A positioning method, a positioning device, a positioning platform and a storage medium

Abstract

The application discloses a positioning method, a positioning device, a positioning platform and a storage medium. The method comprises the following steps: collecting a plurality of in-phase quadrature signal vectors through a signal collection unit i of a collection device in a positioning platform; determining a first Rician factor corresponding to an antenna group n in an antenna array based on the plurality of in-phase quadrature signal vectors and a Rician fading model if it is determined that the signal quality of the signal received by the antenna array meets a signal quality condition based on the plurality of in-phase quadrature signal vectors; wherein n is a positive integer greater than or equal to 1 and less than or equal to N, and N is the total number of antenna groups; determining a reference angle value between a Bluetooth tag and the collection device based on the plurality of in-phase quadrature signal vectors; correcting a Kalman filtering equation based on the first Rician factor and the reference angle value to obtain a target angle value between the Bluetooth tag and the collection device, so as to position the Bluetooth tag according to the target angle value.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication, in particular to a positioning method, a positioning device, a positioning platform and a storage medium. BACKGROUND

[0002] In recent years, Bluetooth technology has been used to provide various types of location-based services, which mainly provide solutions including proximity solutions and positioning systems. Among them, the proximity solution includes a Point of Interest (PoL) information solution, such as a solution for providing indoor item information and finding items for users, where the item information is PoL information, and the PoL information includes name, category, longitude and latitude. The positioning system uses Bluetooth technology to determine the physical location of a target to achieve target tracking or help people provide indoor navigation services in complex indoor environments. Currently, in the Bluetooth positioning system, the positioning method is achieved by measuring the Angle of Arrival (AOA).

[0003] In the related art, the positioning method based on Bluetooth AOA angle measurement is to use an antenna array to distinguish multiple path signals; select two signal paths with the strongest energy according to the energy size of the received signals, and obtain the phase information of the two signal paths from the antenna; use an AOA estimation method to calculate the arrival angle of the two signals; use a Phase Difference of Arrival (PDOA) estimation method to calculate the propagation distance of the two signals; according to the position of the total obstacle in the positioning scene, a virtual base station can be established to convert a Non Line Of Sight (NLOS) path into a Line Of Sight (LOS) path; use a weighted least squares (WLS) algorithm to calculate the position coordinates of the object to be positioned; use a residual weighted LS algorithm to obtain more accurate position coordinates.

[0004] However, when this method processes multiple path signals, only the two strongest paths in multiple signal paths are processed, and there is at least a positioning error. SUMMARY

[0005] The present application provides a positioning method, a positioning device, a positioning platform and a storage medium, which solve the problem of at least positioning error in the related art.

[0006] The technical solution of the present application is implemented as follows:

[0007] The present application provides a positioning method, which comprises:

[0008] The signal acquisition unit i of the acquisition device in the positioning platform is used to acquire a plurality of same-phase quadrature signal vectors; wherein the same-phase quadrature signal vector is a signal vector received by an antenna i in an antenna array of the acquisition device corresponding to the signal acquisition unit i, i is a positive integer greater than 1 and less than or equal to I, and I is the total number of the acquisition units;

[0009] If it is determined that the signal quality of the signal received by the antenna array meets a signal quality condition based on the plurality of same-phase quadrature signal vectors, a first Rician factor corresponding to an antenna group n in the antenna array is determined based on the plurality of same-phase quadrature signal vectors and a Rician fading model; wherein n is a positive integer greater than or equal to 1 and less than or equal to N, and N is the total number of the antenna groups;

[0010] A reference angle value between the Bluetooth tag and the acquisition device is determined based on the plurality of same-phase quadrature signal vectors;

[0011] A Kalman filtering equation is corrected based on the first Rician factor and the reference angle value to obtain a target angle value between the Bluetooth tag and the acquisition device, so that the Bluetooth tag is positioned according to the target angle value.

[0012] The application provides a positioning device, which comprises:

[0013] An acquisition module is configured to acquire a plurality of same-phase quadrature signal vectors by using a signal acquisition unit i of an acquisition device in a positioning platform; wherein the same-phase quadrature signal vector is a signal vector received by an antenna i in an antenna array of the acquisition device corresponding to the signal acquisition unit i, i is a positive integer greater than 1 and less than or equal to I, and I is the total number of the acquisition units;

[0014] A determination module is configured to determine a first Rician factor corresponding to an antenna group n in the antenna array based on the plurality of same-phase quadrature signal vectors and a Rician fading model if it is determined that the signal quality of the signal received by the antenna array meets a signal quality condition based on the plurality of same-phase quadrature signal vectors; wherein n is a positive integer greater than or equal to 1 and less than or equal to N, and N is the total number of the antenna groups;

[0015] The determination module is further configured to determine a reference angle value between the Bluetooth tag and the acquisition device based on the plurality of same-phase quadrature signal vectors;

[0016] A processing module is configured to correct a Kalman filtering equation based on the first Rician factor and the reference angle value to obtain a target angle value between the Bluetooth tag and the acquisition device, so that the Bluetooth tag is positioned according to the target angle value.

[0017] The application provides a positioning platform, which comprises:

[0018] a memory for storing executable instructions;

[0019] a processor for executing the executable instructions stored in the memory to implement the positioning method.

[0020] The application provides a computer storage medium storing one or more programs, which can be executed by one or more processors to implement the positioning method.

[0021] The application provides a positioning method, a positioning device, a positioning platform and a storage medium. A signal acquisition unit i of an acquisition device in the positioning platform acquires a plurality of co-phase quadrature signal vectors. The co-phase quadrature signal vector is a signal vector received by an antenna i in an antenna array of the acquisition device corresponding to the signal acquisition unit i, i is a positive integer greater than 1 and less than or equal to I, I is the total number of acquisition units. If the signal quality of the signal received by the antenna array meets the signal quality condition based on the plurality of co-phase quadrature signal vectors, the first Rician factor corresponding to an antenna group n in the antenna array is determined based on the plurality of co-phase quadrature signal vectors and a Rician fading model. N is a positive integer greater than or equal to 1 and less than or equal to N, and N is the total number of antenna groups. The reference angle value between the Bluetooth tag and the acquisition device is determined based on the plurality of co-phase quadrature signal vectors. The Kalman filtering equation is corrected based on the first Rician factor and the reference angle value to obtain the target angle value between the Bluetooth tag and the acquisition device, so as to position the Bluetooth tag according to the target angle value. In this way, the positioning problem in the related art is solved, and the influence of wireless signal fading on positioning accuracy is effectively weakened by correcting the Kalman filtering equation, so that centimeter-level accurate positioning is realized. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 An optional flowchart of a positioning method provided by an embodiment of the application is shown in the figure;

[0023] Figure 2 An optional schematic diagram of the connection between an antenna and a signal acquisition unit provided by an embodiment of the application is shown in the figure;

[0024] Figure 3 An optional flowchart of a positioning method provided by an embodiment of the application is shown in the figure;

[0025] Figure 4 An optional structural schematic diagram between antenna groups provided by an embodiment of the application is shown in the figure;

[0026] Figure 5A flowchart of an optional positioning method provided by the embodiment of the present application is shown in FIG. 1;

[0027] Figure 6 A flowchart of an optional positioning method provided by the embodiment of the present application is shown in FIG. 1;

[0028] Figure 7 A flowchart of an optional positioning method provided by the embodiment of the present application is shown in FIG. 1;

[0029] Figure 8 A flowchart of an optional positioning method provided by the embodiment of the present application is shown in FIG. 1;

[0030] Figure 9 A flowchart of an optional positioning method provided by the embodiment of the present application is shown in FIG. 1;

[0031] Figure 10 A structural diagram of a positioning device provided by the embodiment of the present application is shown in FIG. 1;

[0032] Figure 11 A structural diagram of a positioning platform provided by the embodiment of the present application is shown in FIG. 1. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Here, the "another" or "yet another" mentioned in the description of the drawings does not refer to a specific embodiment, and the embodiments of the present application can be combined without conflict.

