UWB ranging method, base station, UWB positioning method and UWB system

Abstract

The invention relates to the technical field of UWB range finding, and discloses a UWB range finding method, a base station, a UWB positioning method and a UWB system.The UWB range finding method comprises the steps that CIR information of a target label is acquired, first-path preliminary detection is carried out on the CIR information, and an initial first-path index is obtained; obtaining an energy characteristic, a slope characteristic and a peak value characteristic according to the CIR information and the initial first path index; according to the energy characteristic, the slope characteristic and the peak value characteristic, carrying out first diameter secondary detection to obtain a first diameter detection result; and performing correction or calculation according to the first diameter detection result to obtain a target distance measurement value. According to the invention, the ranging and positioning precision of the UWB technology in a complex indoor environment can be improved, the error is reduced, and the system stability is improved.

Description

Technical Field

[0001] This application relates to the field of UWB ranging technology, and in particular to a UWB ranging method, a base station, a UWB positioning method, and a UWB system. Background Technology

[0002] With the rapid development of IoT technology, the demand for indoor positioning is growing rapidly in many fields such as smart warehousing, smart logistics, smart homes, and smart cars. Ultra-wideband (UWB) technology, with its advantages of high-precision ranging, strong multipath resistance, and low power consumption, has become a popular technology in the field of indoor positioning. However, in complex indoor environments, multipath propagation severely affects the accuracy of UWB ranging and positioning, leading to increased measurement errors and inaccurate positioning results. This greatly limits the application of UWB technology in scenarios with stringent accuracy requirements.

[0003] Most existing UWB ranging technologies rely on the first path (TOA) arrival time (TAT) of the received signal for distance estimation, making accurate TAT determination crucial. