A wireless positioning method, device, medium and product

Abstract

The present application discloses a wireless positioning method, device, medium and product, which relates to the field of wireless positioning. The method includes: judging 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 obtained; if so, determining the first arrival path and the corresponding first arrival path delay of the line-of-sight path state, and determining the distance between the positioning base station and the terminal and the positioning coordinates of the terminal; if not, determining the first arrival path and the corresponding first arrival path delay of the non-line-of-sight path state based on local cognitive feedback; judging whether there is a problem with the first arrival path of the non-line-of-sight path state determined based on local cognitive feedback; if not, determining the distance between the positioning base station and the terminal and the positioning coordinates of the terminal; if so, determining the estimated first arrival path and the corresponding first arrival path delay estimate of the non-line-of-sight path state at the current moment based on the cognitive feedback from the cloud, and determining the distance between the positioning base station and the terminal and the positioning coordinates of the terminal. The present application can reduce positioning errors.

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 measurements mainly include power measurement, time measurement, and angle measurement. Power measurement includes triangulation positioning and fingerprint positioning. Time measurement includes positioning technologies based on time of arrival (TOA) and time difference of arrival (TDOA). Angle measurement includes positioning technologies based on angle of arrival (AOA) and angle of departure (AOD).

[0003] However, the existing technology has the following shortcomings: (1) If the scene has a large area and severe non-line-of-sight situation, or 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 state to minimize the positioning error as much as possible 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 arrival path and obtain the first arrival 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 arrival path and the corresponding first arrival 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 base station-based channel detection result includes: key indicators and direct path mutation conditions.

[0012] It is determined whether there is a problem with the first arrival 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 in 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 arrival path and the corresponding first arrival 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 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 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 described above.

[0017] In a third aspect, the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the wireless positioning method described above is implemented.

[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; 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 cognitive feedback is based on the channel detection result of the base station. 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-reach 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-reach 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, determine 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 first-reach 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 complex electromagnetic environments, 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 following briefly introduces the drawings required for use in the embodiments. 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 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 one embodiment of the present application.

[0025] Figure 4 A schematic diagram of a feasibility analysis (non-line-of-sight propagation path conditions) for adjusting the channel identification first arrival path provided in one embodiment of the present application.

[0026] Figure 5 A schematic diagram of the actual measurement verification (non-line-of-sight propagation path conditions) of adjusting the channel identification first arrival path provided by one 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 this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0030] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to 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 via 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 and the corresponding first arrival path delay of the non-line-of-sight path state 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. 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; judge 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 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 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 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 server 104 can feed back 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 positioning 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 a cloud server.

[0033] In an exemplary embodiment, Figure 2 As shown, a wireless positioning method is provided, which is executed by a computer device, specifically a computer device such as a terminal or a server, or a terminal and a server. 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.

[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 judgment result.

[0036] S3: If the first judgment result is yes, determine the first arrival path in the line-of-sight path state and the corresponding first arrival path delay; the first arrival path in 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 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 in 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 arrival path and the corresponding first arrival 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 a line-of-sight scenario, the strongest path between the transmitter and 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 the 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 non-line-of-sight situations, formula (1) may not be very accurate. This is because when the direct path of wireless signal propagation is blocked, the propagation delay is the delay after the signal is reflected multiple times. The strongest path is not necessarily the first path to arrive. Therefore, if the strongest path is simply identified as the first path to arrive in non-line-of-sight situations, the first path delay estimation error will be large. This application proposes the following three solutions:

[0050] 1) Adjust the channel used by the base station or terminal to find the earliest arriving path in a 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) to 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 arrival path of the current state is obtained.

[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 it 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, a wireless environment map representing the channel twin under time-varying channel conditions must be constructed. This map is based on the 3D digital twin map and combines the first-path delays obtained in the previous steps. This map includes scenario information, network topology and system deployment information, channel propagation characteristics, and 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 that needs 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 transmits 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 determining non-line-of-sight based on base station channel detection feedback results:

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

[0061] If the channel parameter results extracted during the channel detection process show, for example, that 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] Channel characteristics in wireless environments exhibit spatial consistency. For example, the channel impulse response exhibits temporal continuity. When the direct path of wireless signal propagation along the terminal's trajectory undergoes a sudden change, it can be considered that the wireless signal propagation is blocked, thereby identifying the transition from line-of-sight to non-line-of-sight between the positioning base station and the terminal. If the difference in power between the first-reach path identified in the current state and the first-reach path identified in the previous state exceeds a set power threshold, it indicates that the identified first-reach path has undergone a sudden change.