[0034] It should be understood that the "embodiment of the present application" or "the foregoing embodiment" mentioned throughout the description means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in the embodiment of the present application" or "in the foregoing embodiment" appearing throughout the description does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in any suitable manner in one or more embodiments. In various embodiments of the present application, the size of the serial number of the above processes does not mean the order of execution, and the execution order of the processes should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The serial number of the above embodiments of the present application is only for description, not representing the advantages and disadvantages of the embodiments.

[0035] Reference is made to Figure 1 , Figure 1 A flowchart of an optional positioning method provided by the embodiment of the present application is shown in FIG. 1, which is applied to a positioning platform, and includes the following steps:

[0036] Step 101, collecting a plurality of in-phase quadrature signal vectors by positioning a signal collection unit i of a collection device in a platform.

[0037] The in-phase quadrature signal vector is a signal vector received by an antenna i in an antenna array of the collection device corresponding to the signal collection unit i; i is a positive integer greater than 1 and less than or equal to I, and I is the total number of collection units.

[0038] In the embodiment, the in-phase quadrature signal vector is a signal sent by the Bluetooth tag to the collection device. The in-phase quadrature signal, that is, the I / Q signal, can be understood as a radio frequency (RF) signal, and the in-phase quadrature signal includes an in-phase (I) signal and a quadrature (Q) signal. The in-phase quadrature signal vector includes an in-phase signal vector and a quadrature signal vector.

[0039] In the embodiment, the signal collection unit can be a Bluetooth chip, and the antenna in the antenna array can be a Bluetooth antenna of a dipole antenna.

[0040] In the embodiment, the circuit board of the collection device includes a plurality of signal collection units and an antenna array, the plurality of antenna arrays include a plurality of antennas, and the receiving end of each antenna is connected to an independent signal collection unit. For example, the signal collection unit can be two, and the number of antennas in the antenna array can also be two. The signal collection unit can be four, and the number of antennas in the antenna array can also be four. In this way, the antenna array synchronous sampling method is adopted, that is, an independent Bluetooth chip is used to realize real-time and synchronous full-data sampling of each antenna, so that the signal collection unit does not need to switch the antenna during the angle positioning such as angle of arrival (AOA) positioning, and the in-phase quadrature signal vector of the signal waveform of the Bluetooth tag is collected in real time, and then the continuous collection of I / Q data is realized.

[0041] It should be noted that in the related art, when AOA positioning is performed, the sampling device selects a certain antenna in the antenna array by controlling the radio frequency switch, realizes high-speed switching of the antenna, and uses a subsequent single Bluetooth chip to perform time-sharing sampling of data. However, when the sampling device performs time-sharing sampling, the unstable data collected during the antenna switching is discarded, and due to the error of the switching time, the angle error of the AOA is caused, and then the accuracy of the positioning is affected.

[0042] Here, the Bluetooth tag sends a CET sinusoidal waveform with a frequency of 250KHz when performing angle positioning, and according to the Nyquist sampling theorem, based on the main frequency of the signal collection unit such as the Bluetooth chip and the computing power of the microcontroller unit (MCU), the sampling frequency is determined as f s= 1MHz; thus, it is ensured that no spectrum aliasing occurs during sampling.

[0043] In an implementable application scenario, since the baud rate of the serial port transmission of the Bluetooth chip is 115200, the sampling frequency is f s = 1MHz, therefore, the full amount of data of the continuous I / Q signal vector collected cannot be transmitted to the CPU. Here, the signal collection unit is the Bluetooth chip, and the Bluetooth chip has four, and the number of antennas in the antenna array is four, which are taken as examples for description. Referring to Figure 2 As shown in the figure, the synchronization signal generated by the micro control unit of the collection device triggers each Bluetooth chip to start synchronously collecting I / Q signal vectors; N = 1024 I / Q data are collected each time to generate an I / Q data frame, and the frame is transmitted to the MCU through the serial port. It should be noted that during the data collection process, the Bluetooth chip collects 1024 data, which takes 1.02ms; each I / Q signal vector is 2 bytes, and each single-antenna data at a time point contains I and Q two-way signal vector data, totaling 4 bytes, therefore, the byte number of 1024 points collected by four antennas is 4 x 4 x 1024 = 16384 bytes; when using the serial port for transmission, the time required is 115200 / 8 / 16384 = 0.8789s. Therefore, for one data collection, the MCU can collect the complete continuous waveform of the four antennas within 1s, meeting the real-time requirement of the positioning system.

[0044] In actual application, the collection device can be a public mobile communication base station, simply referred to as a base station, and the collection device can also be a mobile communication system; the collection device is a radio transceiver station for transmitting information between a mobile telephone terminal and a mobile communication switching center in a certain radio coverage area.

[0045] In the embodiment of the application, the collection device triggers the signal collection unit i in the collection device through the synchronization signal generated by the micro control unit of the collection device, and collects a plurality of cophasal quadrature signal vectors received by the antenna i in the antenna array in the collection device within a set time period, so that the positioning platform acquires the plurality of cophasal quadrature signal vectors.

[0046] In step 102, if it is determined that the signal quality of the signal received by the antenna array meets the signal quality condition based on the plurality of cophasal quadrature signal vectors, a first Rician factor corresponding to an antenna group n in the antenna array is determined based on the plurality of cophasal quadrature signal vectors and the Rician fading model.

[0047] Wherein, n is a positive integer greater than or equal to 1 and less than or equal to N, and N is the total number of antenna groups.

[0048] In the embodiments of the present application, the signals received by the antenna array include direct signals emitted by the Bluetooth tag directly to the gateway, and also include scattered multipath signals caused by factors such as multipath, non-line-of-sight, etc. The signal quality can be understood as the proportion between the direct signal and the scattered multipath signal; the larger the proportion, the better the signal quality; the smaller the proportion, the worse the signal quality.

[0049] In the embodiments of the present application, the signal quality condition can be understood as the proportion between the direct signal and the scattered multipath signal being within the proportion threshold. It should be noted that the signal quality of the signals received by the antenna array meeting the signal quality condition can be determined by the positioning platform based on the plurality of cophasal quadrature signal vectors, and the signal quality of the signals received by the antenna array meeting the signal quality condition can also be determined by the acquisition device and then sent to the positioning platform by the acquisition device. For this, the present application does not make specific limitation.

[0050] In the embodiments of the present application, the first Rice factor characterizes the proportion between the average power of the direct signal and the average power of the scattered multipath signal in the cophasal quadrature signal vector collected in the antenna group n. The larger the first Rice factor, the higher the proportion of the average power of the direct signal, the lower the average power of the scattered multipath signal, and the higher the signal quality of the signals received by the antennas in the antenna group n. It should be noted that the first Rice factor can be determined by the positioning platform based on the plurality of cophasal quadrature signal vectors and the Rice fading model, and the first Rice factor can also be determined by the acquisition device based on the plurality of cophasal quadrature signal vectors and the Rice fading model and then sent to the positioning platform by the acquisition device. For this, the present application does not make specific limitation.

[0051] In the embodiments of the present application, the direct signal, the refracted signal and the scattered signal received by the antenna array are subject to the Rice fading model, i.e. the sinusoidal wave superimposed narrowband Gaussian process. Compared with other fading models, the Rice channel distribution is suitable for wireless channel environment with obvious path, and is very suitable for the description of signal strength distribution and the evaluation of signal quality by the Bluetooth high-precision positioning platform.

[0052] Here, the Rice fading model is:

[0053]

[0054] wherein z is the envelope of the sinusoidal (cosine) signal superimposed narrowband Gaussian random signal, P(z) is the probability density when the signal envelope is z, ρ 2 is the average power of the direct signal, is the average power of the scattered multipath signal, and I0 is the first-order modified Bessel function of the first kind.

[0055] In the embodiment of the present application, after the positioning platform collects multiple cophasal quadrature signal vectors through the signal collection unit i of the collection device, the positioning platform determines that the signal quality of the signal received by the antenna array meets the signal quality condition based on the multiple cophasal quadrature signal vectors, and determines the first Rician factor corresponding to the antenna group n in the antenna array based on the multiple cophasal quadrature signal vectors and the Rician fading model. In this way, the degree of advantage or disadvantage of the signal quality caused by wireless fading in each antenna group is determined, thereby providing a data basis for further improving the positioning accuracy.

