Positioning method, device and apparatus

Abstract

The embodiments of the present application relate to the technical field of communications. Provided are a positioning method, device and apparatus. The positioning method is applied to a positioning device, and comprises: acquiring a CIR of a channel between a terminal to be positioned and a base station, wherein the CIR comprises a plurality of samples; on the basis of the amplitude of each sample among the plurality of samples, selecting a reference sample from among the plurality of samples, wherein the amplitude of the reference sample is greater than a preset standard; on the basis of the reference sample, calculating a reference phase; on the basis of the reference phase, performing phase alignment on the plurality of samples, in order to obtain a phase-aligned CIR; and inputting the phase-aligned CIR into a positioning model, in order to acquire positioning information outputted by the positioning model. Applying the solution provided in the embodiments of the present application enables phase alignment of CIRs, so as to eliminate the problem of random initial phase mismatch of the CIRs, thereby improving the positioning accuracy of positioning models.

Description

A positioning method, device, apparatus Technical Field

[0001] This application relates to the field of communication technology, and in particular to a positioning method, device, or apparatus. Background Technology

[0002] In 5G (5th Generation Mobile Communication Technology) NR (New Radio) positioning technology, the PRS (Positioning Reference Signal) or SRS (Sounding Reference Signal) can be measured by the terminal or base station to obtain the Channel Impulse Response (CIR). Then, positioning models such as AI (Artificial Intelligence) or ML (Machine Learning) models can be used to process the CIR, thereby locating the terminal based on the positioning information output by the positioning model, thus achieving 5G NR positioning.

[0003] Because the CIR is obtained by measuring the RS (Reference Signal), and there is an asynchrony between the RS transmitter and receiver, there is a deviation between the time the transmitter transmits the RS and the time the receiver receives it. This leads to a random initial phase mismatch problem in the CIR obtained based on the time-biased RS measurement; that is, each sample point in the measured CIR has a phase shift due to random initial phase mismatch. This causes severe ambiguity during the training and inference of the CIR by the positioning model, thus affecting the positioning performance of the model.

[0004] Summary of the Invention

[0005] The purpose of this application is to provide a positioning method, device, and apparatus for phase alignment of the CIR (Circuit Infrared Array) to eliminate the problem of random initial phase mismatch in the CIR, thereby improving the positioning accuracy of the positioning model. The specific technical solution is as follows:

[0006] In a first aspect, embodiments of this application provide a positioning method applied to a positioning device, the method comprising:

[0007] The channel impulse response (CIR) of the channel between the terminal to be located and the base station is obtained, and the CIR includes multiple samples.

[0008] Based on the amplitude of each of the plurality of sample points, a reference sample point is selected from the plurality of sample points, wherein the amplitude of the reference sample point is greater than a preset standard.

[0009] Calculate the reference phase based on the reference sample points;

[0010] Based on the reference phase, the multiple sample points are phase aligned to obtain the phase-aligned CIR;

[0011] Input the phase-aligned CIR into the positioning model and obtain the positioning information output by the positioning model.

[0012] Secondly, embodiments of this application provide a positioning device, the positioning device comprising:

[0013] processor;

[0014] transceiver;

[0015] A machine-readable storage medium storing machine-executable instructions that can be executed by the processor; the machine-executable instructions cause the processor to perform the following steps:

[0016] The channel impulse response (CIR) of the channel between the terminal to be located and the base station is obtained, and the CIR includes multiple samples.

[0017] Based on the amplitude of each of the plurality of sample points, a reference sample point is selected from the plurality of sample points, wherein the amplitude of the reference sample point is greater than a preset standard.

[0018] Calculate the reference phase based on the reference sample points;

[0019] Based on the reference phase, the multiple sample points are phase aligned to obtain the phase-aligned CIR;

[0020] Input the phase-aligned CIR into the positioning model and obtain the positioning information output by the positioning model.

[0021] Thirdly, embodiments of this application provide a positioning device for use in positioning equipment, the device comprising:

[0022] The CIR acquisition module is used to acquire the channel impulse response (CIR) of the channel between the terminal to be located and the base station, wherein the CIR includes multiple sample points;

[0023] The sample point selection module is used to select a reference sample point from the plurality of sample points based on the amplitude of each sample point among the plurality of sample points, wherein the amplitude of the reference sample point is greater than a preset standard;

[0024] The phase calculation module is used to calculate the reference phase based on the reference sample points;

[0025] A phase alignment module is used to perform phase alignment on the plurality of sample points based on the reference phase to obtain a phase-aligned CIR.

[0026] Input the phase-aligned CIR into the positioning model and obtain the positioning information output by the positioning model.

[0027] Fourthly, embodiments of this application provide a machine-readable storage medium storing machine-executable instructions, which, when invoked and executed by a processor, cause the processor to: implement any of the methods described in the first aspect.

[0028] Fifthly, embodiments of this application provide a computer program product that causes a processor to implement any of the methods described in the first aspect.

[0029] Beneficial effects of the embodiments in this application:

[0030] In the solution provided in this application embodiment, after acquiring the CIR, the positioning device selects suitable reference samples that match the actual amplitude of the samples in the CIR. Then, it calculates the reference phase based on the suitable reference samples. Finally, it performs phase alignment on each sample based on the reference phase. Since the reference samples are not fixed-position samples, but rather samples with amplitudes greater than a preset standard are selected based on the actual amplitude of the samples in the CIR, the selected reference samples are more closely matched to the actual CIR, with larger amplitudes and lower phase noise. Phase alignment on this basis introduces less phase noise into the phase-aligned CIR, making the phase-aligned CIR more accurate. It also eliminates the problem of random initial phase mismatch in the CIR, thereby improving the positioning accuracy of the positioning model. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other embodiments can be obtained based on these drawings without creative effort.

[0032] Figure 1 is a flowchart illustrating the first positioning method provided in an embodiment of this application;

[0033] Figure 2 is a schematic diagram of a reference sample point selection method provided in an embodiment of this application;

[0034] Figure 3 is a flowchart illustrating the second positioning method provided in an embodiment of this application;

[0035] Figure 4 is a flowchart illustrating the third positioning method provided in the embodiments of this application;

[0036] Figure 5 is a schematic diagram of a signaling interaction process provided in an embodiment of this application;

[0037] Figure 6 is a flowchart illustrating the fourth positioning method provided in the embodiments of this application;

[0038] Figure 7 is a schematic diagram of a terminal motion trajectory and confidence region provided in an embodiment of this application;

[0039] Figure 8 is a flowchart illustrating the fifth positioning method provided in the embodiments of this application;

[0040] Figure 9 is a flowchart illustrating the sixth positioning method provided in the embodiments of this application;

[0041] Figure 10 is a flowchart illustrating the seventh positioning method provided in the embodiments of this application;

[0042] Figure 11 is a flowchart illustrating the eighth positioning method provided in this application embodiment;

[0043] Figure 12 is a flowchart illustrating the ninth positioning method provided in an embodiment of this application;

[0044] Figure 13 is a schematic diagram of a phase alignment process provided in an embodiment of this application;

[0045] Figure 14 is a schematic diagram of a verification result provided in an embodiment of this application;

[0046] Figure 15 is a structural schematic diagram of a positioning device provided in an embodiment of this application;

[0047] Figure 16 is a schematic diagram of a positioning device provided in an embodiment of this application. Detailed Implementation

[0048] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0049] To illustrate the difference between the embodiments of this application and related technologies, the phase alignment methods in related technologies will be described in detail first.

[0050] In scenarios where positioning enhancement is achieved using AI or ML models for 5G NR positioning, the terminal or base station obtains channel-related information, such as CIR or PDP (Power Delay Profile), by measuring PRS or SRS. Then, the positioning model outputs positioning information for the terminal based on the obtained channel-related information, thus realizing the 5G NR positioning function.

[0051] In related technologies, positioning based on CIR and PDP has received widespread attention. CIR is the response of a unit pulse signal propagating through space. After a wireless pulse signal is transmitted into space by a transmitter antenna, it reaches the receiver through different propagation paths. Under the assumption of linear time invariance, each point in CIR can be represented by the following equation:

[0052] Where a1, θ1, and τ1 represent the amplitude attenuation, phase shift, and time delay of the first signal propagation path, respectively. L is the total number of signal propagation paths. p1(t) represents the unit pulse waveform reaching the receiver through the first signal transmission path with a time delay of t. t represents the time delay. j is the unit of measurement for the imaginary part.

[0053] Therefore, CIR describes the amplitude and phase response of a wireless pulse signal at different time delays as it propagates through a channel, and is often used to represent the multipath effect of a channel.

[0054] In addition, PDP is obtained by averaging CIR in the time domain and then squaring it. It is used to describe the power of the channel at different time delays, that is, the power of multipath signals with different arrival times.

[0055] Therefore, CIR samples need to be represented using two paths, I and Q. The I path represents the in-phase component, and the Q path represents the quadrature component. PDP samples only output one amplitude value. If the bit width of each wireless pulse signal is the same, using CIR as the model input will increase the network reporting overhead compared to PDP.

[0056] However, because CIR contains richer information, it can provide additional phase information about samples or paths to the positioning model during NR positioning, thus improving the positioning accuracy of the positioning model. Therefore, CIR provides higher positioning accuracy for NR positioning.

[0057] However, CIR suffers from random phase mismatch, which affects the accuracy of positioning information obtained by the positioning model from CIR processing. Therefore, it is necessary to eliminate the random initial phase mismatch of CIR to avoid the decrease in AI / ML positioning accuracy caused by its use as input to the positioning model.

[0058] Therefore, phase alignment can be used to solve the problem of random initial phase mismatch. Phase alignment methods in related technologies can be specifically divided into two categories: two-phase differential and relative phase.

[0059] (1) Two-phase differential. In this method, the problem of random initial phase mismatch is eliminated by calculating the CIR phase difference from node A to two synchronization nodes B and C. This is because the random initial phase mismatch of links AB and AC is the same. Link AB is the link between node A and node B, and link AC is the link between node A and node C. However, this requires collecting data on both links when performing NR positioning, making data collection cumbersome. In addition, in complex propagation scenarios, the two links may experience different propagation. For example, link AB is in a LOS (Line of Sight) scenario while link AC is in a NLOS (Non-Line of Sight) scenario. In this case, the random initial phase mismatch of the two links is not the same, so the two-phase differential method cannot be used for phase alignment. In other words, the above method can only be used in LOS scenarios, which limits its application scenarios.