[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 arrival path delay corresponding to this first arrival path is obtained using formula (1). If it is determined to be a non-line-of-sight path, then the three first arrival path identification methods under the non-line-of-sight situation are used, namely:

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

[0067]

[0068] Among them, t DP_nlos is the 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 i-th 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 actual channel measurement results, the signal-to-noise ratio will change, and the fixed threshold cannot adapt well to different environments (spurious noise above this threshold will be considered as multipath component, causing false detection of the first arrival path, and below the threshold will result in missed detection). The dynamic threshold has better adaptability. Therefore, in this application, P th Dynamic setting is that when the terminal moves, the power threshold is lower than 10dB compared to the strongest path corresponding to its current location. Therefore, when searching for the first path from a wider frequency band, the power threshold is 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 arrival 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: The degree of attenuation of the detection signal may vary in different frequency bands. In some environmental conditions, the signal may exhibit 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 multipath reception sensitivities to 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 UWB signals can be adjusted as needed.

[0074] The feasibility analysis of this operation is as follows Figure 4As shown, the selected scenario is a test hall. Ray tracing is used to obtain the power delay profile (PDP) when adjusting the channel. This analysis is used to determine whether adjusting the channel affects first-path identification in non-line-of-sight (NLOS) scenarios. The center frequencies of the ultra-wideband signal are set to 3 GHz, 4 GHz, 6 GHz, and 28 GHz, respectively. The delay resolution is 2 nanoseconds, and the signal transmission power is 0 dBm. During the experiment, the propagation path between the transceiver antennas is non-line-of-sight due to obstruction by the indoor walls. The actual distance between the transceiver antennas is 5.22 meters. Theoretically, the propagation delay of the direct path of the signal is approximately 17.40 nanoseconds. The figure shows that, first, the multipath propagation attenuation varies when adjusting different channels. Second, under non-line-of-sight (NLOS) propagation conditions, the strongest path is generally not the direct path. Due to the influence of obstruction on the NLOS path, the strongest path under these four different center frequencies generally corresponds to a delay of approximately 70 nanoseconds, which differs from the theoretical direct path delay by nearly 52.6 nanoseconds. Therefore, in NLOS conditions, identifying the strongest path as the direct path will result in a significant delay estimation error. Finally, when the center frequency is 4 GHz, the strongest path power is -91.84 dBm, and the first-reaching path power is -97.04 dBm, with the power difference within 10 dB. When the center frequency is 6 GHz, the strongest path power is -94.75 dBm, and the first-reaching path power is -97.19 dBm, with the power difference within 10 dB. Under the current measurement conditions, the delay corresponding to the earliest arriving multipath peak is 24 nanoseconds, which is relatively close to the theoretical direct path delay.

[0075] In addition, actual measurement verification was carried out based on the measurement system. The selected test scenario is 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, due to the obstruction of the large metal plate, a strong non-line-of-sight propagation path was formed between the transceiver antennas. The actual distance between the transceiver antennas was about 1.94 meters. In theory, the propagation delay of the direct path of signal propagation is about 6.47 nanoseconds. From Figure 5As can be seen from the results, first, multipath propagation attenuation varies when adjusting different channels. Second, it can be seen that in non-line-of-sight (NLOS) propagation conditions, the strongest path may not be the direct path. Due to the influence of non-line-of-sight (NLOS) paths caused by obstructions, the first-path delay under channel 9 was approximately 7.11 nanoseconds, the ranging was approximately 2.13 meters, and the ranging error was approximately 0.19 meters. Under channel 2, the first-path delay was approximately 8.57 nanoseconds, the ranging was approximately 2.57 meters, and the ranging error was approximately 0.63 meters, indicating a significant ranging error.

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

[0077] A212: 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 in the non-line-of-sight path state, and obtain the first arrival path delay of the first arrival path in the non-line-of-sight path state.

[0078] In environments with a lot of metal and interference, the strong electromagnetic effects of metal can significantly interfere with detection signals (such as UWB signals). This can cause multipath amplitudes to overlap and phases to influence each other, shifting the direct path position or severely attenuating the direct path amplitude, making it difficult to identify and distinguish multipath signals from different paths. By adjusting the beam direction and size of the base station or terminal antenna array, the transmission direction and coverage of the transmitted detection signal can be changed. This can enhance the signal strength of the direct path to a certain extent, thereby reducing the influence of other paths and making direct path identification more accurate.

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

[0080] For the identified non-line-of-sight path, if the previous state of the non-line-of-sight path at the current time n+1 contains a line-of-sight path state, then its first arrival path delay can be tracked based on the line-of-sight path state at the previous n moments. Specifically, based on the situations that may exist in actual 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:

[0082]

[0083] b) If (i) the terminal's mobile speed is non-uniform, or (ii) the state values ​​are selected at n non-consecutive 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 It is the weight associated with each first path amplitude 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] Here, t1 (when i=1) is not the state delay value at the first moment corresponding to the terminal movement trajectory during actual positioning, but the first arrival path delay value at the first moment of the selected n moments.