[0056] In step 103, the reference angle value between the Bluetooth tag and the collection device is determined based on the multiple cophasal quadrature signal vectors.

[0057] In the embodiment of the present application, the reference angle value is used to position the initial position of the Bluetooth tag. It should be noted that the reference angle value between the Bluetooth tag and the collection device can be calculated by the positioning platform based on the multiple cophasal quadrature signal vectors, or the reference angle value between the Bluetooth tag and the collection device can be calculated by the collection device based on the multiple cophasal quadrature signal vectors. The present application does not make a specific limitation in this regard. It should be noted that in a preferred case, the collection device calculates the reference angle value based on the multiple cophasal quadrature signal vectors, that is, the positioning platform receives the reference angle value between itself and the Bluetooth tag sent by each collection device, and then positions the Bluetooth tag according to the received reference angle value, thereby reducing the calculation amount of the positioning platform.

[0058] In step 104, the Kalman filtering equation is corrected based on the first Rician factor and the reference angle value to obtain the target angle value between the Bluetooth tag and the collection device, so as to position the Bluetooth tag according to the target angle value.

[0059] In the embodiment of the present application, the target angle value is used to position the final position of the Bluetooth tag.

[0060] In the embodiment of the present application, when the positioning platform determines the first Rician factor corresponding to the antenna group n in the antenna array based on the multiple cophasal quadrature signal vectors and the Rician fading model, the positioning platform determines the reference angle value between the Bluetooth tag and the collection device based on the multiple cophasal quadrature signal vectors; then, the positioning platform corrects the Kalman filtering equation based on the first Rician factor and the reference angle value, thereby obtaining the target angle value between the Bluetooth tag and the collection device; further, the positioning platform positions the Bluetooth tag according to the target angle value.

[0061] The application provides a positioning method, through a signal collection unit i of a collection device in a positioning platform, a plurality of co-phase quadrature signal vectors corresponding to the signal collection unit i are collected; wherein, the co-phase quadrature signal vector is a signal vector received by an antenna i in an antenna array of the collection device corresponding to the signal collection unit i, i is a positive integer greater than 1 and less than or equal to I, I is the total number of collection units; if the signal quality of the signal received by the antenna array meets the signal quality condition based on the plurality of co-phase quadrature signal vectors, the first Rician factor corresponding to an antenna group n in the antenna array is determined based on the plurality of co-phase quadrature signal vectors and the Rician fading model; wherein, n is a positive integer greater than or equal to 1 and less than or equal to N, N is the total number of antenna groups; the reference angle value between the Bluetooth tag and the collection device is determined based on the plurality of co-phase quadrature signal vectors; the Kalman filtering equation is corrected based on the first Rician factor and the reference angle value, and the target angle value between the Bluetooth tag and the collection device is obtained, so as to position the Bluetooth tag according to the target angle value; in this way, the positioning problem in the related art is solved, and through the correction of the Kalman filtering equation, the influence of wireless signal fading on the positioning accuracy is effectively weakened, and centimeter-level accurate positioning is realized.

[0062] Reference Figure 3 , Figure 3 is a flowchart of an optional positioning method provided by an embodiment of the application, which is applied to a positioning platform, and the positioning method comprises the following steps:

[0063] Step 301, through a signal collection unit i of a collection device in a positioning platform, a plurality of co-phase quadrature signal vectors are collected.

[0064] Wherein, the co-phase quadrature signal vector is a signal vector received by an antenna i in an antenna array of the collection device corresponding to the signal collection unit i; i is a positive integer greater than 1 and less than or equal to I, I is the total number of collection units.

[0065] In other embodiments of the application, the angle between every two adjacent antenna groups in the N antenna groups of the antenna array is within the angle threshold.

[0066] In the embodiments of the application, the angle within the angle threshold can be understood as ensuring that the phase difference of the signals received by the two connected antenna groups meets the angle threshold range. Exemplarily, the angle threshold can be 90 degrees. In this way, the coverage range of the signal is ensured.

[0067] In other embodiments of the application, the interval between every two adjacent antennas in the antenna group n is within the interval threshold, and the interval between every two adjacent antennas can be determined based on the signal wavelength of the received signal and the number of antennas in the antenna group n, that is, interval = signal wavelength λ / number of antennas.

[0068] In an implementable application scenario, referring to FIG. 1, the signal acquisition unit is a Bluetooth chip, and the Bluetooth chip has four antennas. The antennas in the antenna array are divided into two groups, each group having two dipole antennas, and the two groups are distributed at an angle of 90 degrees. The circuit board adopts a printed circuit board (PCB) to carry the dipole antenna structure. The PCB is 6 layers and is made of FR4 copper clad laminate material with a dielectric constant of 4.1. In the antenna design, the interval between the antennas in each antenna group n is set to λ / 4, where λ is the wavelength of the received signal, which is 0.123 meters (m). Thus, for a horizontally forward propagating sinusoidal wave, the phase difference of the signals received between the antennas in the antenna group n does not exceed 90 degrees, that is, a phase difference of 90 degrees is generated between the two antennas in the same group. Figure 4

[0069] Step 302, if it is determined that the signal quality of the signal received by the antenna array meets the signal quality condition based on the plurality of in-phase quadrature signal vectors, a first Rician factor corresponding to the antenna group n in the antenna array is determined based on the plurality of in-phase quadrature signal vectors and the Rician fading model.

[0070] wherein n is a positive integer greater than or equal to 1 and less than or equal to N, and N is the total number of antenna groups.

[0071] In the embodiments of the present application, referring to FIG. 1, the determination in step 302 that the signal quality of the signal received by the antenna array meets the signal quality condition based on the plurality of in-phase quadrature signal vectors can be implemented by the following steps: Figure 5

[0072] Step A1, calculating the signal envelope vector of each in-phase quadrature signal vector.

[0073] In the embodiments of the present application, the in-phase quadrature signal vector includes an in-phase signal vector and a quadrature signal vector; the square of the signal envelope vector z is equal to the sum of the square of the in-phase signal vector I and the square of the quadrature signal vector Q, that is, z 2 = I 2 + Q 2 ; further, the signal envelope vector z can be expressed as

[0074] In the embodiments of the present application, the positioning platform calculates the signal envelope vector of each in-phase quadrature signal vector, that is, for the plurality of continuously acquired in-phase quadrature signal vectors IQ1, IQ1 = {(I1, Q1), (I2, Q2), …, (In, Qn)}, the calculation is performed to obtain a plurality of signal envelope vectors Z1, Z1 = {z1, z2, …, zn}. m m ​​​​m , …}, m is a positive integer greater than or equal to 1 and less than or equal to M, M is the total number of the in-phase quadrature signal vectors, and M is a positive integer greater than 1.

[0075] Step A2, determining a first maximum signal envelope vector and a first minimum signal envelope vector from the plurality of signal envelope vectors.

[0076] In the embodiments of the present application, the positioning platform determines a first maximum signal envelope vector z max and a first minimum signal envelope vector z min from the plurality of signal envelope vectors Z1.

[0077] Step A3, determining a first probability distribution set of the signal envelope vectors based on the first maximum signal envelope vector, the first minimum signal envelope vector, and the first signal vector segment count set.

[0078] The first probability distribution set includes the first signal envelope vectors and the first probability values corresponding to the first signal envelope vectors.

[0079] In the embodiments of the present application, the first signal envelope vectors and the first probability values in the first probability distribution set are used to calculate the average power of the direct signal and the average power of the scattered multipath signal in the antenna array.

[0080] In the embodiments of the present application, the positioning platform divides the interval between the first maximum signal envelope vector z max and the first minimum signal envelope vector z min into H parts, and the interval of each part is p, that is, p = (z max -z min ) / H; and establishes a signal vector segment count set R1 = {count r (r = 1, 2, …, H)}. Further, the positioning platform polls the data z m in the plurality of signal envelope vectors Z1 in sequence, and when r×p≤z m ≤(r+1)×p, count r is increased by 1, so as to calculate the first signal vector segment count set R1 when the data in the plurality of signal envelope vectors Z1 are classified according to the interval p; further, the positioning platform calculates the first probability distribution set P1(z) = {P r =count r / n, zr=(r×p+(r+1)×p) / 2, (r = 1, 2, …, H)} of the signal envelope vectors Z1 based on the first signal vector segment count set R1; wherein z r is the mean value of r×p and (r+1)×p.

