimation model with the actual measurement value. The distance data is filtered by the dynamic threshold to obtain better distance data to participate in the calculation of the tag position, which can eliminate NLOS (Non Line of Sight, generally refers to non-line of sight transmission of wireless signals) interference and make the tag position more accurate.

[0072] Furthermore, in a more complex measurement environment, various obstructions often cause the measurement signal to refract or scatter during ranging, thus affecting the final positioning result. The present application eliminates these unreliable and inaccurate data by establishing a first dynamic threshold, thereby ensuring the accuracy of the final positioning result.

[0073] In some embodiments, the obtaining final angle data between the tag and the base station includes:

[0074] Acquire the measurement signal from the tag to each slave antenna and the main antenna, and calculate and obtain the first phase difference data between each slave antenna and the main antenna;

[0075] Optimizing the first phase difference data to obtain final phase difference data;

[0076] Obtaining first angle data according to the final phase difference data;

[0077] The first angle data is mean filtered to obtain final angle data.

[0078] In this embodiment, the method for measuring the angle uses a measurement method based on UWB. By acquiring the measurement signal sent by the tag to each slave antenna and the main antenna, the phase difference data between each slave antenna to the main antenna is calculated, and the phase difference data is optimized and then the optimized phase difference data is used to obtain the angle data, and finally the angle data is mean filtered.

[0079] For example, a base station includes four slave antennas and one main antenna, the main antenna is recorded as antenna 0, and the four slave antennas are recorded as antenna 1, antenna 2, antenna 3, and antenna 4. The first phase difference data includes the phase difference data between the main antenna and the above four slave antennas, the phase difference y1 between antenna 1 and antenna 0, the phase difference y2 between antenna 2 and antenna 0, the phase difference y3 between antenna 3 and antenna 0, and the phase difference y4 between antenna 4 and antenna 0. Then the final angle data can be calculated using the phase difference data.

[0080] Furthermore, UWB stands for Ultra Wide Band, which is a wireless carrier communication technology that uses nanosecond non-sinusoidal narrow pulses to transmit data, and occupies a wide spectrum range. UWB technology has the advantages of low system complexity, low power spectrum density of transmitted signals, insensitivity to channel fading, low interception capability, and high positioning accuracy. It is especially suitable for high-speed wireless access in dense multipath places such as indoors.

[0081] Furthermore, finally performing mean filtering on the angle data is a means of increasing measurement accuracy by taking the average value after multiple measurements.

[0082] In some embodiments, the optimizing the first phase difference data to obtain final phase difference data includes:

[0083] Divide [-180°~180°] into 360 / n intervals;

[0084] A first threshold th1 and a second threshold th2 are determined according to the first phase difference data, wherein the first threshold th1 and the second threshold th2 are:

[0085] th1=sin(pi / 2+pi / n)

[0086] th2=sin(3*pi / 2+pi / n)

[0087] The final phase difference data is determined according to the first threshold and the second threshold, wherein a sine value of the final phase difference data is between the first threshold and the second threshold.

[0088] In this embodiment, an optimization method for obtaining final phase difference data from first phase difference data is provided. Figure 1 As shown in the figure, the number of antennas is 4. When the tag moves periodically relative to the base station, the collected phase difference data will have a sinusoidal feature. After filtering and normalizing the phase difference data, the following is obtained: Figure 1 There are four sinusoidal curves shown in the figure, where y1, y2, y3, and y4 are the phase difference data between the first to fourth antennas and the main antenna, respectively, wherein the horizontal axis in the image is the mapping value of the angle, and the vertical axis is the sine value of the angle; th1 is the sine value of the angle (pi / 2+pi / n), and th2 is the sine value of the angle (3*pi / 2+pi / n). The phase difference data with a sine value greater than th1 and less than th2 is used to calculate the final phase difference data.

