Wireless positioning method and device, medium and product

Abstract

The invention discloses a wireless positioning method and device, a medium and a product, and relates to the field of wireless positioning.The method comprises the steps that whether a propagation path at the current moment is a sight distance path or not is judged according to obtained real-time monitoring data of a positioning base station; if yes, determining the first arrival path of the sight distance path state and the corresponding first arrival path time delay, and determining the distance between the positioning base station and the terminal and the positioning coordinate of the terminal; if not, determining a first arrival path of the non-line-of-sight path state and a corresponding first arrival path time delay based on local cognitive feedback; judging whether the first arrival path of the non-line-of-sight path state determined based on local cognitive feedback has a problem or not; if not, determining the distance between the positioning base station and the terminal and the positioning coordinate of the terminal; and if yes, determining an estimated first arrival path of the non-line-of-sight path state at the current moment and a corresponding first arrival path time delay estimation value based on cognitive feedback of the cloud, and determining a distance between the positioning base station and the terminal and a positioning coordinate of the terminal. The positioning error can be reduced.

Description

Technical Field

[0001] The present application relates to the field of wireless positioning technology, and in particular to a wireless positioning method, device, medium and product. Background Art

[0002] Wireless positioning signal measurement mainly includes power measurement, time measurement and angle measurement. Power measurement includes triangulation positioning and fingerprint positioning, time measurement includes positioning technology based on time of arrival (TOA) and time difference of arrival (TDOA), and angle measurement includes positioning technology based on angle of arrival (AOA) and angle of departure (AOD).

[0003] However, the existing technology has the following disadvantages: (1) If the scene has a large area and severe non-line-of-sight conditions, or if the scene has a large area of ​​strong metal shielding, the ranging error of the positioning system will reach the meter level, and the positioning error of the terminal movement trajectory will also deteriorate to the meter level or positioning discontinuity will occur; (2) The positioning system cannot provide real-time feedback and processing based on the time-varying channel status to minimize the positioning error and ensure the terminal service experience. Summary of the invention

[0004] The purpose of this application is to provide a wireless positioning method, device, medium and product, which can effectively identify the first-reach path and obtain the first-reach path delay through a two-layer cognitive feedback mechanism based on local cognitive feedback and cloud-based cognitive feedback, thereby reducing positioning errors and ensuring terminal service experience.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a wireless positioning method, the wireless positioning method comprising:

[0007] Obtain real-time monitoring data of positioning base stations.

[0008] According to the real-time monitoring data of the positioning base station, it is determined whether the propagation path at the current moment is a line-of-sight path to obtain a first determination result.

[0009] If the first judgment result is yes, then determine the first arrival path of the line-of-sight path state and the corresponding first arrival path delay; the first arrival path of the line-of-sight path state is the strongest path between the transmitter and the receiver.

[0010] Based on the first arrival path delay of the line-of-sight path state, the distance between the positioning base station and the terminal is determined, and the positioning coordinates of the terminal are obtained by solving the positioning equation; the distance is the product of the first arrival path delay and the propagation speed.

[0011] If the first judgment result is no, the first-reaching path and the corresponding first-reaching path delay of the non-line-of-sight path state are determined based on local cognitive feedback; the local cognitive feedback is based on the channel detection result of the base station; the channel detection result based on the base station includes: key indicators and direct path mutation conditions.

[0012] It is determined whether there is a problem with the first path of the non-line-of-sight path state determined based on the local cognitive feedback, and a second determination result is obtained.

[0013] If the second judgment result is no, the distance between the positioning base station and the terminal is determined based on the first arrival path delay of the non-line-of-sight path state, and the positioning coordinates of the terminal are obtained by solving the positioning equation.

[0014] If the second judgment result is yes, the estimated first-reach path and the corresponding first-reach path delay estimate of the non-line-of-sight path state at the current moment are determined based on the cloud-based cognitive feedback; the cloud-based cognitive feedback is based on the cloud combined with the global cognition of the digital twin map and the wireless environment map.

[0015] Based on the estimated value of the first-arrival path delay of the non-line-of-sight path at the current moment, the distance between the positioning base station and the terminal is determined, and the positioning coordinates of the terminal are obtained by solving the positioning equation.

[0016] In a second aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the wireless positioning method described above.

[0017] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which implements the wireless positioning method described above when executed by a processor.

[0018] In a fourth aspect, the present application provides a computer program product, including a computer program, which implements the wireless positioning method described above when executed by a processor.