[0081] Step A4: Input multiple first signal envelope vectors and multiple first probability values ​​into the acquired Rice fading model to obtain the first average power of the direct signal and the second average power of the scattered multipath signal.

[0082] In this embodiment of the application, the positioning platform will use multiple first signal envelope vectors P r and multiple first probability values ​​z r Input to the obtained Rice fading model In this context, ρ and σ0 are unknowns. Furthermore, a nonlinear fitting algorithm is used to obtain the first average power ρ of the direct signal and the second average power σ0 of the scattered multipath signal in the antenna array.

[0083] Step A5: Determine the second Rice factor corresponding to the antenna array based on the first average power and the second average power.

[0084] In this embodiment, the second Rice factor characterizes the ratio between the average power of the direct signal and the average power of the scattered multipath signal in the acquired in-phase orthogonal signal vectors throughout the entire antenna array. The larger the second Rice factor, the higher the proportion of the average power of the direct signal and the lower the average power of the scattered multipath signal, resulting in better overall signal quality received by the entire antenna array.

[0085] In this embodiment of the application, after the positioning platform obtains the first average power ρ of the direct signal and the second average power σ0 of the scattered multipath signal in the antenna array, it determines the ratio of the square of the first average power ρ to the square of the second average power σ0 as the second Rice factor.

[0086] Step A6: If the second Rice factor is within the Rice factor threshold range, determine that the signal quality of the signal received by the antenna array meets the signal quality condition.

[0087] In this embodiment of the application, if the second Rice factor is within the Rice factor threshold range, it is determined that the signal quality of the signal received by the antenna array meets the signal quality conditions. Thus, the second Rice factor is used to characterize the occupancy of refracted multipath signals in the I / Q acquisition data of each antenna in the antenna array. The larger the second Rice factor, the higher the average power ratio of the direct signal in the antenna array, the lower the average power of the scattered multipath signal, and the better the overall signal quality of the signal received by the entire antenna array.

[0088] In the embodiments of this application, reference is made to Figure 6 As shown, the determination of the first Rice factor corresponding to antenna group n in the antenna array based on multiple in-phase orthogonal signal vectors and the Ricean fading model in step 302 can be achieved through the following steps:

[0089] Step B1, obtaining a partial signal envelope vector corresponding to each partial in-phase / quadrature signal vector received by each antenna in the antenna group n.

[0090] In the embodiment of the present application, the positioning platform obtains a partial signal envelope vector Z2 corresponding to each partial in-phase / quadrature signal vector I / O received by each antenna in the antenna group n, Z2={z1, z2, …, zn}, where n is an integer greater than or equal to 1 and less than or equal to U, and U is the total number of in-phase / quadrature signal vectors received by the antenna group n, and U is an integer greater than or equal to 1 and less than M. m , …}, m is an integer greater than or equal to 1 and less than or equal to U, and U is the total number of in-phase / quadrature signal vectors received by the antenna group n, and U is an integer greater than or equal to 1 and less than M.

[0091] Step B2, determining a second maximum signal envelope vector and a second minimum signal envelope vector from the partial signal envelope vectors.

[0092] In the embodiment of the present application, the acquisition device determines a second maximum signal envelope vector z nmax and a second minimum signal envelope vector z nmin from the plurality of partial signal envelope vectors Z2.

[0093] Step B3, determining a second probability distribution set of the partial signal envelope vectors based on the second maximum signal envelope vector, the second minimum signal envelope vector, and the second signal vector segmentation count set.

[0094] The second probability distribution set includes a second signal envelope vector and a second probability value corresponding to the second signal envelope vector.

[0095] In the embodiment of the present application, the second signal envelope vector and the second probability value in the second probability distribution set are used to calculate the average power of the direct signal and the average power of the scattered multipath signal in the antenna group n.

[0096] In the embodiment of the present application, the positioning platform divides the interval between the second maximum signal envelope vector z nmax and the second minimum signal envelope vector z nmin into H parts, and the interval of each part is p, where p=(z max -z min ) / H; and a signal vector segmentation count set R2={count nr (r=1, 2, …, H)} is established. Further, the positioning platform sequentially polls the data z m in the plurality of partial signal envelope vectors Z2, and when r×p≤z m ≤(r+1)×p, count nrAdd 1, so as to calculate the first signal vector segmentation count set R2 when the data in the plurality of partial signal envelope vectors Z2 is classified according to the interval p; further, the positioning platform calculates the second probability distribution set P2(z) of the partial signal envelope vector Z2 based on the first signal vector segmentation count set R2. nr = count nr / n, z nr = (r x p + (r + 1) x p) / 2, (r = 1, 2,..., H)}; wherein, z nr is the mean of r x p and (r + 1) x p.

[0097] Step B4, input the plurality of second signal envelope vectors and the plurality of second probability values into the Rice fading model to obtain the third average power of the direct signal and the fourth average power of the scattered multipath signal.

[0098] In the embodiment of the application, the positioning platform inputs the plurality of first signal envelope vectors P nr and the plurality of first probability values z nr into the obtained Rice fading model , wherein, ρ, σ0 are unknown quantities. Further, a nonlinear fitting algorithm is used to obtain the third average power ρ n of the direct signal and the fourth average power σ n0 of the scattered multipath signal in the antenna group n.

[0099] Step B5, determine the first Rice factor corresponding to the antenna group n based on the third average power and the fourth average power.

[0100] In the embodiment of the application, after the positioning platform obtains the third average power ρ n of the direct signal and the fourth average power σ n0 of the scattered multipath signal in the antenna group n, the ratio of the square of the third average power ρ n to the square of the fourth average power σ no is determined as the first Rice factor k n . In this way, the first Rice factor is used to depict the occupation of the refracted multipath signal in the I / Q acquisition data of each antenna in the antenna group n. The larger the first Rice factor is, the higher the average power proportion of the direct signal in the antenna group n is, and the lower the average power of the scattered multipath signal is, and the better the signal quality of the signal received by the entire antenna group n is.

[0101] Step 303, determine the reference angle value between the Bluetooth tag and the acquisition device based on the plurality of in-phase quadrature signal vectors.

[0102] In the embodiment of the application, the reference Figure 7As shown, step 303 determines the reference angle value between the Bluetooth tag and the collection device based on the plurality of in-phase quadrature signal vectors, which can be achieved by the following steps:

[0103] Step C1, based on the partial in-phase quadrature signal vector received by each antenna in the antenna group n, determine the phase difference corresponding to each timestamp in the antenna group n.

[0104] In the embodiment of the application, the in-phase quadrature signal vector collected by the signal collection unit is IQ = {(I n，j，t , Q n，j，t )}, wherein n represents the number of antenna groups, j represents the antenna number in the antenna group n, and t represents the timestamp within the time period. j is a positive integer greater than or equal to 1 and less than or equal to J, J is the total number of antennas in the antenna group n; t is a positive integer greater than or equal to 1 and less than or equal to T, T is the total number of timestamps within the time period, such as T is 1024.

[0105] In the embodiment of the application, the positioning platform obtains the first partial in-phase quadrature signal vector corresponding to the same timestamp, i.e. the same subscript t, in the partial in-phase quadrature signal vector received by each antenna in the antenna group n; and performs phase calculation on the first partial in-phase quadrature signal vector corresponding to the same timestamp t, so as to obtain the accurate phase difference.

[0106] Here, the phase difference calculation process is described by taking an antenna array including two antenna groups and each antenna group including two antennas as an example. According to the antenna group n, the phase difference within the antenna group n is calculated, and the calculation formula is wherein arctan2 is the inverse tangent function. The phase difference corresponding to each timestamp in the antenna group n is calculated.