[0089] The first arrival path delay tracked at this time can be used as a known condition for tracking the first arrival 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 network and system operating parameters. The cloud server can provide feedback to the base station based on the overall understanding for the next step, including adjusting system operating parameters and using terminal mobility to estimate the first path delay of unknown locations. 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 the first-path delay estimation.

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

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

[0095] Δt res =1 / B (7);

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

[0097] For example, assuming the measurement bandwidth of the measurement system is slightly larger than the signal bandwidth, if the transmission and reception 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 approximately 10 nanoseconds. If the detection signal bandwidth is increased to 500 MHz, the system delay resolution improves to 2 nanoseconds, and 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, thereby enabling more precise multipath resolution. Increasing the sampling rate increases the time domain sampling density of the signal, thereby improving multipath delay resolution. The formula is expressed as:

[0099] Δt res =1 / f s ≤1 / (2B) (8);

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

[0101] A222: Utilize terminal mobility to determine the estimated first arrival path and the corresponding first arrival path delay estimate for the current non-line-of-sight path state.

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

[0103]

[0104] Among them, t i is the estimated first arrival 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 positioning performance, the base station can perform wireless environment perception in stages. By sensing possible interference in the environment, it adjusts 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's first-path propagation delay and the propagation speed. After obtaining the ranging result, the terminal's location coordinates can be obtained by solving the positioning equation. Solution methods include but are not limited to trilateration and the 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 in complex electromagnetic environments, especially in severe non-line-of-sight propagation conditions or multi-metal shielding environments through a two-layer cognitive feedback mechanism based on local cognitive feedback and cloud-based cognitive feedback; 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] This application also provides an application scenario that 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 step, a determination of whether it is a line-of-sight path step, a local-based cognitive feedback step, a cloud-based cognitive feedback step, and a first-path delay ranging and positioning step. 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 used to provide feedback. The measurement results include: key indicators and direct path mutation conditions; judging 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 obtaining a second judgment result; if the second judgment result is no, then based on the first-reach 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-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 first-reach 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.

[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, abbreviated as I / O) and a communication interface. The processor, memory and 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 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 shown in the figure, or combine certain components, or have a different component arrangement.

[0113] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the above method embodiments when executing the computer program.

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

[0115] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the above 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 skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented 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 memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may 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 may 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 databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0119] The technical features of the above embodiments can 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 document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may 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; Determining whether the current propagation path is a line-of-sight path based on the real-time monitoring data of the positioning base station, and obtaining a first determination result; If the first judgment result is yes, determining the first arrival path in the line-of-sight path state and the corresponding first arrival path delay; the first arrival path in the line-of-sight path state is the strongest path between the transmitter and the receiver; Based on the first arrival delay in 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 delay and the propagation speed; If the first judgment result is no, determining the first arrival path and the corresponding first arrival path delay of the non-line-of-sight path state 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 status; Determining whether there is a problem with the first arrival path of the non-line-of-sight path state determined based on the local cognitive feedback, and obtaining 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 in 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 arrival path and the corresponding first arrival path delay estimate of the current non-line-of-sight path state based on the cloud-based cognitive feedback; the cloud-based cognitive feedback is based on the cloud's global cognition of the digital twin map and the wireless environment map; Based on the estimated 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, wherein: 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 the 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, wherein: Determine the first arrival path and the corresponding first arrival path delay based on the local cognitive feedback of the non-line-of-sight path state, specifically including: Adjust the channel used by the positioning base station or terminal, use the earliest path reached in the preset frequency band as the first arrival path in the non-line-of-sight path state, and obtain the first arrival path delay of the first arrival 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 in the non-line-of-sight path state, and obtain the first arrival path delay of the first arrival path in 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, wherein: By adjusting the channel used by the positioning base station or terminal, the calculation formula for the first arrival path delay of the non-line-of-sight path state is: Among them, t DP_nlos is the 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 i-th multipath in channel m, P th is the power threshold for extracting multipath settings.

5. The wireless positioning method according to claim 1, wherein: The calculation formula for determining the estimated first-path delay of the current non-line-of-sight path based on cloud-based cognitive feedback is: Among them, t i is the estimated first arrival 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, wherein: Based on the cloud's cognitive feedback, the estimated first arrival path and the corresponding first arrival path delay estimate for the current non-line-of-sight path state are determined, specifically including: Adjusting system operating parameters to calculate a 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; The terminal mobility is used to determine the estimated first arrival path and the corresponding first arrival path delay estimate of the current non-line-of-sight path state.

7. The wireless positioning method according to claim 6, wherein: The calculation formula of the multipath delay resolution is: Δt res = 1 / B or Δt res = 1 / f s ≤ 1 / (2B); Where, 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 according to 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 according to any one of claims 1 to 7 is implemented.

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