[0019] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0020] The present application provides a wireless positioning method, device, medium and product. First, real-time monitoring data of a positioning base station is obtained; according to the real-time monitoring data of the positioning base station, whether the propagation path at the current moment is a line-of-sight path is determined to obtain a first judgment result; if the first judgment result is yes, the first arrival path of the line-of-sight path state and the corresponding first arrival path delay are determined; the first arrival path of the line-of-sight path state is the strongest path between the transmitter and the receiver; based on the first arrival path delay of the line-of-sight path state, the distance between the positioning base station and the terminal is determined, and the positioning coordinates of the terminal are obtained by solving the positioning equation; the distance is the product of the first arrival path delay and the propagation speed; if the first judgment result is no, the first arrival path of the non-line-of-sight path state and the corresponding first arrival path delay are determined based on local cognitive feedback; the local cognitive feedback is based on the channel detection result of the base station to provide feedback; The base station-based channel detection result includes: key indicators and direct path mutation conditions; secondly, determine whether there is a problem with the first path of the non-line-of-sight path state determined based on local cognitive feedback, and obtain a second judgment result; if the second judgment result is no, then based on the first path delay of the non-line-of-sight path state, determine the distance between the positioning base station and the terminal, and obtain the positioning coordinates of the terminal by solving the positioning equation; if the second judgment result is yes, then determine the estimated first path of the non-line-of-sight path state at the current moment and the corresponding first path delay estimate based on the cloud-based cognitive feedback; the cloud-based cognitive feedback is based on the cloud combined with the global cognition of the digital twin map and the wireless environment map to provide feedback; based on the first path delay estimate of the non-line-of-sight path at the current moment, determine the distance between the positioning base station and the terminal, and obtain the positioning coordinates of the terminal by solving the positioning equation. The method proposed in this application can effectively identify the first-reach path and obtain the first-reach path delay through a two-layer cognitive feedback mechanism based on local cognitive feedback and cloud-based cognitive feedback in a complex electromagnetic environment, especially in severe non-line-of-sight propagation conditions or multi-metal shielding environments; at the same time, it can perform real-time processing and feedback based on the time-varying channel state of the complex electromagnetic environment to minimize the first-reach path identification error, thereby reducing the positioning error and ensuring the terminal service experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 This is a diagram of an application environment of a wireless positioning method in one embodiment of the present application.

[0023] Figure 2A flowchart of a wireless positioning method provided in one embodiment of the present application.

[0024] Figure 3 A schematic diagram of local-based cognitive feedback provided in an embodiment of the present application.

[0025] Figure 4 A schematic diagram of a feasibility analysis (non-line-of-sight propagation path condition) of adjusting a channel to identify a first-reaching path provided by an embodiment of the present application.

[0026] Figure 5 A schematic diagram of actual measurement verification (non-line-of-sight propagation path conditions) of adjusting the channel identification first-reach path provided by an embodiment of the present application.

[0027] Figure 6 A schematic diagram of cloud-based cognitive feedback provided in one embodiment of the present application.

[0028] Figure 7 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0030] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0031] The wireless positioning method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown, the terminal 102 communicates with the server 104 through a network. The data storage system can store data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the real-time monitoring data of the positioning base station to the server 104. After the server 104 receives the real-time monitoring data of the positioning base station, the server 104 determines whether the propagation path at the current moment is a line-of-sight path based on the real-time monitoring data of the positioning base station, and obtains a first judgment result; if the first judgment result is yes, the first arrival path of the line-of-sight path state and the corresponding first arrival path delay are determined; the first arrival path of the line-of-sight path state is the strongest path between the transmitter and the receiver; based on the first arrival path delay of the line-of-sight path state, the distance between the positioning base station and the terminal is determined, and the positioning coordinates of the terminal are obtained by solving the positioning equation; the distance is the product of the first arrival path delay and the propagation speed; if the first judgment result is no, the first arrival path of the non-line-of-sight path state and the corresponding first arrival path delay are determined based on local cognitive feedback; the first arrival path of the non-line-of-sight path state based on local cognitive feedback is determined based on local cognitive feedback. Feedback is based on the channel detection result of the base station; the channel detection result based on the base station includes: key indicators and direct path mutation situation; judge whether there is a problem with the first path of the non-line-of-sight path state determined based on the local cognitive feedback, and obtain the second judgment result; if the second judgment result is no, then based on the first path delay of the non-line-of-sight path state, determine the distance between the positioning base station and the terminal, and obtain the positioning coordinates of the terminal by solving the positioning equation; if the second judgment result is yes, then based on the cognitive feedback of the cloud, determine the estimated first path of the non-line-of-sight path state at the current moment and the corresponding first path delay estimate; the cognitive feedback based on the cloud is based on the cloud combined with the global cognition of the digital twin map and the wireless environment map to feedback; based on the estimated first path delay of the non-line-of-sight path at the current moment, determine the distance between the positioning base station and the terminal, and obtain the positioning coordinates of the terminal by solving the positioning equation. The server 104 can feedback the obtained distance between the positioning base station and the terminal and the positioning coordinates of the terminal to the terminal 102. In addition, in some embodiments, the wireless positioning method can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly perform wireless positioning on the real-time monitoring data of the positioning base station, or the server 104 can locate the real-time monitoring data of the base station from the data storage system and perform wireless positioning on the real-time monitoring data of the positioning base station.