[0107] Step C2, based on the mean value of the phase differences corresponding to the plurality of timestamps in the antenna group n, determine the first angle value between the Bluetooth tag and the antenna group n in the collection device.

[0108] In the embodiment of the application, the positioning platform obtains the phase difference corresponding to each timestamp in the antenna group n The mean value of the plurality of phase differences is obtained, and the phase difference between the Bluetooth tag and the antenna group n in the collection device is obtained wherein Further, the inverse sine tangent function is used, and the first angle value θ n between the Bluetooth tag and the antenna group n in the collection device is calculated; wherein n is a positive integer greater than or equal to 1 and less than or equal to N, N is the total number of antenna groups, and d is the antenna spacing.

[0109] Step C3, determining a reference angle value between the Bluetooth tag and the collection device based on the first angle value corresponding to the antenna group n and the first Rake factor.

[0110] In the embodiments of the present application, the positioning platform calculates the first angle value θ corresponding to the antenna group n n and the first Rake factor k n , calculates the sum of the plurality of products as a first parameter, calculates the sum of the plurality of first Rake factors k n , and determines the ratio of the first parameter and the second parameter as the reference angle value between the Bluetooth tag and the collection device, that is, the reference angle value after fusing the antenna array data is obtained by the method of weighted average. Here, the formula of weighted average is In this way, the Rake factor of the antenna group n is used to realize the fusion calculation of the angle of arrival of the antenna group, fully considers the factors of direct signals and scattered signals caused by multipath, and improves the positioning accuracy.

[0111] In other embodiments of the present application, the collection device can be P, and the collection device p can calculate the reference angle value between the collection device p and the Bluetooth tag wherein, wherein, p is a positive integer greater than or equal to 1 and less than or equal to P, and P is the total number of collection devices.

[0112] Step 304, determining the product of the N first Rake factors as the angle calculation confidence factor of the collection device.

[0113] In the embodiments of the present application, the angle calculation confidence factor is used to represent the confidence of the calculated angle value between the collection device and the Bluetooth tag. The angle calculation confidence factor Here, the angle calculation confidence factor p A is greater, which means that the scattering of the multipath signal of the angle calculation is smaller, the overall I / Q signal quality is higher, and the confidence of the calculated angle value of the collection device is higher.

[0114] In other embodiments of the present application, the collection device can be P, and the collection device p can calculate the first angle calculation confidence factor p Ap of the collection device p, and the product of the first angle calculation confidence factors p Ap of the P collection devices, that is, is taken as the angle calculation confidence factor p B of this position settlement.

[0115] Step 305, determining the distance confidence factor of the collection device based on the first position where the collection device is located, the second position where the Bluetooth tag is located, and the target signal strength indication vector sent by the collected Bluetooth tag.

[0116] In this embodiment of the application, the angle calculation confidence factor is used to characterize the confidence of the calculated distance value between the acquisition device and the Bluetooth tag.

[0117] In this embodiment, the target signal strength indication vector is used to determine the distance between the Bluetooth tag transmitting the signal and the acquisition device receiving the signal by measuring the strength of the received signal, and then to perform positioning calculations based on the corresponding data. Here, the target signal strength indication vector can be the Received Signal Strength Indication (RSSI).

[0118] In this embodiment, the positioning platform obtains the first location of the acquisition device, obtains a set of equations pre-established by the positioning platform, and uses the least squares method to calculate the second location of the Bluetooth tag; and obtains the target signal strength indication vector sent by the acquired Bluetooth tag.

[0119] In the embodiments of this application, reference is made to Figure 8 As shown, step 305, based on the first location of the acquisition device, the second location of the acquired Bluetooth tag, and the target signal strength indication vector transmitted by the acquired Bluetooth tag, determines the distance confidence factor of the acquisition device, which can be achieved through the following steps:

[0120] Step D1: Based on the first position and the second position, determine the first distance vector between the Bluetooth tag and the acquisition device.

[0121] In this embodiment, the positioning platform determines the first distance vector d between the Bluetooth tag and the data acquisition device based on the distance formula, the first position, and the second position. Here, the distance formula can be the Euclidean distance formula, the Mahalanobis distance formula, or the Manhattan distance formula. This application does not impose specific limitations on this.

[0122] Step D2: Obtain the attenuation coefficient and the reference signal strength indication vector.

[0123] In this embodiment, the reference signal strength indication vector can be the signal strength vector of the Bluetooth tag when the acquisition device and the Bluetooth tag are at a preset distance, such as 1 meter. Here, both the attenuation coefficient and the reference signal strength indication vector can be obtained through experimental testing.

[0124] Step D3: Input the target signal strength indication vector, attenuation coefficient, and reference signal strength indication vector into the wireless signal attenuation model to obtain the second distance vector between the Bluetooth tag and the acquisition device output by the wireless signal attenuation model.

[0125] In this embodiment of the application, the wireless signal attenuation model is as follows:

[0126]

[0127] wherein, is a second distance vector between the Bluetooth tag and the collection device output by the wireless signal attenuation model, RSSI is a target signal strength indication vector, RSSI1 is a reference signal strength indication vector, and a is an attenuation coefficient.

[0128] Step D4, determining a distance credibility factor based on a difference between the first distance vector and the second distance vector.

[0129] In the embodiments of the present application, the positioning platform obtains the difference between the first distance vector and the second distance vector, determines the maximum value among the first distance vector, the second distance vector and the difference as a third parameter, further, the positioning platform calculates the ratio of the difference and the third parameter as a fourth parameter. Finally, the difference between 1 and the fourth parameter is determined as the distance credibility factor. In this way, for the collection device, the distance error is calculated by two distance calculation methods, which reflects the deviation degree of the collection data from the free space attenuation model when the influence of interference and fading is observed from the signal strength.

[0130] In other embodiments of the present application, the collection device can be P, based on the first distance vector d p between the Bluetooth tag and the collection device p, the first distance vector set D between the Bluetooth tag and the collection device is determined, that is, D={d p (p=1, 2, …, P)}. Based on the second distance vector d between the Bluetooth tag and the collection device p, the first distance vector set D between the Bluetooth tag and the collection device is determined, that is, D={d The distance credibility factor between the collection devices is determined by the following formula.

[0131]

[0132] wherein, max is the maximum value function, and the denominator takes max for normalization processing. The greater the D , the smaller the deviation degree of the collection data from the free space attenuation model, and the higher the credibility of the position solution.

[0133] As can be seen from the above, by calculating the distance between the Bluetooth tag and the collection device, and then according to the RSSI of the Bluetooth tag collected by the collection device, the distance between the Bluetooth tag and the collection device is calculated by using the wireless signal attenuation model, so that the positioning accuracy is improved.

[0134] Step 306, based on the angle credibility factor, the distance credibility factor and the reference angle value, the Kalman filtering equation is corrected to obtain a target angle value, so as to position the Bluetooth tag according to the target angle value.

[0135] In the embodiments of the present application, referring to Figure 9 The step 306 corrects the Kalman filtering equation based on the angle calculation confidence factor, the distance confidence factor and the reference angle value to obtain a target angle value, so as to position the Bluetooth tag according to the target angle value. The positioning can be realized through the following steps:

[0136] Step E1: determining the product of the angle calculation confidence factor and the distance confidence factor as a target confidence factor.

[0137] Step E2: inputting the reference angle value into the established Kalman filtering time update equation to obtain a predicted angle value output by the Kalman filtering time update equation.

[0138] In the embodiments of the present application, the established Kalman filtering time update equation is:

[0139] x t|t-1 =F t ×x t-1 +B t ×u t-1 ,P t|t-1 =F t ×P t-1 ×F t T +Q t

[0140] wherein x t|t-1 is a prediction result according to the prediction at the time t-1, x t-1 is an optimal prediction result at the time t-1, F is a state transition matrix, F T is a transpose matrix of F, B and u are parameters introduced by a system parameter model; P t|t-1 is a covariance matrix of the prediction result according to the prediction at the time t-1, P t-1 is a covariance matrix at the time t-1, and Q is a covariance matrix caused by system process disturbance.