[0060] (2) Relative Phase. In this method, a fixed sample point is first selected in the CIR. Using the phase of this sample point as a reference, the relative phases of other samples in the CIR to this sample point are calculated. This relative phase also carries useful information about channel propagation. Since the initial random phase mismatch has an almost equal impact on all samples / paths in the CIR, that is, the phase shifts caused by the initial random phase mismatch to each sample point in the CIR are almost equal, the relative phases between each other sample point and the reference sample point are almost equal and can be eliminated together. This method is not limited to LOS or NLOS scenarios, and is therefore more suitable for NR positioning.

[0061] The relative phase method will be described in more detail below.

[0062] Assume the input CIR is represented as Where h input h is the set of all samples in the CIR. input，1 For the first sample point, h input，2 For the second sample point, For the Nth t N sample points. t The total number of sample points.

[0063] The i-th sample point h input i can be represented as:

[0064] Where j is the unit of measurement for the imaginary part, h′i and These are the measured values ​​of the amplitude and phase of the i-th sample point, respectively. h′i can be represented as the true amplitude value hi and the equivalent amplitude noise h′. noise，i The sum of. It can be represented as the true value of the phase θ i Phase offset θ caused by random initial phase mismatch mismatch Equivalent phase noise θ′ noise,i The sum. For details, please refer to the following formula (1): h′ i =h i +h′ noise，i

[0065] When the terminal's location changes, h i and θ i Consequently, h changes. i and θ i It implicitly contains the terminal's location information. Therefore, it includes h. i and θ i The CIR can be used as the model input for the positioning model to locate the terminal.

[0066] In related technologies, a sample at a fixed position is selected from the CIR as a reference sample. Due to the influence of the sample input order, the first sample input is often chosen as the reference sample to align the phase of subsequent input samples. The phase of the reference sample is used as the reference phase. When the first sample is used as the reference sample, the reference phase is... Based on this, the data of each sample point are multiplied by Perform phase alignment. Calculate the i-th sample point h after phase alignment. comp,i This can be expressed by the following formula (2):

[0067] The i-th sample point before phase alignment As can be seen, phase alignment eliminates the phase offset θ caused by random initial phase mismatch. mismatch However, after phase alignment, the phase noise of the i-th sample point is θ′. noise，i -θ′ noise，1 Compared to the i-th sample point before phase alignment in formula (1) above, additional phase noise θ′ is added. noise，1 .

[0068] Additionally, it should be noted that if i = 1, then That is, the first sample point after phase alignment can be represented as h. comp，1 =h′ iTherefore, the phase information of the first sample point is lost after phase alignment. In other words, the phase information of the reference sample point will be lost after phase alignment using the relative phase method, but since only the phase information of one sample point is lost, it is acceptable.

[0069] However, to ensure the integrity of CIR measurements in the time domain, the first sample point is typically located at the beginning of the first signal propagation path of the CIR, or even in the noise region before the first signal transmission path. Therefore, the true amplitude value h1 of the first sample point is relatively low. Assuming the noise power remains stable during the measurement, because the true amplitude value h1 of the first sample point is small, the noise has a significant impact on h1 and θ1. This translates to the equivalent amplitude noise h′. noise，1 and equivalent phase noise θ′ noise，1 Larger.

[0070] Therefore, compared to h input After phase alignment, the equivalent phase noise of each sample point will be affected by θ′. noise，1 The additional introduction of phase noise enhances the effect. Especially for sample i, which has a stronger true amplitude and contains more terminal location information, the phase noise shows a significant deterioration. It may even lead to h... comp，i The true value of the phase θ in i -θ1, and equivalent phase noise (θ′) noise，i -θ′ noise，1 The value is too small compared to the h value. This, in turn, affects the localization model from h. comp，i The terminal's position information is extracted from the true phase value. At this point, whether the CIR input positioning model is directly used before phase alignment or after phase alignment, both will result in low positioning performance.

[0071] The above process takes the first sample point as a reference sample point as an example. However, as long as a fixed sample point is sampled as a reference sample point, the reference sample point may have a small true value of amplitude, which will affect the positioning performance.

[0072] As can be seen, the CIR in related technologies suffers from random initial phase mismatch, leading to inaccurate positioning information based on CIR. To solve this problem, phase alignment of the CIR is required. Therefore, embodiments of this application provide a positioning method, device, and apparatus.

[0073] Referring to Figure 1, which is a flowchart illustrating the first positioning method provided in this application embodiment, the method is applied to a positioning device, which may be a first terminal, a first base station, or an LMF (Location Management Function) device. The method includes the following steps S101-S105.

[0074] S101: Obtain the CIR of the channel between the terminal to be located and the base station.

[0075] The aforementioned CIR includes multiple sample points. In one embodiment of this application, the aforementioned CIR can be measured by the positioning device itself, or it can be measured by other devices and then sent to the positioning device. The aforementioned terminal can be a user terminal or other network terminal, and the aforementioned base station can be a gNB (next generation NodeB), an eNB (evolved Node B), etc.

[0076] Furthermore, when the executing entity in this application embodiment is a first terminal, the terminal corresponding to CIR can be the first terminal. After executing subsequent steps S102-S105, the first terminal can locate itself. Alternatively, the terminal corresponding to CIR can be another terminal besides the first terminal. After executing subsequent steps S102-S105, the first terminal can locate other terminals besides itself.

[0077] Furthermore, when the executing entity in this application embodiment is the first base station, the base station corresponding to the CIR can be the first base station, that is, the CIR obtained by the first base station is the CIR of the channel between itself and the terminal to be located. Alternatively, the base station corresponding to the CIR may not be the first base station, that is, the CIR obtained by the first base station is the CIR of the channel between another base station other than the first base station and the terminal.

[0078] The specific sources of CIR can be found in the description below, and will not be detailed here.

[0079] S102: Select a reference sample point from the above sample points based on the amplitude of each sample point.

[0080] The amplitude of the aforementioned reference sample points is greater than the preset standard.

[0081] In one embodiment of this application, a sample point whose amplitude is greater than a preset standard can be selected from the plurality of sample points as a reference sample point. The phrase "greater than the preset standard" can mean that the amplitude of the reference sample point is greater than the amplitudes of all other sample points, or that the amplitude of the reference sample point is greater than a set amplitude threshold.

[0082] In one embodiment of this application, reference sample points can be selected using the first algorithm described below. The first algorithm may be referred to as the "strongest sample point method," and a detailed description can be found below.

[0083] In another embodiment of this application, reference sample points can also be selected by the second algorithm described below. The second algorithm can be referred to as the "first satisfying sample point method", and a detailed description can also be found in the following description.

[0084] S103: Calculate the reference phase based on the above reference samples.

[0085] In one embodiment of this application, the phase of the aforementioned reference sample point is directly used as the reference phase. The index of this reference sample point is denoted as I. ref ,but Where θ0 is the reference phase. For index I ref The phase of the sample points.

[0086] In another embodiment of this application, a sample point can be selected first as a reference sample point. Then, since the phase of adjacent samples in a CIR generally does not change significantly, after obtaining the reference sample point, a predetermined number of samples can be extracted from the reference sample point to form a sample point set. The sample point set can also be called a sample point vector. When a sample point set exists, the reference phase is calculated using all the samples in the set.

[0087] This application provides two algorithms for calculating the reference phase: a third algorithm and a fourth algorithm. The third algorithm can be referred to as the mean method, and the fourth algorithm can be referred to as the minimum phase angle method. Detailed descriptions of the third and fourth algorithms are provided below.

[0088] S104: Based on the above reference phase, perform phase alignment on the above multiple samples to obtain the phase-aligned CIR.

[0089] Specifically, multiple samples in a CIR can be phase-aligned using the following formula:

[0090] Among them, h comp，i h is the i-th sample point after phase alignment. input，i Let θ be the i-th sample before phase alignment, and θ0 be the reference phase. The meanings of other parameters can be found above. All the phase-aligned samples together form the phase-aligned CIR.

[0091] The phase-aligned CIR can be used to input the localization model to generate localization information, or for training the localization model, or for testing the localization model. This application does not limit the phase-aligned CIR.

[0092] S105: Input the phase-aligned CIR into the positioning model and obtain the positioning information output by the positioning model.

[0093] The aforementioned positioning model can be an AI model or an ML model. This application does not limit the specific structure and training method of the positioning model, as long as the input phase alignment result can be processed to obtain the positioning information.

[0094] In addition, the aforementioned positioning information can be the coordinates of the terminal directly. Alternatively, the positioning information can be auxiliary positioning information, which is an intermediate value in the process of generating the terminal's coordinates. Or, the positioning information can also be the coordinates of a fixed reference point in the environment. The coordinates of the terminal can be further calculated based on the coordinates of the reference point. The process of calculating the terminal's coordinates based on the coordinates of the reference point can be implemented using relevant technologies, which will not be elaborated upon in this embodiment.

[0095] Furthermore, since continuous positioning of the terminal is often required, it is necessary to continuously acquire CIRs and perform phase alignment. The number of phase-aligned CIRs needed for training and testing the positioning model is often large, thus requiring continuous acquisition and phase alignment of CIRs as well. Therefore, steps S101-S105 can be executed cyclically and continuously.

[0096] As can be seen from the above, in the solution provided by this application embodiment, after acquiring the CIR, the positioning device selects suitable reference samples that match the actual amplitude of the samples in the CIR. Then, it calculates the reference phase based on the suitable reference samples. Finally, it performs phase alignment on each sample based on the reference phase. Since the reference samples are not fixed-position samples, but rather samples with amplitudes greater than a preset standard are selected based on the actual amplitude of the samples in the CIR, the selected reference samples are more closely matched to the actual situation of the CIR, with larger amplitudes and lower phase noise. Phase alignment on this basis introduces less phase noise into the phase-aligned CIR, making the phase-aligned CIR more accurate. It also eliminates the problem of random initial phase mismatch in the CIR, thereby improving the positioning accuracy of the positioning model.

[0097] In one embodiment of this application, step S102 described above can be implemented by step A.

[0098] Step A: Using either the first or second algorithm, select a reference sample point from the multiple sample points based on the amplitude of each sample point.

[0099] The first algorithm selects the sample point with the largest amplitude from multiple sample points as the reference sample point. The second algorithm selects the first sample point with an amplitude threshold higher than the amplitude threshold from the multiple sample points as the reference sample point. The amplitude threshold is a preset multiple of the noise standard deviation of the CIR.