[0032] The terminal 102 may be, but is not limited to, various desktop computers, laptop computers, smart phones, and tablet computers. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.

[0033] In an exemplary embodiment, Figure 2 As shown, a wireless positioning method is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps S1 to S9. Among them:

[0034] S1: Obtain real-time monitoring data of the positioning base station.

[0035] S2: According to the real-time monitoring data of the positioning base station, determine whether the propagation path at the current moment is a line-of-sight path, and obtain a first determination result.

[0036] S3: If the first judgment result is yes, determine the first arrival path of the line-of-sight path state and the corresponding first arrival path delay; the first arrival path of the line-of-sight path state is the strongest path between the transmitter and the receiver.

[0037] S4: Based on the first arrival path delay of the line-of-sight path state, determine the distance between the positioning base station and the terminal, and obtain the positioning coordinates of the terminal by solving the positioning equation; the distance is the product of the first arrival path delay and the propagation speed.

[0038] S5: If the first judgment result is no, the first-reaching path and the corresponding first-reaching path delay of the non-line-of-sight path state are determined based on local cognitive feedback; the local cognitive feedback is based on the channel detection result of the base station; the channel detection result based on the base station includes: key indicators and direct path mutation conditions.

[0039] S6: Determine whether there is a problem with the first-reach path of the non-line-of-sight path state determined based on local cognitive feedback, and obtain a second judgment result. It is set that if the change in the power of the first-reach path identified in the current state and the power of the first-reach path identified in the previous state is greater than a set power threshold, it means that the identified first-reach path has undergone a mutation. At this time, it is a non-line-of-sight path. At this time, if there is no path that exceeds the first-path identification threshold, or there is only one path that exceeds the first-path identification threshold and it is the strongest path, and the time interval between the delay corresponding to this path and the delay corresponding to the first-reach path at the previous moment is significantly greater than the time the terminal moves. Then the local end feedback identifies that there is a problem with the first-reach path, and performs cognitive feedback in the cloud.

[0040] S7: If the second judgment result is no, the distance between the positioning base station and the terminal is determined based on the first arrival path delay of the non-line-of-sight path state, and the positioning coordinates of the terminal are obtained by solving the positioning equation.

[0041] S8: If the second judgment result is yes, the estimated first-reach path and the corresponding first-reach path delay estimate of the non-line-of-sight path state at the current moment are determined based on the cloud-based cognitive feedback; the cloud-based cognitive feedback is based on the cloud combined with the global cognition of the digital twin map and the wireless environment map.

[0042] S9: Based on the estimated first-arrival path delay of the non-line-of-sight path at the current moment, determine the distance between the positioning base station and the terminal, and obtain the positioning coordinates of the terminal by solving the positioning equation.

[0043] By implementing the above steps S1 to S9, the present application uses a dual-layer cognitive feedback mechanism of local feedback and cloud feedback to promptly give the positioning system corresponding feedback actions for the time-varying channel state, and improves the positioning performance of the terminal movement trajectory through interactive and iterative operation.

[0044] The technical solution of this application is described in detail as follows.

[0045] A1: Identify the first path.

[0046] First, identify the first arrival path and obtain the first arrival path delay. Generally speaking, in the line-of-sight scenario, the strongest path between the transmitter and the receiver can be identified as the first arrival path, that is, the direct path. The arrival time of the first arrival path (the first arrival path delay in the line-of-sight path state) can be expressed as:

[0047]

[0048] Among them, t DP is the first arrival delay in line-of-sight path state, t i is the arrival time of the i-th multipath, P i is the power of the i-th multipath.

[0049] In the case of non-line-of-sight, formula (1) may not be very accurate. Because when the direct path of wireless signal propagation is blocked, the propagation delay is the delay after multiple reflections of the signal, and the strongest path is not necessarily the first path. Therefore, if the strongest path is simply identified as the first path in the case of non-line-of-sight, then the first path delay estimation error is large. This application proposes the following three solutions:

[0050] 1) Adjust the channel used by the base station or terminal, find the earliest arriving path in the wider frequency band as the first arrival path, and obtain the corresponding first arrival path delay.

[0051] 2) Adjust the beam direction and size of the base station or terminal, find the earliest arriving path from a larger spatial dimension as the first arrival path, and obtain the corresponding first arrival path delay.

[0052] 3) Based on the previously known line-of-sight path status, the first path of the current state is obtained by tracking.

[0053] A2: Obtain the first-path delay based on a two-layer feedback mechanism.

[0054] Specifically, the two-layer cognitive feedback mechanism includes two levels. From the system level, the first is local-based cognitive feedback, and the second is cloud-based cognitive feedback. It should be noted that the working mechanism of the entire system is mainly based on the local feedback mechanism. If the local end (such as the base station) feedback identifies the first-path problem (if there is no path that exceeds the first-path identification threshold, or there is only one path that exceeds the first-path identification threshold and is the strongest path, and the time delay corresponding to this path is significantly longer than the time delay corresponding to the first-path at the previous moment), and the positioning performance still cannot be guaranteed, the cloud-based feedback mechanism will be executed.

[0055] First, it is necessary to construct a wireless environment map of the channel twin under the time-varying channel state. Based on the three-dimensional digital twin map and combined with the first-path delay obtained in the previous steps, the wireless environment map of the channel twin is constructed. The wireless environment map includes scene information, network topology and system deployment information, channel propagation characteristics information, and some feedback information that helps optimize system performance.

[0056] A21: Locally based cognitive feedback.

[0057] According to the real-time monitoring data of the local base station, determine the solution to be adopted. Figure 3 Shown is a block diagram of local-based cognitive feedback.

[0058] The base station sends a broadcast frame, and when the terminal needs to complete a positioning request, the terminal sends a ranging frame (wireless detection signal). The base station receives the signal sent by the terminal, performs channel detection and analyzes the detection results.

[0059] Method for judging non-line-of-sight based on the channel detection feedback results of the base station:

[0060] a) Key indicators based on channel detection results.

[0061] If, in the channel parameter results extracted during the channel detection process, for example, the signal-to-noise ratio of the extracted detection signal is very low, it generally reflects that the current state is a non-line-of-sight propagation path.

[0062] b) Direct path mutation situation identified based on channel detection results.

[0063] The channel characteristics in the wireless environment have spatial consistency, for example, the channel impulse response has the characteristics of time continuity. When the direct path of the wireless signal propagation along the terminal motion trajectory changes suddenly, it can be considered that the wireless signal propagation is blocked, so that the transition from line-of-sight to non-line-of-sight between the positioning base station and the terminal can be identified. If the change in the power of the first-reaching path identified in the current state and the power of the first-reaching path identified in the previous state is greater than a set power threshold, it means that the identified first-reaching path has mutated suddenly.

[0064] Therefore, if the feedback result of the base station determines that the propagation path at this time is a line-of-sight path, the first-reach path delay corresponding to this first-reach path is obtained using formula (1). If it is determined to be a non-line-of-sight path, then the three first-reach path identification methods under the non-line-of-sight condition are used, namely:

[0065] A211: Adjust the channel channel used by the positioning base station or terminal, take the earliest reached (identified) path in the preset frequency band as the first reached path in the non-line-of-sight path state, and obtain the first reached path delay of the first reached path in the non-line-of-sight path state.

[0066] By adjusting the channel used by the positioning base station or terminal, the calculation formula for the first-reach path delay of the non-line-of-sight path state is obtained as follows:

[0067]

[0068] Among them, t DP_nlos is the first arrival time of the first arrival path in the non-line-of-sight path state, M is the number of adjustable channels, tm,i is the arrival time of the i-th multipath in channel m, P m,i is the power of the ith multipath in channel m, P th It is the power threshold for extracting multipath settings. Generally, there are two methods for selecting this threshold, namely fixed threshold and dynamic threshold. However, in the actual channel measurement results, the signal-to-noise ratio will change, and the fixed threshold cannot adapt well to different environments (the stray noise above this threshold will be considered as a multipath component, causing false detection of the first-reaching path, and below the threshold will result in missed detection), and the dynamic threshold has better adaptability. Therefore, in this application, P th Dynamic setting is that when the terminal moves, the power threshold is 10dB lower than the strongest path corresponding to its current location. Therefore, when searching for the first path from a wider frequency band, the power threshold greater than P th The first path that reaches the power threshold can be identified as the first-reaching path.

[0069] In non-line-of-sight environments, signal transmission may be affected by obstructions, making it difficult to accurately identify the first path. By adjusting the channel used, the detection signal may experience different propagation conditions in different frequency bands. The reasons are:

[0070] (1) Different multipath effects: In different frequency bands, the interaction between the detection signal and the environment is different. The signal may be affected by different environments, resulting in different multipath effects. Therefore, in different frequency bands, different main propagation paths may appear, some of which may have shorter propagation delays, resulting in smaller errors when identified as the first arrival path.