[0141] In the embodiments of the present application, the positioning platform inputs the reference angle value into the established Kalman filtering time update equation to obtain a predicted angle value x t|t-1 output by the Kalman filtering time update equation and a state transition matrix P t|t-1 corresponding to the predicted angle value, so as to perform iterative operation at the next time based on the predicted angle value x t|t-1 and the state transition matrix P t|t-1 corresponding to the predicted angle value.

[0142] Step E3: correcting the established Kalman filtering state update equation based on the target confidence factor.

[0143] The Kalman filtering equation includes a Kalman filtering time update equation and a Kalman filtering state update equation.

[0144] In the embodiment of the application, the established Kalman filtering state update equation is:

[0145] x t =x t|t-1 +K t ×(w t -H t ×x t|t-1 ),P t =(I-K t ×H t )×P t|t-1

[0146] K t is a Kalman gain, K t =ρ Wt ×P t|t-1 ×H t T / (H t ×P t|t-1 ×H t T +R t ), ρ wt is a target confidence factor, w t is a measurement value, that is, a position calculation result at time t, H is a conversion matrix, H T is a transpose matrix of H, and R is a measurement value covariance matrix. I is an identity matrix.

[0147] In the above calculation process, the positioning platform adds the target confidence factor ρ Wt as a product item to the calculation of the Kalman gain Kt. Based on the corrected K t , the established Kalman filtering state update equation is corrected.

[0148] Step E4: inputting the predicted angle value into the corrected Kalman filtering state update equation to obtain a target angle value output by the corrected Kalman filtering state update equation.

[0149] In the embodiment of the application, the positioning platform inputs the predicted angle value x t|t-1 and the state transition matrix P t|t-1 corresponding to the predicted angle value into the corrected Kalman filtering state update equation to obtain a target angle value x t output by the corrected Kalman filtering state update equation and a target state transition matrix P t .

[0150] It should be noted that in the embodiments of the present application, the positioning platform can obtain the target angle value after one correction of the Kalman filter state update equation, that is, after one iteration operation. Alternatively, the positioning platform can obtain the target angle value after multiple corrections of the Kalman filter state update equation, that is, after multiple iteration operations. The present application does not make a specific limitation in this regard.

[0151] It should be noted that the same steps and the same content in the present embodiment and other embodiments are described with reference to the description in other embodiments, and will not be described here.

[0152] Based on the foregoing embodiments, the present application provides a positioning device, which can be used to implement Figure 1 、 Figure 3 、 Figures 5 to 9 Corresponding to a positioning method, referring to Figure 10 The positioning device 10 comprises:

[0153] The acquisition module 1001 is configured to acquire a plurality of co-phase quadrature signal vectors through a signal acquisition unit i of a collection device in the positioning platform; wherein the co-phase quadrature signal vector is a signal vector received by an antenna i in an antenna array of the collection device corresponding to the signal acquisition unit i, i is a positive integer greater than 1 and less than or equal to I, and I is the total number of acquisition units;

[0154] The determination module 1002 is configured to determine a first Rician factor corresponding to an antenna group n in the antenna array based on the plurality of co-phase quadrature signal vectors and a Rician fading model, if the signal quality of the signal received by the antenna array meets a signal quality condition based on the plurality of co-phase quadrature signal vectors; wherein n is a positive integer greater than or equal to 1 and less than or equal to N, and N is the total number of antenna groups;

[0155] The determination module 1002 is further configured to determine a reference angle value between the Bluetooth tag and the collection device based on the plurality of co-phase quadrature signal vectors;

[0156] The processing module 1003 is configured to correct the Kalman filter equation based on the first Rician factor and the reference angle value, to obtain a target angle value between the Bluetooth tag and the collection device, and to position the Bluetooth tag according to the target angle value.

[0157] In other embodiments of the present application, the included N antenna groups of the antenna array have an included angle between each adjacent two antenna groups within an included angle threshold.

[0158] In other embodiments of the present application, the included N antenna groups of the antenna array have an included angle between each adjacent two antenna groups within an included angle threshold.

[0159] In other embodiments of the present application, the processing module 1003 is further configured to calculate a signal envelope vector of each co-phase quadrature signal vector; the determining module 1002 is further configured to determine a first maximum signal envelope vector and a first minimum signal envelope vector from the plurality of signal envelope vectors; determine a first probability distribution set of the signal envelope vector based on the first maximum signal envelope vector, the first minimum signal envelope vector and the first signal vector segment count set; wherein the first probability distribution set includes a first signal envelope vector and a first probability value corresponding to the first signal envelope vector; the processing module 1003 is further configured to input the plurality of first signal envelope vectors and the plurality of first probability values into the obtained Ricean fading model to obtain a first average power of the direct signal and a second average power of the scattered multipath signal; the determining module 1002 is further configured to determine a second Ricean factor corresponding to the antenna array based on the first average power and the second average power; and if the second Ricean factor is within a Ricean factor threshold, determine that the signal quality of the signal received by the antenna array satisfies the signal quality condition.

[0160] In other embodiments of the present application, the positioning device 10 further comprises an acquisition module, the acquisition module is configured to acquire a partial signal envelope vector corresponding to a partial co-phase quadrature signal vector received by each antenna in the antenna group n; the determining module 1002 is further configured to determine a second maximum signal envelope vector and a second minimum signal envelope vector from the partial signal envelope vectors; determine a second probability distribution set of the partial signal envelope vector based on the second maximum signal envelope vector, the second minimum signal envelope vector and the second signal vector segment count set; wherein the second probability distribution set includes a second signal envelope vector and a second probability value corresponding to the second signal envelope vector; the processing module 1003 is further configured to input the plurality of second signal envelope vectors and the plurality of second probability values into the Ricean fading model to obtain a third average power of the direct signal and a fourth average power of the scattered multipath signal; and the determining module 1002 is further configured to determine a first Ricean factor corresponding to the antenna group n based on the third average power and the fourth average power.

[0161] In other embodiments of the present application, the determining module 1002 is further configured to determine a phase difference of a first partial co-phase quadrature signal vector corresponding to each timestamp in the antenna group n based on the partial co-phase quadrature signal vector received by each antenna in the antenna group n; determine a first angle value between the Bluetooth tag and the antenna group n in the collection device based on the mean value of the phase differences corresponding to the plurality of timestamps in the antenna group n; and determine a reference angle value between the Bluetooth tag and the collection device based on the first angle value corresponding to the antenna group n and the first Ricean factor.

[0162] In other embodiments of this application, the determining module 1002 is further configured to determine the product of N first Rice factors to calculate the confidence factor for the angle of the acquisition device; and to determine the distance confidence factor of the acquisition device based on the first location of the acquisition device, the second location of the Bluetooth tag, and the target signal strength indication vector sent by the acquired Bluetooth tag. The processing module 1003 is further configured to modify the Kalman filter equation based on the angle confidence factor, the distance confidence factor, and the reference angle value to obtain the target angle value.

[0163] In other embodiments of this application, the determining module 1002 is further configured to determine a first distance vector between the Bluetooth tag and the acquisition device based on the first position and the second position; the acquiring module is further configured to acquire the attenuation coefficient and the reference signal strength indication vector; the processing module 1003 is further configured to input the target signal strength indication vector, the attenuation coefficient, and the reference signal strength indication vector into the wireless signal attenuation model to obtain the second distance vector between the Bluetooth tag and the acquisition device output by the wireless signal attenuation model; the determining module 1002 is further configured to determine a distance confidence factor based on the difference between the first distance vector and the second distance vector.

[0164] In other embodiments of this application, the determining module 1002 is further configured to determine the product of the angle calculation confidence factor and the distance confidence factor as the target confidence factor; the processing module 1003 is further configured to input the reference angle value into the established Kalman filter time update equation to obtain the predicted angle value output by the Kalman filter time update equation; based on the target confidence factor, the established Kalman filter state update equation is modified, wherein the Kalman filter equation includes the Kalman filter time update equation and the Kalman filter state update equation; the predicted angle value is input into the modified Kalman filter state update equation to obtain the target angle value output by the modified Kalman filter state update equation.