[0100] In this embodiment of the application, the amplitude of each sample point in the CIR can be determined, and the sample point with the highest amplitude can be selected as the reference sample point after comparing the amplitudes of each sample point.

[0101] The selected reference sample point has the largest amplitude and the smallest noise. As mentioned earlier, the larger the amplitude of the reference sample point, the smaller the noise, and the smaller the phase noise introduced into the sample point after phase alignment. Therefore, by using the strongest sample point method to select the reference sample point with the largest amplitude and the smallest noise, the phase noise introduced into the sample point after phase alignment is minimized. Furthermore, the reference sample point can be selected through simple amplitude comparison, the first algorithm requires less computation, and the selection speed of the reference sample point is faster.

[0102] In one embodiment of this application, the noise standard deviation of the CIR can be calculated first. The noise standard deviation of the CIR can be calculated in any way in the related art, and this embodiment of the application does not limit this.

[0103] After calculating the noise standard deviation, if the preset multiple is 1, the noise standard deviation will be used as the amplitude threshold. Alternatively, if the preset multiple is N and N>1, then N times the noise standard deviation will be used as the amplitude threshold. The preset multiple can be set according to requirements.

[0104] Specifically, an amplitude higher than the amplitude threshold indicates that the amplitude of the sample point is much higher than the noise floor, resulting in less noise in the selected reference sample point. After phase alignment, the phase noise introduced into the sample point is also less.

[0105] Following the order in which the samples are acquired, the first sample with an amplitude higher than the amplitude threshold is taken as the reference sample. This allows for the rapid acquisition of the reference sample, which in turn enables phase alignment of subsequent acquired samples. Therefore, the second algorithm can also be called the "first-satisfaction sample method".

[0106] Furthermore, as mentioned above, the phase information of the sample selected as the reference sample will be lost after phase alignment. Therefore, in order to retain the phase information of the sample with the strongest amplitude as much as possible, the "first-satisfaction sample method" can be used to select the reference sample. This way, the sample with the highest amplitude may not be selected as the reference sample, thus retaining the phase information of the sample with the largest amplitude, while also ensuring that the selected reference sample has low noise, introducing less phase noise after phase alignment.

[0107] Referring to Figure 2, it is a schematic diagram of a reference sample selection method provided in an embodiment of this application.

[0108] In the graph, the horizontal axis corresponds to each sample point, and the vertical axis represents the amplitude of each sample point. The wavy curve represents the CIR waveform, the vertical lines represent the amplitude corresponding to each sample point, and the circles represent the positions of the sample points. The horizontal line represents the amplitude threshold.

[0109] In the figure, sample 1 is the reference sample selected when performing phase alignment using correlation techniques. It can be seen that this sample has a low amplitude and high noise. The signal transmission path containing sample 1 is the first path. The first sample that satisfies the condition is the first sample with an amplitude greater than the amplitude threshold. The strongest sample is the sample with the highest amplitude. The signal transmission path containing the strongest sample is the strongest path.

[0110] Alternatively, step S103 described above can be achieved through step B.

[0111] Step B: Using the third or fourth algorithm, calculate the reference phase based on the above reference samples.

[0112] The third algorithm described above is as follows: calculate the average phase of each sample point in the sample point set as a reference phase. The sample point set includes multiple consecutive sample points starting from the reference sample point.

[0113] Specifically, the reference phase can be calculated using the following formula:

[0114] Where 00 is the reference phase, L ref h represents the number of points in the sample set, or the length of the sample set, and angle(*) represents the phase of the complex number. ref，i Let i be the i-th sample point in the sample point set, where i is the sample point number in the sample point set.

[0115] The third algorithm is simple to implement; the reference phase can be quickly obtained through a simple mean calculation. The third algorithm can also be called the "mean method".

[0116] The fourth algorithm described above is as follows: For each of the multiple candidate angles, calculate the sum of the imaginary parts of the phase of the sample points in the sample point set after rotating the candidate angle, and select the candidate angle that minimizes the sum of the imaginary parts as the reference phase.

[0117] Since the sample points in the sample set are a predetermined number of samples starting from the reference sample point, the samples in the sample set are adjacent samples. Theoretically, the phases of adjacent samples in a CIR should be approximately the same. Therefore, after rotating the phases of each sample point by the same suitable candidate angle, the imaginary part of each sample point should be close to 0. Based on this, the candidate angle that minimizes the sum of the imaginary parts of all samples is taken as the reference phase.

[0118] Specifically, the reference phase can be calculated using the following formula:

[0119] Here, imag(*) represents the imaginary part of the complex number elements. See above for descriptions of the other parameters.

[0120] Since it's impossible to exhaustively enumerate all candidate angles within the range [0, 2π] to calculate θ0, in practical implementations, a minimum interval between candidate angles can be set. Just gather from the alternative angles The search in the middle makes the sample set h ref，i e -jθ The candidate angle with the smallest sum of the imaginary parts of the midpoints can be used as the reference phase.

[0121] The fourth algorithm can also be called the minimum phase angle method.

[0122] Compared to the mean method, the minimum phase angle method is more complex and requires more computational resources. However, it considers the amplitude of the samples in the sample set, thus giving greater weight to samples with larger amplitudes and lower equivalent noise when calculating the reference phase. This makes the calculated reference phase more susceptible to the influence of samples with lower equivalent noise. Ultimately, the calculated reference phase is more accurate, so the minimum phase angle method has better reference phase estimation performance.

[0123] Referring to Figure 3, which is a flowchart of the second positioning method provided in the embodiment of this application, when the positioning device is a first terminal or a first base station, compared with the embodiment shown in Figure 1 above, the following step S106 is included before the above step S101.

[0124] S106: Receive the first signaling sent by the LMF device.

[0125] The first signaling includes a first flag value and a second flag value. The first flag value represents the algorithm used to select the reference sample points, and the second flag value represents the algorithm used to calculate the reference phase.

[0126] The aforementioned first signaling can be referred to as phase mismatch elimination configuration signaling. This first signaling is used to instruct the positioning device on the algorithm used when selecting reference samples and calculating reference phases.

[0127] Specifically, the algorithm used for selecting reference sample points and calculating reference phase is generally fixed during the execution of the embodiments of this application by the positioning device, so step S106 usually only needs to be executed once.

[0128] Compared with the embodiment shown in Figure 1 above, step S102 can be implemented by step S102A.

[0129] S102A: Using the algorithm represented by the first marker value, a reference sample point is selected from the plurality of sample points based on the magnitude of each sample point.

[0130] The algorithm represented by the first tag value can be either the first algorithm or the second algorithm.

[0131] In one embodiment of this application, when the first marker value is a first value, the first marker value is used to represent the first algorithm.

[0132] When the first flag value is the second value, the first flag value is used to represent the second algorithm.

[0133] Specifically, the length of the first flag value can be 1 bit. In one case, the first value is 0 and the second value is 1. In another case, the first value is 1 and the second value is 0.

[0134] Compared with the embodiment shown in Figure 1 above, step S103 can be implemented by step S103A.

[0135] S103A: Using the algorithm represented by the second marker value mentioned above, the reference phase is calculated based on the reference sample points mentioned above.

[0136] The algorithm represented by the second tag value can be either the third or the fourth algorithm.

[0137] When the second marker value is the third value, the second marker value is used to represent the third algorithm.

[0138] When the second marker value is the fourth value, the second marker value is used to represent the fourth algorithm.

[0139] The length of the second flag value can also be 1 bit. In one case, the first value is 0 and the second value is 1. In another case, the first value is 1 and the second value is 0.

[0140] Furthermore, it should be noted that this application does not limit the specific values ​​of the first, second, third, and fourth values, as long as the first value is not equal to the second value, and the third value is not equal to the fourth value. The first and third values ​​can be equal or unequal. The first and fourth values ​​can be equal or unequal. The second and third values ​​can be equal or unequal. The second and fourth values ​​can be equal or unequal.

[0141] In addition to the first and second algorithms provided in the embodiments of this application, other algorithms can also be used to select reference samples. For example, any sample with a phase greater than the noise standard deviation of CIR can be selected as a reference sample. In this case, the number of bits contained in the first flag value can be set according to the number of optional algorithms for selecting reference samples, as long as the number of possible values ​​for the first flag value is greater than or equal to the number of algorithms for selecting reference samples.

[0142] The number of bits in the second flag value can also be set according to the number of optional algorithms for calculating the reference phase, as long as the number of possible values ​​of the second flag value is greater than or equal to the number of algorithms for calculating the reference phase. For example, different values ​​of the second flag value can represent the third algorithm, the fourth algorithm, and the algorithm that directly uses the phase of the reference sample as the reference phase, etc.

[0143] To reduce the space occupied by the first and second flag values ​​in the first signaling, the number of bits in the first flag value can be set to the minimum number of bits required to ensure that the number of possible values ​​for the first flag value is greater than or equal to the number of algorithms for selectable reference samples. Similarly, the number of bits in the second flag value can be set to the minimum number of bits required to ensure that the number of possible values ​​for the second flag value is greater than or equal to the number of algorithms for selectable reference phases.

[0144] Based on the above description, in a possible example, both the first and second identifier values ​​are 1 bit. A combined value of 00 indicates the selection of "strongest sample method" + "mean method". A combined value of 01 indicates the selection of "strongest sample method" + "minimum phase angle method". A combined value of 10 indicates the selection of "first satisfying sample method" + "mean method". A combined value of 11 indicates the selection of "first satisfying sample method" + "minimum phase angle method".

[0145] As can be seen from the above, in the embodiments of this application, the LMF device can control the algorithm used by the positioning device when selecting reference sample points and calculating reference phase through the first signaling, thereby controlling the phase alignment process of the positioning device.

[0146] In another embodiment of this application, the first signaling further includes a first parameter, which represents the number of samples used to calculate the reference phase. If the first parameter is equal to 1, it indicates that there is only one sample used to calculate the reference phase, i.e., a reference sample, and there is no sample set. If the first parameter is greater than 1, it indicates that there are multiple samples used to calculate the reference phase, forming a sample set. In another embodiment of this application, the length of the first parameter can be 2 bits, and the value range can be [1, 2, 3, 4].

[0147] When the first flag value represents the second algorithm, the first signaling also includes a second parameter, which is used to represent the preset multiple.

[0148] When the first marker value represents the second algorithm, the amplitude threshold in the second algorithm is a preset multiple of the noise standard deviation. In this case, the second parameter can represent the preset multiple. If the second parameter is not present in the first signaling, the positioning device can also calculate the amplitude threshold based on the default preset multiple.