[0071] (2) Signal (frequency selectivity) attenuation differences: In different frequency bands, the attenuation degree of the detection signal may be different. Under some environmental conditions, it will show less attenuation or experience less multipath interference, making it easier for the signal to cross obstacles and reach the receiving antenna, thereby improving the accuracy of estimating the first-reach path propagation delay.

[0072] (3) Different antenna characteristics: In different frequency bands, the antenna radiation patterns and gain characteristics of base stations and terminal devices may be slightly different, which may lead to different reception sensitivities to the multipath of the detection signal, thus affecting the identification of the first arrival path.

[0073] For example, the IEEE 802.15.4 / 4z standard defines 16 channels for ultrawideband (UWB) signals. Therefore, in practical applications, the operating frequency band of the UWB signal can be adjusted as needed.

[0074] The feasibility analysis of this operation is as follows Figure 4As shown in the figure, the selected scene is a test hall. The power delay profile (PDP) when adjusting the channel is obtained by ray tracing method to analyze whether adjusting the channel has an impact on the first path identification in the non-line-of-sight scenario. The center frequencies of the ultra-wideband signal are set to 3GHz, 4GHz, 6GHz and 28GHz, respectively, the delay resolution is 2 nanoseconds, and the signal transmission power is 0dBm. During the experiment, the transceiver antennas formed a non-line-of-sight propagation path due to the obstruction of the indoor walls. The actual distance between the transceiver antennas is 5.22 meters. In theory, the propagation delay of the direct path of the signal propagation is about 17.40 nanoseconds. As can be seen from the figure, first, when adjusting different channels, the propagation attenuation of multipath is different; second, under non-line-of-sight propagation conditions, the strongest path is generally not the direct path. Due to the influence of the non-line-of-sight path formed by obstruction, the strongest paths under the four different center frequency conditions basically correspond to a delay of about 70 nanoseconds, which is nearly 52.6 nanoseconds different from the theoretical direct path delay. Therefore, under the non-line-of-sight path, identifying the strongest path as the direct path will result in a large delay estimation error; finally, when the center frequency is 4 GHz, the strongest path is -91.84 dBm, and the first-reaching path power is -97.04 dBm, and the difference between the powers is within 10 dB; when the center frequency is 6 GHz, the strongest path is -94.75 dBm, and the first-reaching path power is -97.19 dBm, and the difference between the powers is within 10 dB. It can be judged that under the current measurement conditions, the delay corresponding to the earliest multipath peak is 24 nanoseconds, which is less than the error between the theoretical direct path delay.

[0075] In addition, actual measurement verification was carried out based on the measurement system. The test scenario selected was an office environment. The detection signal uses the UWB signal of the IEEE802.15.4a / z standard with a delay resolution of 1 nanosecond. The test channel uses channel 2 (center frequency of 3993.6MHz, bandwidth of 499.2MHz) and channel 9 (center frequency of 7987.2MHz, bandwidth of 499.2MHz) that comply with the IEEE802.15.4a / z standard. During the experiment, a strong non-line-of-sight propagation path was formed between the transceiver antennas due to the obstruction of the large metal plate. The actual distance between the transceiver antennas was about 1.94 meters. Theoretically, the propagation delay of the direct path of signal propagation is about 6.47 nanoseconds. From Figure 5It can be seen that, firstly, the propagation attenuation of multipath is different when adjusting different channels; secondly, it can be seen that under non-line-of-sight propagation conditions, the strongest path may not be the direct path. Due to the influence of non-line-of-sight paths formed by obstruction, the first path delay under the channel9 test condition is about 7.11 nanoseconds, the ranging is about 2.13 meters, and the ranging error is about 0.19 meters; the first path delay under the channel2 test condition is about 8.57 nanoseconds, the ranging is about 2.57 meters, and the ranging error is about 0.63 meters, which is a large ranging error.

[0076] Therefore, by adjusting the channel used by the base station or terminal, the different channel characteristics and propagation effects of signals on different frequency bands can be utilized to more effectively search for the first arrival path from a wider frequency band range, reduce the first arrival path identification error, and thus further reduce the ranging error.

[0077] A212: Adjust the beam direction and size of the positioning base station or terminal, take the earliest arriving path in the preset spatial dimension as the first arrival path of the non-line-of-sight path state, and obtain the first arrival path delay of the first arrival path of the non-line-of-sight path state.