[0165] Based on the foregoing embodiments, this application provides a data acquisition device that can be used for implementation. Figure 1 , Figure 3 , Figures 5 to 9 One corresponding positioning method is provided, see reference. Figure 11 As shown, the positioning platform 11 ( Figure 11 The positioning platform 11 in the middle corresponds to Figure 10 The positioning device 10 in the system includes a memory 1101 and a processor 1102, wherein the processor 1102 is used to execute the positioning program stored in the memory 1101, and the positioning platform 11 uses the processor 1102 to implement the following steps:

[0166] The signal acquisition unit i of the acquisition device in the positioning platform is used to acquire a plurality of in-phase quadrature signal vectors; wherein, the in-phase quadrature signal vector is a signal vector received by the antenna i in the antenna array of the acquisition device corresponding to the signal acquisition unit i, i is a positive integer greater than 1 and less than or equal to I, I is the total number of acquisition units;

[0167] If it is determined that the signal quality of the signal received by the antenna array meets the signal quality condition based on the plurality of in-phase quadrature signal vectors, the first Rician factor corresponding to the antenna group n in the antenna array is determined based on the plurality of in-phase quadrature signal vectors and the Rician fading model; wherein, n is a positive integer greater than or equal to 1 and less than or equal to N, N is the total number of antenna groups;

[0168] The reference angle value between the Bluetooth tag and the acquisition device is determined based on the plurality of in-phase quadrature signal vectors;

[0169] The target angle value between the Bluetooth tag and the acquisition device is obtained by correcting the Kalman filtering equation based on the first Rician factor and the reference angle value, so as to position the Bluetooth tag according to the target angle value.

[0170] In other embodiments of the present application, the included N antenna groups of the antenna array have an included angle between each adjacent two antenna groups within an included angle threshold.

[0171] In other embodiments of the present application, the included N antenna groups of the antenna array have an included angle between each adjacent two antenna groups within an included angle threshold.

[0172] In other embodiments of the present application, the processor 1102 is configured to execute the positioning program stored in the memory 1101 to implement the following steps:

[0173] The signal envelope vector of each in-phase quadrature signal vector is calculated; the first maximum signal envelope vector and the first minimum signal envelope vector are determined from the plurality of signal envelope vectors; the first probability distribution set of the signal envelope vector is determined based on the first maximum signal envelope vector, the first minimum signal envelope vector and the first signal vector segment count set; wherein, the first probability distribution set includes the first signal envelope vector and the first probability value corresponding to the first signal envelope vector; the plurality of first signal envelope vectors and the plurality of first probability values are input into the obtained Rician fading model to obtain the first average power of the direct signal and the second average power of the scattered multipath signal; the second Rician factor corresponding to the antenna array is determined based on the first average power and the second average power; if the second Rician factor is within the Rician factor threshold, it is determined that the signal quality of the signal received by the antenna array meets the signal quality condition.

[0174] In other embodiments of the present application, the processor 1102 is configured to execute the positioning program stored in the memory 1101 to implement the following steps:

[0175] obtaining a partial signal envelope vector corresponding to each partial in-phase quadrature signal vector received by each antenna in the antenna group n; determining a second maximum signal envelope vector and a second minimum signal envelope vector from the partial signal envelope vectors; determining a second probability distribution set of the partial signal envelope vectors based on the second maximum signal envelope vector, the second minimum signal envelope vector and the second signal vector segment count set; wherein the second probability distribution set comprises a second signal envelope vector and a second probability value corresponding to the second signal envelope vector; inputting the plurality of second signal envelope vectors and the plurality of second probability values into a Rice fading model to obtain a third average power of a direct signal and a fourth average power of a scattered multipath signal; and determining a first Rice factor corresponding to the antenna group n based on the third average power and the fourth average power.

[0176] In other embodiments of the present application, the processor 1102 is configured to execute the positioning program stored in the memory 1101 to implement the following steps:

[0177] determining a phase difference of a first partial in-phase quadrature signal vector corresponding to each timestamp in the antenna group n based on the partial in-phase quadrature signal vector received by each antenna in the antenna group n; determining a first angle value between the Bluetooth tag and the antenna group n in the collection device based on the mean value of the phase differences corresponding to the plurality of timestamps in the antenna group n; and determining a reference angle value between the Bluetooth tag and the collection device based on the first angle value corresponding to the antenna group n and the first Rice factor.

[0178] In other embodiments of the present application, the processor 1102 is configured to execute the positioning program stored in the memory 1101 to implement the following steps:

[0179] determining a product of the N first Rice factors as an angle solution confidence factor of the collection device; determining a distance confidence factor of the collection device based on the obtained first position of the collection device, the obtained second position of the Bluetooth tag, and the collected target signal strength indication vector sent by the Bluetooth tag; and correcting a Kalman filtering equation based on the angle solution confidence factor, the distance confidence factor and the reference angle value to obtain a target angle value.

[0180] In other embodiments of the present application, the processor 1102 is configured to execute the positioning program stored in the memory 1101 to implement the following steps:

[0181] Based on the first position and the second position, a first distance vector between the Bluetooth tag and the collection device is determined; an attenuation coefficient and a reference signal strength indication vector are obtained; the target signal strength indication vector, the attenuation coefficient and the reference signal strength indication vector are input into a wireless signal attenuation model to obtain a second distance vector between the Bluetooth tag and the collection device output by the wireless signal attenuation model; and based on a difference value of the first distance vector and the second distance vector, a distance confidence factor is determined.

[0182] In other embodiments of the present application, the processor 1102 is configured to execute a positioning program stored in the memory 1101 to implement the following steps:

[0183] The product of the angle solution confidence factor and the distance confidence factor is determined as a target confidence factor; the reference angle value is input into the established Kalman filter time update equation to obtain a predicted angle value output by the Kalman filter time update equation; the established Kalman filter state update equation is corrected based on the target confidence factor, wherein the Kalman filter equation includes the Kalman filter time update equation and the Kalman filter state update equation; and the predicted angle value is input into the corrected Kalman filter state update equation to obtain a target angle value output by the corrected Kalman filter state update equation.

[0184] The present application provides a computer readable storage medium, which stores one or more programs executable by one or more processors to implement the above method. Figure 1 、 Figure 3 、 Figures 5 to 9 A corresponding positioning method is provided.

[0185] The application provides a storage medium, through a signal acquisition unit i of an acquisition device in a positioning platform, a plurality of in-phase quadrature signal vectors are acquired; wherein the in-phase quadrature signal vector is a signal vector received by an antenna i in an antenna array of the acquisition device corresponding to the signal acquisition unit i, i is a positive integer greater than 1 and less than or equal to I, I is the total number of acquisition units; if the signal quality of the signal received by the antenna array meets the signal quality condition based on the plurality of in-phase quadrature signal vectors, the first Rician factor corresponding to an antenna group n in the antenna array is determined based on the plurality of in-phase quadrature signal vectors and a Rician fading model; wherein n is a positive integer greater than or equal to 1 and less than or equal to N, N is the total number of antenna groups; the reference angle value between the Bluetooth tag and the acquisition device is determined based on the plurality of in-phase quadrature signal vectors; the Kalman filtering equation is corrected based on the first Rician factor and the reference angle value, and the target angle value between the Bluetooth tag and the acquisition device is obtained, so that the Bluetooth tag is positioned according to the target angle value; the positioning problem in the related art is solved, and through the correction of the Kalman filtering equation, the influence of wireless signal fading on the positioning accuracy is effectively weakened, and the centimeter-level accurate positioning is realized.

[0186] It should be noted that the above computer storage medium / memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a ferromagnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM) memory, etc. It can also be various terminals including one or any combination of the above memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc.

[0187] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other manners. The embodiments described above are merely exemplary, for example, the division of the units is only a logical function division, and there can be another division manner for the actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the various components shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0188] In addition, each function unit in each embodiment of the present application can be integrated into one processing module, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be realized in the form of hardware, or in the form of hardware plus software function unit. Those skilled in the art can understand that all or part of the steps of the above method embodiments can be completed by a program instructing related hardware, and the foregoing program can be stored in a computer readable storage medium, and when the program is executed, the steps of the method embodiments are executed; and the foregoing storage medium includes mobile storage equipment, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and various media capable of storing program codes.