[0149] In the case where the second marker value represents the fourth algorithm, the first signaling also includes a third parameter, which is used to represent the minimum interval between each alternative angle.

[0150] When the second marker value represents the fourth algorithm, the fourth algorithm requires setting the minimum interval between the candidate angles. In this case, the third parameter can represent the minimum interval between the candidate angles. If the third parameter is not present in the first signaling, the positioning device can also determine that the minimum interval between the candidate angles is the default interval.

[0151] In addition, to save the bits occupied by the second and third parameters, the actual meaning of different values ​​of the second and third parameters can be agreed upon between the sending and receiving ends of the first signaling.

[0152] For example, the second parameter can be predefined to have a value of 00 representing a preset multiple of 2. A value of 01 represents a preset multiple of 4. A value of 10 represents a preset multiple of 8. A value of 11 represents a preset multiple of 12. If the second parameter is directly set to a standard binary number, when the maximum preset multiple is the decimal number 12, 4 bits of binary "1100" would be needed to represent the decimal number 12. Therefore, using the predefined method saves 2 bits.

[0153] In another example, the third parameter can be predefined to have a value of 00, representing a minimum interval of 1° between candidate angles. A value of 01 represents a minimum interval of 5°. A value of 10 represents a minimum interval of 10°. A value of 11 represents a minimum interval of 20°. If the third parameter were directly set to a standard binary number, a 5-bit binary number "10100" would be needed to represent the decimal number 20 when the maximum minimum interval is 20. Therefore, using the predefined method saves 3 bits.

[0154] In another embodiment of this application, referring to FIG4, it is a flowchart of the third positioning method provided by the embodiment of this application. Compared with the embodiment shown in FIG3 above, the step S107 is included before step S106.

[0155] S107: Send the second signaling to the LMF device.

[0156] The aforementioned second signaling can be referred to as the "provide alignment capabilities" signaling.

[0157] The second signaling mentioned above includes a fourth parameter and a fifth parameter. The fourth parameter is used to represent the algorithm supported by the positioning device for selecting the reference sample points, and the fifth parameter is used to represent the algorithm supported by the positioning device for calculating the reference phase.

[0158] Different values ​​for the fourth parameter can indicate that the positioning device supports only the first algorithm, only the second algorithm, both the first and second algorithms, or neither the first nor the second algorithm. For example, the fourth parameter is 2 bits, with a value of 00 indicating that the positioning device supports only the first algorithm, a value of 01 indicating that the positioning device supports only the second algorithm, a value of 10 indicating that neither of the two algorithms is supported, and a value of 11 indicating that both of the two algorithms are supported.

[0159] Different values ​​for the fifth parameter can indicate that the positioning device supports only the third algorithm, only the fourth algorithm, both the third and fourth algorithms, or neither the third nor the fourth algorithm. For example, the fifth parameter is 2 bits; a value of 00 indicates that the positioning device supports only the third algorithm, a value of 01 indicates that the positioning device supports only the fourth algorithm, a value of 10 indicates that neither of the above algorithms is supported, and a value of 11 indicates that both of the above algorithms are supported.

[0160] Accordingly, when generating the first signaling, the LMF device must set the values ​​of the parameters in the first signaling to the values ​​corresponding to the algorithms supported by the positioning device, based on the capabilities of the positioning device. This instructs the positioning device to use its supported algorithms for data processing. Therefore, the algorithm represented by the first marker value is one of the algorithms supported by the positioning device for selecting the reference sample points. The algorithm represented by the second marker value is one of the algorithms supported by the positioning device for calculating the reference phase.

[0161] In addition, the second signaling may also include a third flag value, which indicates whether the positioning device supports phase alignment. For example, the third flag value can be 1 bit, with a value of 0 indicating that phase alignment is not supported, and a value of 1 indicating that phase alignment is supported.

[0162] Upon receiving the second signaling, the first signaling sent by the LMF device to the positioning device may also include a fourth flag value. This fourth flag value indicates whether the positioning device is suitable for phase alignment. The fourth flag value is 1 bit; a value of 0 indicates that the device is not suitable for phase alignment, and a value of 1 indicates that the device is suitable for phase alignment. Alternatively, a value of 1 indicates that the device is not suitable for phase alignment, and a value of 0 indicates that the device is suitable for phase alignment.

[0163] In this case, the aforementioned first signaling can be referred to as alignment configuration signaling. If the fourth flag value indicates that the positioning device is not suitable for phase alignment, the device may not execute subsequent steps S101-S105, and the process of this embodiment ends.

[0164] Referring to Figure 5, it is a schematic diagram of a signaling interaction process provided in an embodiment of this application.

[0165] In the diagram, the terminal / base station refers to the first terminal / base station acting as the positioning device. The terminal / base station sends a provide alignment capabilities signaling message to the LMF device, and the LMF device sends an alignment configuration signaling message to the terminal / base station, thus completing the signaling interaction.

[0166] As can be seen from the above, before the LMF device sends the first signaling to the positioning device, the positioning device can also send a second signaling to the LMF device to notify the LMF device of the positioning device's ability to select reference samples and calculate reference phase, so that the LMF device can issue the first signaling according to the positioning device's capabilities.

[0167] In another embodiment of this application, the second signaling further includes a sixth parameter, which represents the range of values ​​for the number of samples used to calculate the reference phase.

[0168] If the algorithm represented by the fourth parameter above includes the second algorithm, the second signaling above also includes the seventh parameter.

[0169] The seventh parameter mentioned above is used to represent the range of values ​​for the preset multiple.

[0170] If the algorithm represented by the fifth parameter above includes the fourth algorithm, the second signaling above also includes the eighth parameter.

[0171] The eighth parameter mentioned above is used to represent the range of values ​​for the interval between each candidate angle.

[0172] In another embodiment of this application, the positioning device is further configured with a positioning model. In this case, referring to FIG6, which is a flowchart of the fourth positioning method provided by the embodiment of this application, compared with the embodiment shown in FIG1 above, the following steps S108-S110 are included after the above step S105.

[0173] S108: Based on the obtained positioning information, predict the confidence zone in which the above terminal should be located at the future target time.

[0174] Since the terminal's location may change, this embodiment of the application can periodically and continuously locate the terminal to continuously obtain location information. In this case, based on all the obtained location information, or a fixed number of recently obtained location information, the confidence region where the location information at a future target time should be located can be predicted. In one embodiment of this application, the terminal's future moving speed and future moving route can be predicted, and the predicted position that the terminal can move to along the predicted moving route at the predicted moving speed can be calculated. The area centered on this predicted position with a radius of a preset radius is determined as the confidence region.

[0175] In another embodiment of this application, the probability of the terminal being at each location at a future target time can be estimated separately to obtain the probability distribution P of the terminal being at each location x. k (x|X k-1 Where k represents the k-th time, i.e., the future target time, X k-1 Let X be the set of terminal locations determined in the first k-1 time steps. k-1 = [x1, x2, ..., x k-1 [And predict the position of the terminal at time k]. Set a pre-set confidence level Γ (0 < Γ < 1), and define the set of positions with a probability greater than Γ as the confidence region.

[0176] Alternatively, other methods in related technologies can be used to predict the confidence region where the terminal should be at a future target time based on the determined location of the terminal. This application does not limit this approach.

[0177] Referring to Figure 7, it is a schematic diagram of a terminal motion trajectory and confidence region provided in an embodiment of this application.

[0178] In the figure, the black dots represent the terminal's position indicated by the positioning information obtained in the previous k-1 time steps, the white dots represent the terminal's position at the predicted target time step, the dashed lines represent the terminal's motion trajectory, and the ellipses in the figure represent the confidence region.

[0179] In theory, the terminal should be located within this confidence region at the target future time.

[0180] S109: After reaching the target time, the location information of the target time is obtained to determine the actual location of the terminal at the target time.

[0181] Once the target time is reached, the actual location of the terminal at the target time can be determined through steps S101-S105 as described above, which will not be repeated here.

[0182] S110: Determine whether the actual location corresponding to the current target time is within the current confidence region.

[0183] A target time is a relative concept, meaning it is a future moment. As the embodiments of this application continue to execute, time will reach that target time, at which point the target time will be updated to another future moment. Predicting the target time at different times can yield different confidence regions. When the target time arrives, the actual location of the terminal corresponding to that target time will be obtained. In other words, each target time corresponds to a confidence region and an actual location, and these two are compared for judgment. As the embodiments of this application continue to execute, multiple judgment results may be obtained.

[0184] If the cumulative number of times the actual location is not located in the confidence region has not reached the preset number, then return to step S101.

[0185] If the cumulative number of times does not reach the preset number, it means that the number of times the actual location is determined to be outside the confidence region is relatively small, indicating that the actual location determined by the scheme provided by the present application embodiment is relatively accurate. Therefore, the execution step S101 can be returned.

[0186] Conversely, if the cumulative count reaches the preset number, it indicates that the currently determined actual position is inaccurate. This problem may be caused by inaccurate CIR after phase alignment.

[0187] Since continuous phase alignment of samples in the CIR requires significant computational resources, continuing phase alignment would only waste resources if the accuracy is lower than a preset accuracy. Therefore, the current phase alignment process can be stopped, i.e., steps S102-S104 can be discontinued to reduce resource consumption. In subsequent positioning processes, the obtained CIR is directly input into the positioning model to obtain positioning information.

[0188] In another embodiment of this application, if the cumulative number of times the actual position is not located within the confidence region reaches a preset number, it indicates that the current phase alignment method is not suitable for the current scenario. Therefore, the current phase alignment process can be stopped, and a new phase alignment method can be used to continue phase alignment and positioning. For example, the selection method of the reference sample points can be adjusted, switching between the "strongest sample point method" and the "first satisfying sample point method". Alternatively, the calculation method of the reference phase can be adjusted, switching between the "minimum phase angle method" and the "mean method". Or, the interval of the smallest alternative angle when calculating the reference phase using the minimum phase angle method can be adjusted. Alternatively, the phase alignment method can be switched from the method provided in the embodiments of this application to other methods in related technologies. Continue to execute the aforementioned steps S101-S105.

[0189] Furthermore, if the actual location of the terminal determined by the positioning information at the target time is not within the aforementioned confidence region, it may be due to a malfunction in the positioning model. Therefore, in addition to stopping the current phase alignment process, the positioning model can be readjusted. For example, retraining the positioning model or adjusting its structure. In other words, the embodiments of this application can also provide assistance in monitoring the positioning model.