[0078] When the environment is a multi-metal and multi-interference environment, the strong electromagnetic effect brought by the metal material will strongly interfere with the detection signal (such as UWB signal), causing the multipath amplitudes to overlap and the phases to affect each other, causing the direct path position to shift, or the direct path amplitude to be severely attenuated, resulting in inability to identify and distinguish multipath signals of different paths. By adjusting the beam direction and size of the base station or terminal antenna array, the transmission direction and coverage range of the emitted detection signal can be changed, and the signal strength of the direct path can be enhanced to a certain extent, thereby reducing the influence of other paths and making the direct path identification more accurate.

[0079] A213: Based on the previously known line-of-sight path status, obtain the first path of the current state.

[0080] For the identified non-line-of-sight path, if there is a line-of-sight path state in the previous state of the non-line-of-sight path at the current time n+1, its first-path delay can be tracked based on the line-of-sight path state at the previous n times. Specifically, for situations that may exist in practical applications, linear prediction and nonlinear prediction tracking methods are used to track the first-path delay at time n+1:

[0081] a) If (i) the terminal moves at a uniform speed, or (ii) the state values ​​are selected at n consecutive moments, or (iii) the positioning frequency (positioning time interval) is fixed, then the formula for the linear prediction (delay domain) tracking method is expressed as:

[0082]

[0083] b) If (i) the terminal moving speed is non-uniform, or (ii) the state values ​​are selected at n non-continuous moments, or (iii) the positioning frequency (positioning time interval) is not fixed, then the formula for the nonlinear prediction (delay domain) tracking method is expressed as:

[0084]

[0085] Among them, ω i is the weight associated with each of the first path amplitudes corresponding to the selected n moments. Assume that the first path amplitude of the channel impulse response corresponding to the selected n moments is expressed as a i ,i=1,...,n, then ω i It can be obtained by normalization method, that is,

[0086]

[0087]

[0088] Among them, t1 (when i=1) is not the state delay value of the first moment corresponding to the terminal movement trajectory during actual positioning, but the first path delay value of the first moment of the selected n moments.

[0089] The first-reach path delay tracked at this time can be used as a known condition for tracking the first-reach path in subsequent non-line-of-sight scenarios.

[0090] A22: Cloud-based cognitive feedback.

[0091] The cloud on the network side has a digital twin map, a wireless environment map, and stores the working parameters of the network and system. The cloud server can provide feedback to the base station based on the overall understanding for the next step, including adjusting the system working parameters and using the terminal mobility to infer the first path delay of an unknown location. Figure 6 Shown is a block diagram of cloud-based cognitive feedback.

[0092] A221: Adjust system operating parameters and calculate the multipath delay resolution; the system operating parameters include: detection signal bandwidth and sampling rate; the multipath delay resolution is used to improve the accuracy of first-path delay estimation.

[0093] By adjusting the system parameters, the multipath delay resolution is improved, and then the accuracy of the first-path delay estimation is improved. Specifically:

[0094] i. It can increase the bandwidth of the communication system detection signal. A detection signal with a larger bandwidth helps improve the system's ability to resolve multipath channels, thereby improving the multipath delay resolution. The formula is:

[0095] Δt res =1 / B (7);

[0096] Among them, Δt res is the delay resolution, and B is the detection signal bandwidth.

[0097] For example, assuming that the measurement bandwidth of the measurement system is slightly larger than the signal bandwidth, if the receiving and transmitting distance between the base station and the terminal is 15 meters, the theoretical value of the direct path propagation delay is 50 nanoseconds. When the detection signal bandwidth is 100 MHz, the system delay resolution is about 10 nanoseconds. If the detection signal bandwidth is increased to 500 MHz, the system delay resolution is improved to 2 nanoseconds, then the estimated direct path delay is closer to the theoretical direct path delay.

[0098] ii. The system sampling rate can be increased. Increasing the system sampling rate can obtain more time domain information within the unit time window of channel parameter extraction, so that multipath can be distinguished more finely. Increasing the sampling rate increases the time domain sampling density of the signal, thereby improving the multipath delay resolution. The formula is expressed as:

[0099] Δt res =1 / f s ≤1 / (2B) (8);

[0100] Among them, Δt res is the delay resolution, B is the detection signal bandwidth, and fs is the sampling rate.

[0101] A222: Using the terminal mobility, determine the estimated first-reach path and the corresponding first-reach path delay estimate of the current non-line-of-sight path state.