[0089] Furthermore, the reasons for eliminating the phase difference data greater than th1 and less than th2 are as follows. When the sine value corresponding to the phase difference data is greater than th1 or less than th2, the following will occur: Figure 2 The phenomenon shown in Figure n 0 is the main antenna, n 1 From antenna 1, R 0 is the actual location of the label, R 1 The wrong position corresponds to the same angle, that is, one angle corresponds to two symmetrical positions; Figure 1 It can also be seen from the above that within an angle range, when the phase difference data is greater than th1 or less than th2, in the same phase difference data, the sine values ​​corresponding to two different phase difference data will be equal; that is, when the sine value of the phase difference data is greater than th1 or less than th2 and is used to calculate the tag position, an erroneous angle data will appear, which will affect the accuracy of the tag position.

[0090] On the contrary, when the sine value of the phase difference data is between th2 and th1, the sine values ​​corresponding to two different phase difference data in the same phase difference data will not be equal, that is, an erroneous symmetrical position will not appear, thereby improving the accuracy of angle measurement.

[0091] For example, when there are 4 slave antennas, th1 = √2 / 2, th2 = -√2 / 2, then the part of the collected phase difference data that is greater than th2 and less than th1 is mapped to Figure 1 The shadowed part is the phase difference data. It can be clearly seen that outside the shadowed part, when in any 90° interval, there are two different phase difference data corresponding to the same sine value; on the contrary, in the shadowed part, any 90° interval has one phase difference data corresponding to one sine value.

[0092] In some embodiments, obtaining the first angle data according to the final phase difference data includes:

[0093] Performing weighted calculation according to the final phase difference data and a preset weight corresponding to the final phase difference data to obtain the first angle data;

[0094] The closer the target phase difference data is to 0°, the greater the weight of the target phase difference data is, and the target phase difference data is any data in the final phase difference data.

[0095] In this embodiment, when the final phase difference data is used to calculate the first angle data, each phase difference data corresponds to a weight, and the phase difference data closer to 0° has a greater weight.

[0096] Furthermore, since the closer to the zero point, the higher the phase accuracy, setting the weight can reduce the noise interference of the edge value to achieve the purpose of improving the accuracy of the measured angle.

[0097] For example, the final phase difference data includes four phase difference data, namely 48.9°, 50.0°, 50.5°, and 51.2°, and the corresponding weights are 0.9, 0.85, 0.8, and 0.75, respectively. The final phase difference is calculated to be 41.32°, and then the final phase difference is used to calculate the first angle data.

[0098] In some embodiments, after performing mean filtering on the first angle data to obtain final angle data, PI filtering may be performed on the final angle data.

[0099] In this embodiment, the angle data can be further optimized through PI filtering to remove noise and interference signals, making the output signal clearer and more stable.

[0100] In some embodiments, the optimizing the first distance data to obtain the second distance data includes:

[0101] According to a preset distance measurement algorithm, the distance values ​​between the tag and each base station are measured multiple times to obtain multiple distance values;

[0102] calculating a variance of the plurality of distance values;

[0103] obtaining a second dynamic threshold according to the variance of the plurality of distance values ​​and the plurality of distance values;

[0104] Optimizing the first distance data according to the second dynamic threshold to obtain first optimized distance data;

[0105] According to a preset ranging algorithm, multiple measurements are performed to obtain frequency deviation values ​​between the tag and each base station, thereby obtaining multiple frequency deviation values;

[0106] Calculating the variance of the multiple frequency offset values;

[0107] Obtaining a third dynamic threshold according to the variance of the plurality of frequency offset values ​​and the plurality of frequency offset values;

[0108] Optimizing the first optimized distance data according to the third dynamic threshold to obtain second optimized distance data;

[0109] The second optimized distance data is mean filtered to obtain the second distance data.

[0110] In this embodiment, if Figure 4 As shown, a specific method for optimizing the first distance data to obtain the second distance data is provided. The variance of the distance values ​​obtained by multiple DS-TWR measurements is calculated, and the second dynamic threshold is obtained according to the variance data. The second dynamic threshold is an empirical threshold, and the threshold includes distance values ​​with smaller distance value variances, and the distance values ​​with larger distance value variances are eliminated, so as to achieve the purpose of optimizing the distance data.