[0190] Additionally, the aforementioned preset number of times can be 1, meaning that if a single judgment result indicates that the actual position of the terminal is not within the aforementioned confidence region, then the current phase alignment is determined to be inaccurate. Alternatively, the preset number of times can be greater than 1, meaning that if multiple judgment results indicate that the actual position of the terminal is not within the aforementioned confidence region, then the current phase alignment is determined to be inaccurate. Or, if the preset number of times is greater than 1, and the judgment results obtained for a consecutive preset number of times indicate that the actual position of the terminal is not within the aforementioned confidence region, then the current phase alignment is determined to be inaccurate.

[0191] As can be seen from the above, the solution provided in this application can monitor phase alignment and only continue phase alignment processing when the phase alignment is accurate, thereby avoiding the waste of computing resources.

[0192] In addition, based on the selection of positioning devices for deploying positioning models and the positioning framework, NR positioning scenarios can be divided into three categories and five scenarios.

[0193] Scenario 1: In the framework of using a positioning model for direct or assisted positioning, the positioning model is deployed in the first terminal, which acts as a positioning device. The positioning information output by the positioning model in the first terminal is directly the coordinates of the terminal to be located.

[0194] Scenario 2a: The positioning model is deployed in the first terminal, which acts as a positioning device. The positioning information output by the positioning model in the first terminal is used to assist in the positioning of the terminal to be located, and the LMF device performs the final positioning.

[0195] Scenario 2b: The positioning model is deployed in the LMF device. The LMF device acts as a positioning device, and the terminal to be located is assisted in positioning. The positioning information output by the positioning model in the LMF device is directly the coordinates of the terminal to be located.

[0196] Scenario 3a: The positioning model is deployed in the first base station, which acts as the positioning device. The NG-RAN (Next Generation Radio Access Network) node assists in positioning. The positioning information output by the positioning model in the first base station is used to assist in the positioning of the terminal to be located, and the LMF device performs the final positioning.

[0197] Scenario 3b: The positioning model is deployed in the LMF device, which acts as a positioning device with NG-RAN assisted positioning. The positioning information output by the positioning model in the LMF device is directly the coordinates of the terminal to be located.

[0198] Scenario 1 above is the first type of scenario, where the positioning process is mainly completed by the terminal.

[0199] The above scenarios 2a and 2b are the second type of scenarios, where the positioning process is mainly completed by the interaction between the terminal and the LMF device.

[0200] The above scenarios 3a and 3b are the third type of scenarios, where the positioning process is mainly completed by the interaction between the base station and the LMF device.

[0201] In addition, scenario 3a above includes sub-scenario 1 and sub-scenario 2. In sub-scenario 1, the CIR is measured by the base station itself, while in sub-scenario 2, the CIR is measured by the terminal and sent to the base station.

[0202] The specific process of NR positioning is described below for different scenarios.

[0203] Referring to Figure 8, which is a flowchart illustrating the fifth positioning method provided in this application embodiment, applicable to the aforementioned scenario 1, the terminal to be located in this embodiment is the first terminal, referred to simply as the terminal in Figure 8. The complete positioning process includes steps 0a-4a, a total of five steps.

[0204] The content within the first solid box in the diagram represents step 0a: configuration. This means the LMF device sends a phase mismatch elimination configuration to the terminal, implementing step S106. If no configuration anomalies occur, this step can be performed only once after location startup.

[0205] The second and third solid-line boxes in the diagram represent two identical positioning processes. The only difference is that the third solid-line box contains some steps indicated by dashed lines, signifying that these steps can be omitted. Therefore, to avoid repetition, only the steps contained in the second solid-line box will be described here.

[0206] The content within the dashed box in the second solid box in the figure represents step 1a: CIR measurement.

[0207] The specific process is as follows: The LMF device sends a positioning information request to the base station. The base station sends a PRS configuration to the terminal and a positioning information ack to the LMF device. Then, the base station transmits the PRS to the terminal. The terminal performs CIR measurements based on the received PRS.

[0208] Step 1a above corresponds to step S101.

[0209] The remaining content in the second solid box represents steps 2a to 4a.

[0210] Step 2a: Phase mismatch elimination. Specifically, the terminal performs phase mismatch elimination to achieve phase alignment. Step 2a corresponds to steps S102-S104 above.

[0211] Step 3a: Location. Specifically, the terminal runs an AI / ML direct location model, and the location information output by the AI / ML direct location model is the terminal's location. This corresponds to the aforementioned step S105.

[0212] Step 4a: Mismatch Elimination Monitoring. Specifically, this is monitored by the terminal, corresponding to the aforementioned steps S108-S110.

[0213] Referring to Figure 9, which is a flowchart illustrating the sixth positioning method provided in this application embodiment, applicable to the aforementioned scenario 2a, the terminal to be positioned in this embodiment is the first terminal, referred to simply as the terminal in Figure 9. The complete positioning process includes steps 0b-5b, a total of six steps. The second and third solid-line boxes in the figure represent two positioning processes, which are identical, differing only in that some steps in the third solid-line box are indicated by dashed lines, signifying that these steps may be omitted.

[0214] Compared to the embodiment shown in Figure 8 above, steps 0b and 0a are the same, steps 1b and 1a are the same, steps 2b and 2a are the same, and steps 4b and 4a are the same. The difference lies in step 3b and the addition of step 5b. Only steps 3b and 5b will be described below.

[0215] Step 3b: Obtaining Auxiliary Information. Specifically, the terminal runs the AI / ML indirect positioning model. The positioning information output by the AI / ML indirect positioning model is auxiliary positioning information and cannot yet determine the terminal's location. This corresponds to the aforementioned step S105. In this case, step 5b also needs to be executed.

[0216] Step 5b: Location. Specifically, the terminal sends auxiliary location information to the LMF device, which then performs the final location.

[0217] Referring to Figure 10, which is a flowchart of the third positioning method provided in the embodiment of this application, applicable to sub-scenario 1 of the aforementioned scenario 3a, in this example, the first base station measures the CIR of the channel between itself and the terminal to be located. In Figure 10, the first base station is referred to as the base station. The complete positioning process includes steps 0c-5c.

[0218] The content within the first solid box in the diagram represents step 0c: configuration. This means the LMF device sends a phase mismatch elimination configuration to the base station, implementing step S106. If no configuration anomalies occur, this step can be performed only once after positioning is initiated.

[0219] The second and third solid-line boxes in the diagram represent two identical positioning processes. The only difference is that the third solid-line box contains some steps indicated by dashed lines, signifying that these steps can be omitted. Therefore, to avoid repetition, only the steps contained in the second solid-line box will be described here.

[0220] The content within the dashed box in the second solid box in the figure represents step 1c: CIR measurement.

[0221] The specific process is as follows: The LMF device sends a positioning information request to the base station. The base station sends an SRS configuration to the terminal and a positioning information ack to the LMF device. The terminal then transmits an SRS to the base station. The base station performs CIR measurements based on the received SRS.

[0222] Step 1c above corresponds to step S101.

[0223] The remaining content in the second solid box represents steps 2c to 5c.

[0224] Step 2c: Phase mismatch elimination. Specifically, the base station performs phase mismatch elimination to achieve phase alignment. Step 2c corresponds to steps S102-S104 mentioned above.

[0225] Step 3c: Obtaining auxiliary information. Specifically, the base station runs an AI / ML indirect positioning model, and the positioning information output by the AI / ML indirect positioning model is auxiliary positioning information. This corresponds to the aforementioned step S105.

[0226] Step 4c: Mismatch Elimination Monitoring. Specifically, this is monitored by the base station, corresponding to the aforementioned steps S108-S110.

[0227] Step 5c: Positioning. Specifically, the base station sends auxiliary positioning information to the LMF device, which then performs the final positioning.

[0228] Additionally, referring to Figure 11, which is a flowchart of the seventh positioning method provided in this application embodiment, applicable to sub-scenario 2 of the aforementioned scenario 3a, the terminal to be positioned measures the CIR between itself and the first base station. In Figure 11, the first base station is referred to as the base station. The complete positioning process includes steps 0d-5d.

[0229] Compared with the embodiment shown in Figure 10 above, steps 0d and 0c are similar, steps 2d and 2c are similar, steps 3d and 3c are similar, steps 4d and 4c are similar, and steps 5d and 5c are similar. These will not be repeated here. Only step 1d, which differs significantly from step 1c, will be described here.

[0230] Step 1d: CIR measurement.

[0231] The specific process is as follows: The LMF device sends a positioning information request to the base station. The base station sends a PRS configuration to the terminal and a positioning information ack to the LMF device. Then, the base station transmits a PRS to the terminal. The terminal performs CIR measurement based on the received PRS. Finally, the terminal sends the measured CIR back to the base station.

[0232] For scenario 2b or scenario 3b, the positioning device is an LMF device. The positioning model in the LMF device processes the phase-aligned CIR to obtain the positioning information, which is directly the location information of the terminal.

[0233] Referring to Figure 12, which is a flowchart illustrating the eighth positioning method provided in this application embodiment, the terminal in Figure 12 is the terminal to be located. The terminal or base station sends a CIR to the LMF device, the LMF device performs phase mismatch elimination, and then the AI / ML direct positioning model in the LMF device directly outputs the terminal's location information, followed by mismatch elimination monitoring by the LMF.

[0234] The methods for terminals or base stations to obtain CIRs can be found above and will not be repeated here.

[0235] The complete process of the positioning device is described below with reference to Figure 13. Figure 13 is a schematic diagram of a phase alignment process provided in an embodiment of this application.

[0236] The positioning device first collects the CIR (Circuit Irregularity) data. Then, based on the first marker value in the first signaling, it selects either the "first satisfying sample method" or the "strongest sample method" to select reference samples, thus obtaining reference samples. The topmost black dot in the diagram is connected to the white origin on the left, indicating that in this embodiment, the first marker value of the first signaling indicates the selection of the first satisfying sample method. Next, based on the second marker value in the first signaling, it selects either the "mean method" or the "minimum phase angle method" to calculate the reference phase, thus obtaining the reference phase. The second black dot in the diagram is connected to the white origin on the left, indicating that in this embodiment, the second marker value of the first signaling indicates the selection of the mean method. Phase alignment is then performed, and phase alignment monitoring is conducted.

[0237] To demonstrate the positive effect of the phase alignment method provided in this application compared with the phase alignment method in related technologies, the phase alignment effect is verified in the following ways in this application.