[0102] Since the previous step has identified that the propagation path at this time is a non-line-of-sight path, and the first-reach path delay at this time cannot be obtained based on local cognitive feedback. Then the prior knowledge in the cloud can be used to infer the first-reach path at this time. Specifically, the cloud wireless environment map has the positioning trajectory of the terminal in the scene, and combined with the digital twin map in the cloud, the nearest line-of-sight path from this place can be indexed from the wireless environment map, combined with the terminal's moving speed and the positioning frequency of the positioning system, to infer the first-reach path delay of the unknown location at this time. The formula is expressed as:

[0103]

[0104] Among them, t i is the estimated first-path delay of the non-line-of-sight path at the current moment, t index is the first arrival path delay corresponding to the line-of-sight path closest to the current non-line-of-sight path, f p is the frequency of the positioning system, a is the number of times the system performs positioning between the two paths, SNR i is the signal-to-noise ratio of the non-line-of-sight path at the current state i, SNR i-1is the signal-to-noise ratio of the non-line-of-sight path at the current state i-1.

[0105] Then, after predicting the first-arrival path delay under the non-line-of-sight propagation conditions at this time, the constructed channel twin wireless environment map can be updated to support the next cloud feedback.

[0106] In addition, in order to further improve the positioning performance, the base station can perform wireless environment perception in stages. By sensing the possible interference in the environment, it can adjust the operating frequency and frame interval of the communication system detection signal to minimize the interference to the current detection signal.

[0107] A3: Ranging and positioning based on first-reach path delay.

[0108] The distance between the positioning base station and the terminal is estimated based on the first-path delay. The ranging result is the product of the signal first-path propagation delay and the propagation speed. After obtaining the ranging result, the positioning coordinates of the terminal can be obtained by solving the positioning equation. The solution methods include but are not limited to trilateration and Chan algorithm.

[0109] The wireless positioning method of the present application can effectively identify the first-reach path and obtain the first-reach path delay through a two-layer cognitive feedback mechanism based on local cognitive feedback and cloud-based cognitive feedback in a complex electromagnetic environment, especially in severe non-line-of-sight propagation conditions or multi-metal shielding environments; at the same time, it can perform real-time processing and feedback based on the time-varying channel state of the complex electromagnetic environment to minimize the first-reach path identification error, thereby reducing the positioning error and ensuring the terminal service experience.

[0110] The present application also provides an application scenario, which applies the above-mentioned wireless positioning method. Specifically: The wireless positioning method provided in this embodiment can be applied in a wireless positioning scenario. The wireless positioning scenario includes: a data acquisition link, a link to determine whether it is a line-of-sight path, a local-based cognitive feedback link, a cloud-based cognitive feedback link, and a first-reach path delay ranging and positioning link. Specifically, real-time monitoring data of the positioning base station is obtained; based on the real-time monitoring data of the positioning base station, whether the propagation path at the current moment is a line-of-sight path is determined to obtain a first judgment result; if the first judgment result is yes, the first arrival path of the line-of-sight path state and the corresponding first arrival path delay are determined; the first arrival path of the line-of-sight path state is the strongest path between the transmitter and the receiver; based on the first arrival path delay of the line-of-sight path state, the distance between the positioning base station and the terminal is determined, and the positioning coordinates of the terminal are obtained by solving the positioning equation; the distance is the product of the first arrival path delay and the propagation speed; if the first judgment result is no, the first arrival path of the non-line-of-sight path state and the corresponding first arrival path delay are determined based on local cognitive feedback; the local-based cognitive feedback is based on the channel detection result of the base station to provide feedback; the channel detection result based on the base station is based on the feedback. The measurement results include: mutations of key indicators and direct paths; judging whether there is a problem with the first path of the non-line-of-sight path state determined based on local cognitive feedback, and obtaining a second judgment result; if the second judgment result is no, determining the distance between the positioning base station and the terminal based on the first path delay of the non-line-of-sight path state, and obtaining the positioning coordinates of the terminal by solving the positioning equation; if the second judgment result is yes, determining the estimated first path of the non-line-of-sight path state at the current moment and the corresponding first path delay estimate based on the cloud-based cognitive feedback; the cloud-based cognitive feedback is based on the cloud-based global cognition of the digital twin map and the wireless environment map; determining the distance between the positioning base station and the terminal based on the first path delay estimate of the non-line-of-sight path at the current moment, and obtaining the positioning coordinates of the terminal by solving the positioning equation.

[0111] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 7As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store real-time monitoring data of the positioning base station. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a wireless positioning method is implemented.

[0112] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0113] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the above-mentioned method embodiments are implemented when the processor executes the computer program.

[0114] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the above-mentioned method embodiments are implemented.

[0115] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the above-mentioned method embodiments are implemented.