[0111] For example, multiple measurements result in four distance values ​​of 10m, 22m, 21m, and 18m, respectively. The variance of the distance values ​​is 22.1875m. At this time, the second dynamic threshold range can be set to 22.1875±2m. The distance values ​​actually used are 22m, 21m, and 18m. The distance value of 10m should be eliminated.

[0112] Furthermore, distance values ​​within the ±2m error range of the variance of a set of distance value data are all normal distance measurement values, while distance measurement values ​​exceeding this range are not accurate enough and should be eliminated.

[0113] Furthermore, data with large variance in the distance value may be affected by obstructions in a complex environment, resulting in a large degree of discreteness, and the quality of the measured distance value is poor. Therefore, this part of the distance value data is eliminated through the second dynamic threshold to obtain more reliable and accurate data for calculating the tag position, which can further improve the accuracy of the tag position.

[0114] This embodiment also provides a method for optimizing corresponding distance value data by utilizing the variance of frequency deviation values, calculating the variance of frequency deviation values ​​obtained by multiple DS-TWR measurements, and obtaining a third dynamic threshold based on the frequency deviation values. The third dynamic threshold is an empirical threshold, and the threshold includes corresponding distance value data with smaller frequency deviation value variances, while corresponding distance value data with larger frequency deviation value variances are eliminated, so as to achieve the purpose of optimizing distance data.

[0115] Furthermore, data with larger variance in the frequency deviation value may be affected by obstructions in a complex environment, resulting in a larger degree of deviation, and the quality of the corresponding distance value measured is poor. Therefore, the distance value data corresponding to this part of the frequency deviation value with larger variance is eliminated to obtain more reliable and accurate data for calculating the tag position, which can further improve the accuracy of the tag position.

[0116] Furthermore, after being screened by the second dynamic threshold and the third dynamic threshold, the remaining distance value data are mean filtered to obtain the second distance data.

[0117] In some embodiments, after the first distance data is optimized to obtain the second distance data, the second distance data may be subjected to EKF filtering.

[0118] In this embodiment, more accurate second distance data is obtained through EKF filtering.

[0119] In some embodiments, in the antenna array, with the main antenna as the center, n slave antennas are evenly distributed around the main antenna at 360 / n degrees.

[0120] The distance between each slave antenna and the main antenna is equal and less than or equal to half the wavelength of the measurement signal.

[0121] In this embodiment, an antenna array antenna structure is provided, in which the main antenna is circular, and n slave antennas are evenly and equidistantly distributed around the main antenna at 360 / n degrees, and the distance from the slave antenna to the main antenna is less than or equal to half the wavelength of the measurement signal.

[0122] Furthermore, when the distance from the antenna to the main antenna is less than or equal to half the wavelength of the measurement signal, if the distance exceeds half the wavelength, noise will be generated and affect the measurement result.

[0123] Further, the distance from the antenna to the main antenna may be selected to be 90% of half the wavelength.

[0124] In some embodiments, the number m of base stations is greater than or equal to 3.

[0125] In this embodiment, the minimum number of base stations is limited. When the number of base stations is less than 3, the final data result will be cancelled.

[0126] Furthermore, the reason for limiting the minimum number of base stations is that if the number of base stations is less than 3, the sample size of the positioning data of the tag through each base station is small, and when a large error occurs, comparison cannot be performed, so the minimum number of base stations is limited.

[0127] In summary, through the above method, the influence of unstable angle measurement boundary value can be effectively solved, the angle measurement accuracy can be improved, the static ranging stability and dynamic ranging speed and accuracy can be effectively optimized, the NLOS interference can be effectively eliminated, and the positioning stability and accuracy can be improved.

[0128] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, the embodiments should be considered exemplary and non-restrictive in all respects, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims be included in the present invention.

[0129] In addition, it should be understood that although the present specification is described according to embodiments, not every embodiment contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation methods that those skilled in the art can understand.