[0238] First, 1000 channel measurements were performed on the time-invariant channel to obtain 1000 CIRs. Then, the obtained CIRs were phase-aligned using five different phase alignment methods. In this verification scenario, the signal bandwidth was 100MHz, and the CIR measurement time interval was 0.5ns.

[0239] See Table 1 for the phase alignment method table provided in the embodiments of this application.

[0240] Table 1

[0241] In this case (example) 1, phase alignment is performed using algorithms from relevant technologies. Case 2 uses the strongest sample method for reference sample selection and the mean method for reference phase calculation. Case 3 uses the strongest sample method for reference sample selection and the minimum phase angle method for reference phase calculation. Case 4 uses the first-satisfied sample method for reference sample selection and the mean method for reference phase calculation. Case 5 uses the first-satisfied sample method for reference sample selection and the minimum phase angle method for reference phase calculation.

[0242] The first sampling method uses a ratio of amplitude threshold to noise standard deviation of 10, and the number of reference samples is 10. The minimum interval between candidate angles in the minimum phase angle method is also specified.

[0243] After phase calibration, the first group of CIRs was selected as the benchmark. The similarity between the other 999 phase-aligned CIRs and the benchmark CIR was calculated to evaluate the case's performance. Each pair of CIRs with calculated similarity forms a CIR group. The similarity of CIRs is evaluated using the imaginary part of the correlation coefficient, denoted as h for the two groups of CIRs. 1，jh 2，j Let j = 1, 2, ..., J, where J is the total number of CIR groups. The imaginary part of the correlation coefficient between the two is r. 1，2 Defined as:

[0244] Where I(·)I represents the absolute value of the imaginary number, and (·)* represents the conjugate of the imaginary number.

[0245] As can be seen, if the phase alignment of the samples in two sets of CIRs is better and the similarity is higher, the imaginary part of the correlation coefficient should tend to a real number. Therefore, the smaller the imaginary part of the correlation coefficient, the higher the phase alignment effect.

[0246] For the above five cases, see Figure 14, which is a schematic diagram of a verification result provided by an embodiment of this application.

[0247] The horizontal axis in the graph represents SNR (Signal to Noise Radio), which is defined as the ratio of total CIR power to noise power. The vertical axis represents the imaginary part of the correlation coefficient.

[0248] Taking the SNR of 10dB in the figure as the baseline, the curves at the SNR of 10dB in the figure correspond to case1, case4, case2, case5, and case3 from top to bottom.

[0249] As can be seen, compared with Case 1, which uses related technologies for phase alignment, the imaginary part of the correlation coefficient of all phase alignment methods provided in this application embodiment is lower. In other words, the phase alignment effect of all phase alignment methods provided in this application embodiment is superior to that of related technologies.

[0250] Furthermore, compared to the first-satisfaction sampling method, the strongest sampling method can achieve a lower imaginary part of the correlation coefficient. However, the difference between the two methods decreases as the SNR increases. Therefore, when the SNR is low, the strongest sampling method can be used to select reference samples to ensure phase alignment. However, in scenarios with high SNR or where it is desirable to retain the phase information of the sample with the highest amplitude, the first-satisfaction sampling method can also be chosen for reference sample selection.

[0251] Furthermore, compared to the mean method, the minimum phase angle method yields a lower imaginary part of the correlation coefficient. However, the difference between the two methods also decreases as the SNR increases. Therefore, when the SNR is low, the minimum phase angle method can be used to calculate the reference phase to ensure phase alignment. However, in scenarios with high SNR or where it is desirable to reduce computational complexity, the mean method can also be chosen for reference phase calculation.

[0252] Corresponding to the aforementioned positioning method applied to positioning devices, this application embodiment also provides a positioning device, as shown in FIG15, the positioning device comprising:

[0253] Processor 1501;

[0254] Transceiver 1504;

[0255] A machine-readable storage medium 1502 stores machine-executable instructions that can be executed by the processor 1501; the machine-executable instructions cause the processor 1501 to perform the following steps:

[0256] The channel impulse response (CIR) of the channel between the terminal to be located and the base station is obtained, and the CIR includes multiple samples.

[0257] Based on the amplitude of each of the plurality of sample points, a reference sample point is selected from the plurality of sample points, wherein the amplitude of the reference sample point is greater than a preset standard.

[0258] Calculate the reference phase based on the reference sample points;

[0259] Based on the reference phase, the multiple sample points are phase aligned to obtain the phase-aligned CIR;

[0260] Input the phase-aligned CIR into the positioning model and obtain the positioning information output by the positioning model.

[0261] As shown in Figure 15, the network device may also include a communication bus 1503. The processor 1501, machine-readable storage medium 1502, and transceiver 1504 communicate with each other via the communication bus 1503. The communication bus 1503 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus 1503 can be divided into an address bus, a data bus, a control bus, etc.

[0262] Transceiver 1504 can be a wireless communication module. Under the control of processor 1501, transceiver 1504 interacts with other devices for data exchange.

[0263] Machine-readable storage medium 1502 may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Alternatively, machine-readable storage medium 1502 may also be at least one storage device located remotely from the aforementioned processor.

[0264] Processor 1501 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0265] As can be seen from the above, in the solution provided by this application embodiment, after acquiring the CIR, the positioning device selects suitable reference samples that match the actual amplitude of the samples in the CIR. Then, it calculates the reference phase based on the suitable reference samples. Finally, it performs phase alignment on each sample based on the reference phase. Since the reference samples are not fixed-position samples, but rather samples with amplitudes greater than a preset standard are selected based on the actual amplitude of the samples in the CIR, the selected reference samples are more closely matched to the actual situation of the CIR, with larger amplitudes and lower phase noise. Phase alignment on this basis introduces less phase noise into the phase-aligned CIR, making the phase-aligned CIR more accurate. It also eliminates the problem of random initial phase mismatch in the CIR, thereby improving the positioning accuracy of the positioning model.

[0266] In one embodiment of this application, the step of selecting a reference sample point from the plurality of sample points based on the amplitude of each sample point specifically includes:

[0267] Using either the first algorithm or the second algorithm, a reference sample point is selected from the plurality of sample points based on the magnitude of each sample point.

[0268] The first algorithm selects the sample point with the largest amplitude from multiple sample points as the reference sample point, and the second algorithm selects the first sample point with an amplitude threshold higher than the amplitude threshold from the multiple sample points as the reference sample point. The amplitude threshold is a preset multiple of the noise standard deviation of the CIR.

[0269] The calculation of the reference phase based on the reference sample points includes:

[0270] The reference phase is calculated based on the reference samples using either the third or fourth algorithm.

[0271] The third algorithm is as follows: calculate the average phase of each sample point in the sample point set as a reference phase, wherein the sample point set includes multiple consecutive sample points starting from the reference sample point;

[0272] The fourth algorithm is as follows: For each of the multiple candidate angles, calculate the sum of the imaginary parts of the phase of the sample points in the sample point set after rotating the candidate angle, and select the candidate angle that minimizes the sum of the imaginary parts as the reference phase.

[0273] In one embodiment of this application, when the positioning device is the terminal or the base station, before acquiring the channel impulse response (CIR) of the channel between the terminal to be located and the base station, the machine-executable instructions further cause the processor 1501 to perform the following steps:

[0274] The device receives a first signaling message sent by the Position Management Function (LMF) device. The first signaling message includes a first marker value and a second marker value. The first marker value represents an algorithm for selecting the reference sample point, and the second marker value represents an algorithm for calculating the reference phase.

[0275] The step of selecting a reference sample point from the plurality of sample points based on the amplitude of each sample point includes:

[0276] Using the algorithm represented by the first marker value, a reference sample point is selected from the plurality of sample points based on the magnitude of each sample point among the plurality of sample points;

[0277] The calculation of the reference phase based on the reference sample points includes:

[0278] The algorithm, represented by the second marker value, calculates the reference phase based on the reference sample points.

[0279] As can be seen from the above, in the embodiments of this application, the LMF device can control the algorithm used by the positioning device when selecting reference sample points and calculating reference phase through the first signaling, thereby controlling the phase alignment process of the positioning device.

[0280] In one embodiment of this application, the first signaling further includes a first parameter, which represents the number of samples used to calculate the reference phase;

[0281] When the first flag value represents the second algorithm, the first signaling further includes a second parameter, which is used to represent the preset multiple;

[0282] When the second marker value represents the fourth algorithm, the first signaling also includes a third parameter, which is used to represent the minimum interval between each alternative angle.

[0283] In one embodiment of this application, the algorithm represented by the first marker value is one of the algorithms supported by the positioning device for selecting the reference sample points; the algorithm represented by the second marker value is one of the algorithms supported by the positioning device for calculating the reference phase.

[0284] Prior to receiving the first signaling from the LMF device, the machine-executable instructions also cause the processor 1501 to perform the following steps:

[0285] Send a second signaling message to the LMF device;

[0286] The second signaling includes a fourth parameter and a fifth parameter. The fourth parameter represents the algorithm supported by the positioning device for selecting the reference sample point, and the fifth parameter represents the algorithm supported by the positioning device for calculating the reference phase.

[0287] As can be seen from the above, before the LMF device sends the first signaling to the positioning device, the positioning device can also send a second signaling to the LMF device to notify the LMF device of the positioning device's ability to select reference samples and calculate reference phase, so that the LMF device can issue the first signaling according to the positioning device's capabilities.

[0288] In one embodiment of this application, the second signaling further includes a sixth parameter, which represents the range of values ​​for the number of samples used to calculate the reference phase;

[0289] If the algorithm represented by the fourth parameter includes the second algorithm, the second signaling also includes the seventh parameter;

[0290] The seventh parameter is used to represent the range of values ​​for the preset multiple;

[0291] If the algorithm represented by the fifth parameter includes the fourth algorithm, the second signaling also includes an eighth parameter;

[0292] The eighth parameter is used to represent the range of values ​​for the interval between each candidate angle.

[0293] In one embodiment of this application, after inputting the phase-aligned CIR into the positioning model and obtaining the positioning information output by the positioning model, the machine-executable instructions further cause the processor 1501 to perform the following steps:

[0294] Based on the obtained positioning information, predict the confidence region in which the terminal should be located at the future target time;

[0295] After reaching the target time, the location information of the target time is obtained to determine the actual location of the terminal at the target time;

[0296] Determine whether the actual location corresponding to the current target time is within the current confidence region;

[0297] If the cumulative number of times the actual location is determined to be outside the confidence region has not reached the preset number, then return to the step of obtaining the channel impulse response (CIR) of the channel between the terminal to be located and the base station.