[0189] The methods disclosed in several method embodiments provided in the present application can be combined arbitrarily without conflict, to obtain new method embodiments.

[0190] The features disclosed in several method or device embodiments provided in the present application can be combined arbitrarily without conflict, to obtain new method embodiments or device embodiments.

[0191] The above description is merely a specific implementation of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed in the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A positioning method, characterized by, The method comprises: Collecting a plurality of in-phase quadrature signal vectors by positioning a signal collection unit i of a collection device in a platform; wherein the in-phase quadrature signal vector is a signal vector received by an antenna i in an antenna array of the collection device corresponding to the signal collection unit i, i is a positive integer greater than 1 and less than or equal to I, I is the total number of the collection units; If it is determined that the signal quality of the signal received by the antenna array meets the signal quality condition based on the plurality of in-phase quadrature signal vectors, determining a first Rician factor corresponding to an antenna group n in the antenna array based on the plurality of in-phase quadrature signal vectors and a Rician fading model; wherein n is a positive integer greater than or equal to 1 and less than or equal to N, N is the total number of the antenna groups; Determining a reference angle value between a Bluetooth tag and the collection device based on the plurality of in-phase quadrature signal vectors; Based on the first Rician factor and the reference angle value, correcting a Kalman filtering equation to obtain a target angle value between the Bluetooth tag and the collection device, so as to position the Bluetooth tag according to the target angle value; Wherein, the correction of the Kalman filtering equation based on the first Rician factor and the reference angle value to obtain the target angle value between the Bluetooth tag and the collection device comprises: Determining the product of the N first Rician factors as an angle solution credibility factor of the collection device; Based on the first position of the collection device obtained, the second position of the Bluetooth tag obtained, and the target signal strength indication vector sent by the Bluetooth tag collected, determining a distance credibility factor of the collection device; Based on the angle solution credibility factor, the distance credibility factor, and the reference angle value, correcting the Kalman filtering equation to obtain the target angle value.

2. The method of claim 1, wherein, In the N antenna groups included in the antenna array, the included angle between each adjacent two antenna groups is within an included angle threshold.

3. The method of claim 2, wherein, The interval between each adjacent two antennas in the antenna group n is within an interval threshold.

4. The method of claim 1, wherein, The determination that the signal quality of the signal received by the antenna array meets the signal quality condition based on the plurality of in-phase quadrature signal vectors comprises: Calculating a signal envelope vector of each in-phase quadrature signal vector; From the plurality of signal envelope vectors, determining a first maximum signal envelope vector and a first minimum signal envelope vector; Based on the first maximum signal envelope vector, the first minimum signal envelope vector, and a first signal vector segment count set, determining a first probability distribution set of the signal envelope vector; wherein the first probability distribution set comprises a first signal envelope vector and a first probability value corresponding to the first signal envelope vector; Inputting a plurality of the first signal envelope vectors and a plurality of the first probability values into the obtained Rician fading model to obtain a first average power of a direct signal and a second average power of a scattered multipath signal; Based on the first average power and the second average power, determining a second Rician factor corresponding to the antenna array; If the second Rake factor is within a Rake factor threshold range, it is determined that the signal quality of the signal received by the antenna array satisfies a signal quality condition.

5. The method of claim 1, wherein, The first Rake factor corresponding to the antenna group n in the antenna array is determined based on the plurality of co-phase quadrature signal vectors and a Rake fading model, including: A partial signal envelope vector corresponding to a partial co-phase quadrature signal vector received by each antenna in the antenna group n is obtained; From the partial signal envelope vector, a second maximum signal envelope vector and a second minimum signal envelope vector are determined; Based on the second maximum signal envelope vector, the second minimum signal envelope vector and a second signal vector segment count set, a second probability distribution set of the partial signal envelope vector is determined; wherein the second probability distribution set includes a second signal envelope vector and a second probability value corresponding to the second signal envelope vector; A plurality of second signal envelope vectors and a plurality of second probability values are input into the Rake fading model to obtain a third average power of a direct signal and a fourth average power of a scattered multipath signal; Based on the third average power and the fourth average power, the first Rake factor corresponding to the antenna group n is determined.

6. The method of claim 5, wherein, The reference angle value between the Bluetooth tag and the acquisition device is determined based on the plurality of co-phase quadrature signal vectors, including: Based on the partial co-phase quadrature signal vector received by each antenna in the antenna group n, the phase difference of the first partial co-phase quadrature signal vector corresponding to each timestamp in the antenna group n is determined; Based on the average of the phase differences corresponding to a plurality of timestamps in the antenna group n, a first angle value between the Bluetooth tag and the antenna group n in the acquisition device is determined; Based on the first angle value and the first Rake factor corresponding to the antenna group n, the reference angle value between the Bluetooth tag and the acquisition device is determined.

7. The method according to any one of claims 1 to 6, characterized in that, The distance reliability factor of the acquisition device is determined based on the obtained first position of the acquisition device, the obtained second position of the Bluetooth tag, and the acquired target signal strength indication vector sent by the Bluetooth tag, including: Based on the first position and the second position, a first distance vector between the Bluetooth tag and the acquisition device is determined; An attenuation coefficient and a reference signal strength indication vector are obtained; The target signal strength indication vector, the attenuation coefficient and the reference signal strength indication vector are input into a wireless signal attenuation model to obtain a second distance vector between the Bluetooth tag and the acquisition device output by the wireless signal attenuation model; Based on the difference between the first distance vector and the second distance vector, the distance reliability factor is determined.

8. The method according to any one of claims 1 to 6, characterized in that, The Kalman filtering equation is modified based on the angle calculation reliability factor, the distance reliability factor and the reference angle value to obtain the target angle value, including: The product of the angle calculation reliability factor and the distance reliability factor is determined as a target reliability factor; The reference angle value is input into the established Kalman filtering time update equation to obtain a predicted angle value output by the Kalman filtering time update equation; correct the established Kalman filtering state update equation based on the target credibility factor, wherein the Kalman filtering equation comprises the Kalman filtering time update equation and the Kalman filtering state update equation; input the predicted angle value into the corrected Kalman filtering state update equation to obtain a target angle value output by the corrected Kalman filtering state update equation.

9. A positioning device, characterized in that The device comprises: The acquisition module is configured to acquire a plurality of in-phase quadrature signal vectors through a signal acquisition unit i of an acquisition device in a positioning platform; wherein the in-phase quadrature signal vector is a signal vector received by an antenna i in an antenna array of the acquisition device corresponding to the signal acquisition unit i, i is a positive integer greater than 1 and less than or equal to I, and I is the total number of the acquisition units; The determination module is configured to determine a first Rician factor corresponding to an antenna group n in the antenna array based on the plurality of in-phase quadrature signal vectors and a Rician fading model if the signal quality of the signal received by the antenna array meets a signal quality condition based on the plurality of in-phase quadrature signal vectors; wherein n is a positive integer greater than or equal to 1 and less than or equal to N, and N is the total number of the antenna groups; The determination module is further configured to determine a reference angle value between a Bluetooth tag and the acquisition device based on the plurality of in-phase quadrature signal vectors; The processing module is configured to correct a Kalman filtering equation based on the first Rician factor and the reference angle value to obtain a target angle value between the Bluetooth tag and the acquisition device, and to position the Bluetooth tag according to the target angle value; The processing module is further configured to determine the product of N first Rician factors as an angle calculation credibility factor of the acquisition device, to determine a distance credibility factor of the acquisition device based on the acquired first position of the acquisition device, the acquired second position of the Bluetooth tag, and the acquired target signal strength indication vector sent by the Bluetooth tag, and to correct the Kalman filtering equation based on the angle calculation credibility factor, the distance credibility factor, and the reference angle value to obtain the target angle value.

10. A positioning platform, characterized by The positioning platform comprises: A memory configured to store executable instructions; A processor configured to execute the executable instructions stored in the memory to implement the positioning method according to any one of claims 1 to 8.

11. A computer storage medium, characterized in that The computer storage medium stores one or more programs executable by one or more processors to implement the positioning method according to any one of claims 1 to 8.

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