Claims

1. An optimized direction finding and ranging positioning method based on UWB, characterized in that: The method is applied to a measuring device, the measuring device comprising at least m base stations and tags, each of the base stations comprising an antenna array consisting of a main antenna and n slave antennas; The method comprises: Acquire final angle data between the tag and the base station; Obtaining first distance data from the tag to each base station by a preset distance measurement algorithm; Optimizing the first distance data to obtain second distance data; Obtaining an estimated value of the tag position according to the final angle data, the preset position of the base station, the second distance data, and a pre-constructed least squares estimation model, wherein the pre-constructed least squares estimation model represents a mapping relationship between the angle between the tag and the base station, the distance between the tag and the base station, the tag position, and the base station position; Obtaining third distance data from the tag to each base station according to the estimated value of the tag position and the base station position; Compare the third distance data with the second distance data to obtain a first dynamic threshold; Obtaining final distance data from the tag to each base station according to the first dynamic threshold and the third distance data, wherein the final distance data is the portion of the third distance data that does not exceed the first dynamic threshold; Obtaining the tag position according to the final angle data, the final distance data, and the base station position; The optimizing the first distance data to obtain the second distance data includes: According to a preset distance measurement algorithm, the distance values ​​between the tag and each base station are measured multiple times to obtain multiple distance values; calculating a variance of the plurality of distance values; obtaining a second dynamic threshold according to the variance of the plurality of distance values ​​and the plurality of distance values; Optimizing the first distance data according to the second dynamic threshold to obtain first optimized distance data; According to a preset ranging algorithm, multiple measurements are performed to obtain frequency deviation values ​​between the tag and each base station, thereby obtaining multiple frequency deviation values; Calculating the variance of the multiple frequency offset values; Obtaining a third dynamic threshold according to the variance of the plurality of frequency offset values ​​and the plurality of frequency offset values; Optimizing the first optimized distance data according to the third dynamic threshold to obtain second optimized distance data; The second optimized distance data is mean filtered to obtain the second distance data.

2. The method for optimizing direction finding and ranging based on UWB as claimed in claim 1, characterized in that: The obtaining of final angle data between the tag and the base station comprises: Acquire the measurement signal from the tag to each slave antenna and the main antenna, and calculate and obtain the first phase difference data between each slave antenna and the main antenna; Optimizing the first phase difference data to obtain final phase difference data; Obtaining first angle data according to the final phase difference data; The first angle data is mean filtered to obtain final angle data.

3. The method for optimizing direction finding and ranging based on UWB as claimed in claim 2, characterized in that: The optimizing the first phase difference data to obtain final phase difference data includes: Divide [-180°~180°] into 360 / n intervals; A first threshold th1 and a second threshold th2 are determined according to the first phase difference data, wherein the first threshold th1 and the second threshold th2 are: th1=sin(pi / 2+pi / n) th2=sin(3*pi / 2+pi / n) The final phase difference data is determined according to the first threshold and the second threshold, wherein a sine value of the final phase difference data is between the first threshold and the second threshold.

4. The method for optimizing direction finding and ranging based on UWB as claimed in claim 2, characterized in that: The obtaining first angle data according to the final phase difference data comprises: Performing weighted calculation according to the final phase difference data and a preset weight corresponding to the final phase difference data to obtain the first angle data; The closer the target phase difference data is to 0°, the greater the weight of the target phase difference data is, and the target phase difference data is any data in the final phase difference data.

5. The method for optimizing direction finding and ranging based on UWB as claimed in claim 4, characterized in that: After performing mean filtering on the first angle data to obtain final angle data, PI filtering may be performed on the final angle data.

6. The method for optimizing direction finding and ranging based on UWB as claimed in claim 1, characterized in that: After the first distance data is optimized to obtain the second distance data, the second distance data may be subjected to EKF filtering.

7. The method for optimizing direction finding and ranging based on UWB as claimed in claim 1, characterized in that: In the antenna array, with the main antenna as the center, n slave antennas are evenly distributed around the main antenna at 360 / n degrees. The distance between each slave antenna and the main antenna is equal and less than or equal to half the wavelength of the measurement signal.

8. The method for optimizing direction finding and ranging based on UWB as claimed in claim 1, characterized in that: The number m of the base stations is greater than or equal to 3.

Images