[0298] As can be seen from the above, the solution provided in this application can monitor phase alignment and only continue phase alignment processing when the phase alignment is accurate, thereby avoiding the waste of computing resources.

[0299] In one embodiment of this application, the positioning device is the terminal, the base station, or the LMF device.

[0300] Corresponding to the aforementioned positioning method applied to positioning devices, this application also provides a positioning device applied to positioning devices.

[0301] Referring to Figure 16, which is a schematic diagram of a positioning device provided in an embodiment of this application, applied to a positioning equipment, the device includes:

[0302] CIR acquisition module 1601 is used to acquire the channel impulse response (CIR) of the channel between the terminal to be located and the base station, wherein the CIR includes multiple sample points;

[0303] The sample point selection module 1602 is used to select a reference sample point from the plurality of sample points based on the amplitude of each sample point among the plurality of sample points, wherein the amplitude of the reference sample point is greater than a preset standard.

[0304] The phase calculation module 1603 is used to calculate the reference phase based on the reference sample points;

[0305] Phase alignment module 1604 is used to perform phase alignment on the plurality of sample points based on the reference phase to obtain a phase-aligned CIR;

[0306] The positioning information acquisition module 1605 is used to input the phase-aligned CIR into the positioning model and acquire the positioning information output by the positioning model.

[0307] As can be seen from the above, in the solution provided by this application embodiment, after acquiring the CIR, the positioning device selects suitable reference samples that match the actual amplitude of the samples in the CIR. Then, it calculates the reference phase based on the suitable reference samples. Finally, it performs phase alignment on each sample based on the reference phase. Since the reference samples are not fixed-position samples, but rather samples with amplitudes greater than a preset standard are selected based on the actual amplitude of the samples in the CIR, the selected reference samples are more closely matched to the actual situation of the CIR, with larger amplitudes and lower phase noise. Phase alignment on this basis introduces less phase noise into the phase-aligned CIR, making the phase-aligned CIR more accurate. It also eliminates the problem of random initial phase mismatch in the CIR, thereby improving the positioning accuracy of the positioning model.

[0308] In one embodiment of this application, the sample selection module 1602 is specifically used for:

[0309] Using either the first algorithm or the second algorithm, a reference sample point is selected from the plurality of sample points based on the magnitude of each sample point.

[0310] The first algorithm selects the sample point with the largest amplitude from multiple sample points as the reference sample point, and the second algorithm selects the first sample point with an amplitude threshold higher than the amplitude threshold from the multiple sample points as the reference sample point. The amplitude threshold is a preset multiple of the noise standard deviation of the CIR.

[0311] The phase calculation module 1603 is specifically used for:

[0312] The reference phase is calculated based on the reference samples using either the third or fourth algorithm.

[0313] The third algorithm is as follows: calculate the average phase of each sample point in the sample point set as a reference phase, wherein the sample point set includes multiple consecutive sample points starting from the reference sample point;

[0314] The fourth algorithm is as follows: For each of the multiple candidate angles, calculate the sum of the imaginary parts of the phase of the sample points in the sample point set after rotating the candidate angle, and select the candidate angle that minimizes the sum of the imaginary parts as the reference phase.

[0315] In one embodiment of this application, the apparatus further includes:

[0316] The signaling receiving module is used to receive first signaling sent by the positioning management function (LMF) device. The first signaling includes a first marker value and a second marker value. The first marker value represents an algorithm for selecting the reference sample point, and the second marker value represents an algorithm for calculating the reference phase.

[0317] The sample point selection module 1602 is specifically used for:

[0318] Using the algorithm represented by the first marker value, a reference sample point is selected from the plurality of sample points based on the magnitude of each sample point among the plurality of sample points;

[0319] The phase calculation module 1603 is specifically used for:

[0320] The algorithm, represented by the second marker value, calculates the reference phase based on the reference sample points.

[0321] As can be seen from the above, in the embodiments of this application, the LMF device can control the algorithm used by the positioning device when selecting reference sample points and calculating reference phase through the first signaling, thereby controlling the phase alignment process of the positioning device.

[0322] In one embodiment of this application, the first signaling further includes a first parameter, which represents the number of samples used to calculate the reference phase;

[0323] When the first flag value represents the second algorithm, the first signaling further includes a second parameter, which is used to represent the preset multiple;

[0324] When the second marker value represents the fourth algorithm, the first signaling also includes a third parameter, which is used to represent the minimum interval between each alternative angle.

[0325] In one embodiment of this application, the algorithm represented by the first marker value is one of the algorithms supported by the positioning device for selecting the reference sample points; the algorithm represented by the second marker value is one of the algorithms supported by the positioning device for calculating the reference phase.

[0326] The device further includes:

[0327] The signaling sending module is used to send a second signaling message to the LMF device;

[0328] The second signaling includes a fourth parameter and a fifth parameter. The fourth parameter represents the algorithm supported by the positioning device for selecting the reference sample point, and the fifth parameter represents the algorithm supported by the positioning device for calculating the reference phase.

[0329] As can be seen from the above, before the LMF device sends the first signaling to the positioning device, the positioning device can also send a second signaling to the LMF device to notify the LMF device of the positioning device's ability to select reference samples and calculate reference phase, so that the LMF device can issue the first signaling according to the positioning device's capabilities.

[0330] In one embodiment of this application, the second signaling further includes a sixth parameter, which represents the range of values ​​for the number of samples used to calculate the reference phase;

[0331] If the algorithm represented by the fourth parameter includes the second algorithm, the second signaling also includes the seventh parameter;

[0332] The seventh parameter is used to represent the range of values ​​for the preset multiple;

[0333] If the algorithm represented by the fifth parameter includes the fourth algorithm, the second signaling also includes an eighth parameter;

[0334] The eighth parameter is used to represent the range of values ​​for the interval between each candidate angle.

[0335] In one embodiment of this application, the apparatus further includes:

[0336] The region prediction module is used to predict the confidence region where the terminal should be located at a future target time based on the obtained positioning information.

[0337] The actual location determination module is used to determine the actual location of the terminal at the target time by obtaining the positioning information of the target time after arriving at the target time.

[0338] The location determination module is used to determine whether the actual location of the target at the current time is within the current confidence region;

[0339] If the cumulative number of times the actual location is determined to be outside the confidence region has not reached the preset number, then the process will return to trigger the execution of the CIR acquisition module.

[0340] As can be seen from the above, the solution provided in this application can monitor phase alignment and only continue phase alignment processing when the phase alignment is accurate, thereby avoiding the waste of computing resources.

[0341] In one embodiment of this application, the positioning device is the terminal, the base station, or the LMF device.

[0342] Based on the same inventive concept, according to the positioning method provided in the above embodiments of this application, a machine-readable storage medium stores machine-executable instructions, which, when called and executed by a processor, cause the processor to: implement the steps of any positioning method applied to a positioning device.

[0343] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to perform the steps of any of the positioning methods applied to a positioning device in the above embodiments.

[0344] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0345] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0346] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, computer-readable storage media, and computer program products are basically similar to the method embodiments, and therefore the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0347] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A positioning method, characterized in that, Applied to a positioning device, the method includes: The channel impulse response (CIR) of the channel between the terminal to be located and the base station is obtained, and the CIR includes multiple samples. Based on the amplitude of each of the plurality of sample points, a reference sample point is selected from the plurality of sample points, wherein the amplitude of the reference sample point is greater than a preset standard. Calculate the reference phase based on the reference sample points; Based on the reference phase, the multiple sample points are phase aligned to obtain the phase-aligned CIR; Input the phase-aligned CIR into the positioning model and obtain the positioning information output by the positioning model.

2. The method according to claim 1, characterized in that, The step of selecting a reference sample point from the plurality of sample points based on the amplitude of each sample point includes: Using either the first or the second algorithm, a reference sample point is selected from the plurality of sample points based on the magnitude of each sample point. The first algorithm selects the sample point with the largest amplitude from multiple sample points as the reference sample point, and the second algorithm selects the first sample point with an amplitude threshold higher than the amplitude threshold from the multiple sample points as the reference sample point. The amplitude threshold is a preset multiple of the noise standard deviation of the CIR. The calculation of the reference phase based on the reference sample points includes: The reference phase is calculated based on the reference samples using either the third or fourth algorithm. The third algorithm is as follows: calculate the average phase of each sample point in the sample point set as a reference phase, wherein the sample point set includes multiple consecutive sample points starting from the reference sample point; The fourth algorithm is as follows: For each of the multiple candidate angles, calculate the sum of the imaginary parts of the phase of the sample points in the sample point set after rotating the candidate angle, and select the candidate angle that minimizes the sum of the imaginary parts as the reference phase.

3. The method according to claim 2, characterized in that, When the positioning device is a first terminal or a first base station, before acquiring the channel impulse response (CIR) of the channel between the terminal to be located and the base station, the method further includes: The device receives a first signaling message sent by the Position Management Function (LMF) device. The first signaling message includes a first marker value and a second marker value. The first marker value represents an algorithm for selecting the reference sample point, and the second marker value represents an algorithm for calculating the reference phase. The step of selecting a reference sample point from the plurality of sample points based on the amplitude of each sample point includes: Using the algorithm represented by the first marker value, a reference sample point is selected from the plurality of sample points based on the magnitude of each sample point among the plurality of sample points; The calculation of the reference phase based on the reference sample points includes: The algorithm, represented by the second marker value, calculates the reference phase based on the reference sample points.

4. The method according to claim 3, characterized in that, The first signaling also includes a first parameter, which represents the number of samples used to calculate the reference phase; When the first flag value represents the second algorithm, the first signaling further includes a second parameter, which is used to represent the preset multiple; When the second marker value represents the fourth algorithm, the first signaling also includes a third parameter, which is used to represent the minimum interval between each alternative angle.

5. The method according to claim 3, characterized in that, The algorithm represented by the first marker value is one of the algorithms supported by the positioning device for selecting the reference sample points; the algorithm represented by the second marker value is one of the algorithms supported by the positioning device for calculating the reference phase. Before the first signaling sent by the receiving LMF device, the following is also included: Send a second signaling message to the LMF device; The second signaling includes a fourth parameter and a fifth parameter. The fourth parameter represents the algorithm supported by the positioning device for selecting the reference sample point, and the fifth parameter represents the algorithm supported by the positioning device for calculating the reference phase.