[0116] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0117] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0118] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0119] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0120] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A wireless positioning method, characterized in that: The wireless positioning method comprises: Obtain real-time monitoring data of positioning base stations; According to the real-time monitoring data of the positioning base station, determining whether the propagation path at the current moment is a line-of-sight path, and obtaining a first determination result; If the first judgment result is yes, determining the first arrival path of the line-of-sight path state and the corresponding first arrival path delay; the first arrival path of the line-of-sight path state is the strongest path between the transmitter and the receiver; Based on the first arrival path delay of the line-of-sight path state, determine the distance between the positioning base station and the terminal, and obtain the positioning coordinates of the terminal by solving the positioning equation; the distance is the product of the first arrival path delay and the propagation speed; If the first judgment result is no, the first path of the non-line-of-sight path state and the corresponding first path delay are determined based on local cognitive feedback; the local cognitive feedback is based on the channel detection result of the base station; the channel detection result based on the base station includes: key indicators and direct path mutation conditions; Determine whether there is a problem with the first path of the non-line-of-sight path state determined based on the local cognitive feedback, and obtain a second determination result; If the second judgment result is no, determining the distance between the positioning base station and the terminal based on the first arrival path delay of the non-line-of-sight path state, and obtaining the positioning coordinates of the terminal by solving the positioning equation; If the second judgment result is yes, then determining the estimated first-reach path and the corresponding first-reach path delay estimate of the non-line-of-sight path state at the current moment based on the cloud-based cognitive feedback; the cloud-based cognitive feedback is based on the cloud combined with the global cognition of the digital twin map and the wireless environment map to provide feedback; Based on the estimated value of the first-arrival path delay of the non-line-of-sight path at the current moment, the distance between the positioning base station and the terminal is determined, and the positioning coordinates of the terminal are obtained by solving the positioning equation.

2. The wireless positioning method according to claim 1, characterized in that: The calculation formula for the first arrival path delay in the line-of-sight path state is: Among them, t DP is the first arrival delay in line-of-sight path state, t i is the arrival time of the i-th multipath, P i is the power of the i-th multipath.

3. The wireless positioning method according to claim 1, characterized in that: Determine the first arrival path and the corresponding first arrival path delay of the non-line-of-sight path state based on local cognitive feedback, including: Adjust the channel channel used by the positioning base station or terminal, use the earliest path in the preset frequency band as the first path in the non-line-of-sight path state, and obtain the first path delay of the first path in the non-line-of-sight path state; or Adjust the beam direction and size of the positioning base station or terminal, use the earliest arriving path in the preset spatial dimension as the first arrival path of the non-line-of-sight path state, and obtain the first arrival path delay of the first arrival path of the non-line-of-sight path state; or Based on the existing line-of-sight path state at the previous moment, the first arrival path and the corresponding first arrival path delay of the non-line-of-sight path state are tracked.

4. The wireless positioning method according to claim 1, characterized in that: By adjusting the channel used by the positioning base station or terminal, the calculation formula for the first-reach path delay of the non-line-of-sight path state is obtained as follows: Among them, t DP_nlos is the first arrival time of the first arrival path in the non-line-of-sight path state, M is the number of adjustable channels, tm,i is the arrival time of the i-th multipath in channel m, P m,i is the power of the ith multipath in channel m, P th is the power threshold for extracting multipath settings.

5. The wireless positioning method according to claim 1, characterized in that: The calculation formula for determining the estimated first-path delay of the non-line-of-sight path at the current moment based on the cognitive feedback from the cloud is: Among them, t i is the estimated first-path delay of the non-line-of-sight path at the current moment, t index is the first arrival path delay corresponding to the line-of-sight path closest to the current non-line-of-sight path, f p is the frequency of the positioning system, a is the number of times the system performs positioning between the two paths, SNR i is the signal-to-noise ratio of the non-line-of-sight path at the current state i, SNR i-1 is the signal-to-noise ratio of the non-line-of-sight path at the current state i-1.

6. The wireless positioning method according to claim 1, characterized in that: Based on the cognitive feedback from the cloud, the estimated first arrival path and the corresponding first arrival path delay estimate of the current non-line-of-sight path state are determined, including: Adjusting system operating parameters to calculate the multipath delay resolution; the system operating parameters include: detection signal bandwidth and sampling rate; the multipath delay resolution is used to improve the accuracy of first-path delay estimation; By using the terminal mobility, the estimated first arrival path and the corresponding first arrival path delay estimation value of the current non-line-of-sight path state are determined.

7. The wireless positioning method according to claim 6, characterized in that: The calculation formula of the multipath delay resolution is: Δt res = 1 / B or Δt res = 1 / f s ≤ 1 / (2B); Among them, Δt res is the delay resolution, B is the detection signal bandwidth, and fs is the sampling rate.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the wireless positioning method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the wireless positioning method described in any one of claims 1 to 7 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the wireless positioning method described in any one of claims 1 to 7 is implemented.

Images