6. The method according to claim 5, characterized in that, The second signaling also includes a sixth parameter, which represents the range of values ​​for the number of samples used to calculate the reference phase; If the algorithm represented by the fourth parameter includes the second algorithm, the second signaling also includes the seventh parameter; The seventh parameter is used to represent the range of values ​​for the preset multiple; If the algorithm represented by the fifth parameter includes the fourth algorithm, the second signaling also includes an eighth parameter; The eighth parameter is used to represent the range of values ​​for the interval between each candidate angle.

7. The method according to any one of claims 1-6, characterized in that, After inputting the phase-aligned CIR into the positioning model and obtaining the positioning information output by the positioning model, the method further includes: Based on the obtained positioning information, predict the confidence region in which the terminal should be located at the future target time; After reaching the target time, the location information of the target time is obtained to determine the actual location of the terminal at the target time; Determine whether the actual location corresponding to the current target time is within the current confidence region; If the cumulative number of times the actual location is determined to be outside the confidence region has not reached the preset number, then return to the step of obtaining the channel impulse response (CIR) of the channel between the terminal to be located and the base station.

8. The method according to claim 1 or 2, characterized in that, The positioning device is a first terminal, a first base station, or an LMF device.

9. A positioning device, characterized in that, The positioning device includes: processor; transceiver; A machine-readable storage medium storing machine-executable instructions that can be executed by the processor; the machine-executable instructions cause the processor to perform the following steps: The channel impulse response (CIR) of the channel between the terminal to be located and the base station is obtained, and the CIR includes multiple samples. Based on the amplitude of each of the plurality of sample points, a reference sample point is selected from the plurality of sample points, wherein the amplitude of the reference sample point is greater than a preset standard. Calculate the reference phase based on the reference sample points; Based on the reference phase, the multiple sample points are phase aligned to obtain the phase-aligned CIR; Input the phase-aligned CIR into the positioning model and obtain the positioning information output by the positioning model.

10. The positioning device according to claim 9, characterized in that, The step of selecting a reference sample point from the plurality of sample points based on the amplitude of each sample point specifically includes: Using either the first or the second algorithm, a reference sample point is selected from the plurality of sample points based on the magnitude of each sample point. The first algorithm selects the sample point with the largest amplitude from multiple sample points as the reference sample point, and the second algorithm selects the first sample point with an amplitude threshold higher than the amplitude threshold from the multiple sample points as the reference sample point. The amplitude threshold is a preset multiple of the noise standard deviation of the CIR. The calculation of the reference phase based on the reference sample points includes: The reference phase is calculated based on the reference samples using either the third or fourth algorithm. The third algorithm is as follows: calculate the average phase of each sample point in the sample point set as a reference phase, wherein the sample point set includes multiple consecutive sample points starting from the reference sample point; The fourth algorithm is as follows: For each of the multiple candidate angles, calculate the sum of the imaginary parts of the phase of the sample points in the sample point set after rotating the candidate angle, and select the candidate angle that minimizes the sum of the imaginary parts as the reference phase.

11. The positioning device according to claim 10, characterized in that, When the positioning device is a first terminal or a first base station, before acquiring the channel impulse response (CIR) of the channel between the terminal to be located and the base station, the machine-executable instructions further cause the processor to perform the following steps: The system receives a first signaling message from a Location Management Function (LMF) device, the first signaling message including a first tag value and a second tag value. The first marker value represents the algorithm used to select the reference sample points, and the second marker value represents the algorithm used to calculate the reference phase; The step of selecting a reference sample point from the plurality of sample points based on the amplitude of each sample point includes: Using the algorithm represented by the first marker value, a reference sample point is selected from the plurality of sample points based on the magnitude of each sample point among the plurality of sample points; The calculation of the reference phase based on the reference sample points includes: The algorithm, represented by the second marker value, calculates the reference phase based on the reference sample points.

12. The positioning device according to claim 11, characterized in that, The first signaling also includes a first parameter, which represents the number of samples used to calculate the reference phase; When the first flag value represents the second algorithm, the first signaling further includes a second parameter, which is used to represent the preset multiple; When the second marker value represents the fourth algorithm, the first signaling also includes a third parameter, which is used to represent the minimum interval between each alternative angle.

13. The positioning device according to claim 11, characterized in that, The algorithm represented by the first marker value is one of the algorithms supported by the positioning device for selecting the reference sample points; the algorithm represented by the second marker value is one of the algorithms supported by the positioning device for calculating the reference phase. Before receiving the first signaling from the LMF device, the machine-executable instructions also cause the processor to perform the following steps: Send a second signaling message to the LMF device; The second signaling includes a fourth parameter and a fifth parameter. The fourth parameter represents the algorithm supported by the positioning device for selecting the reference sample point, and the fifth parameter represents the algorithm supported by the positioning device for calculating the reference phase.

14. The positioning device according to claim 13, characterized in that, The second signaling also includes a sixth parameter, which represents the range of values ​​for the number of samples used to calculate the reference phase; If the algorithm represented by the fourth parameter includes the second algorithm, the second signaling also includes the seventh parameter; The seventh parameter is used to represent the range of values ​​for the preset multiple; If the algorithm represented by the fifth parameter includes the fourth algorithm, the second signaling also includes an eighth parameter; The eighth parameter is used to represent the range of values ​​for the interval between each candidate angle.

15. The positioning device according to any one of claims 9-14, characterized in that, After inputting the phase-aligned CIR into the positioning model and obtaining the positioning information output by the positioning model, the machine-executable instructions further cause the processor to perform the following steps: Based on the obtained positioning information, predict the confidence region in which the terminal should be located at the future target time; After reaching the target time, the location information of the target time is obtained to determine the actual location of the terminal at the target time; Determine whether the actual location corresponding to the current target time is within the current confidence region; If the cumulative number of times the actual location is determined to be outside the confidence region has not reached the preset number, then return to the step of obtaining the channel impulse response (CIR) of the channel between the terminal to be located and the base station.

16. The positioning device according to claim 9 or 10, characterized in that, The positioning device is a first terminal, a first base station, or an LMF device.

17. A positioning device, characterized in that, Applied to a positioning device, the device includes: The CIR acquisition module is used to acquire the channel impulse response (CIR) of the channel between the terminal to be located and the base station, wherein the CIR includes multiple sample points; The sample point selection module is used to select a reference sample point from the plurality of sample points based on the amplitude of each sample point among the plurality of sample points, wherein the amplitude of the reference sample point is greater than a preset standard; The phase calculation module is used to calculate the reference phase based on the reference sample points; A phase alignment module is used to perform phase alignment on the plurality of sample points based on the reference phase to obtain a phase-aligned CIR. The positioning information acquisition module is used to input the phase-aligned CIR into the positioning model and acquire the positioning information output by the positioning model.

18. The apparatus according to claim 17, characterized in that, The sample point selection module is specifically used for: Using either the first or the second algorithm, a reference sample point is selected from the plurality of sample points based on the magnitude of each sample point. The first algorithm selects the sample point with the largest amplitude from multiple sample points as the reference sample point, and the second algorithm selects the first sample point with an amplitude threshold higher than the amplitude threshold from the multiple sample points as the reference sample point. The amplitude threshold is a preset multiple of the noise standard deviation of the CIR. The phase calculation module is specifically used for: The reference phase is calculated based on the reference samples using either the third or fourth algorithm. The third algorithm is as follows: calculate the average phase of each sample point in the sample point set as a reference phase, wherein the sample point set includes multiple consecutive sample points starting from the reference sample point; The fourth algorithm is as follows: For each of the multiple candidate angles, calculate the sum of the imaginary parts of the phase of the sample points in the sample point set after rotating the candidate angle, and select the candidate angle that minimizes the sum of the imaginary parts as the reference phase.

19. The apparatus according to claim 18, characterized in that, The device further includes: The signaling receiving module is used to receive first signaling sent by the positioning management function (LMF) device. The first signaling includes a first marker value and a second marker value. The first marker value represents an algorithm for selecting the reference sample point, and the second marker value represents an algorithm for calculating the reference phase. The sample point selection module is specifically used for: Using the algorithm represented by the first marker value, a reference sample point is selected from the plurality of sample points based on the magnitude of each sample point among the plurality of sample points; The phase calculation module is specifically used for: The algorithm, represented by the second marker value, calculates the reference phase based on the reference sample points.

20. The apparatus according to claim 19, characterized in that, The first signaling also includes a first parameter, which represents the number of samples used to calculate the reference phase; When the first flag value represents the second algorithm, the first signaling further includes a second parameter, which is used to represent the preset multiple; When the second marker value represents the fourth algorithm, the first signaling also includes a third parameter, which is used to represent the minimum interval between each alternative angle.

21. The apparatus according to claim 19, characterized in that, The algorithm represented by the first marker value is one of the algorithms supported by the positioning device for selecting the reference sample points; the algorithm represented by the second marker value is one of the algorithms supported by the positioning device for calculating the reference phase. The device further includes: The signaling sending module is used to send a second signaling message to the LMF device; The second signaling includes a fourth parameter and a fifth parameter. The fourth parameter represents the algorithm supported by the positioning device for selecting the reference sample point, and the fifth parameter represents the algorithm supported by the positioning device for calculating the reference phase.

22. The apparatus according to claim 21, characterized in that, The second signaling also includes a sixth parameter, which represents the range of values ​​for the number of samples used to calculate the reference phase; If the algorithm represented by the fourth parameter includes the second algorithm, the second signaling also includes the seventh parameter; The seventh parameter is used to represent the range of values ​​for the preset multiple; If the algorithm represented by the fifth parameter includes the fourth algorithm, the second signaling also includes an eighth parameter; The eighth parameter is used to represent the range of values ​​for the interval between each candidate angle.

23. The apparatus according to any one of claims 17-22, characterized in that, The device further includes: The region prediction module is used to predict the confidence region where the terminal should be located at a future target time based on the obtained positioning information. The actual location determination module is used to determine the actual location of the terminal at the target time by obtaining the positioning information of the target time after arriving at the target time. The location determination module is used to determine whether the actual location of the target at the current time is within the current confidence region; If the cumulative number of times the actual location is determined to be outside the confidence region has not reached the preset number, then the process will return to trigger the execution of the CIR acquisition module.

24. The apparatus according to claim 17 or 18, characterized in that, The positioning device is a first terminal, a first base station, or an LMF device.

25. A machine-readable storage medium, characterized in that, The device stores machine-executable instructions that, when invoked and executed by a processor, cause the processor to: implement the method of any one of claims 1-8.

26. A computer program product, characterized in that, The computer program product causes the processor to implement the method of any one of claims 1-8.

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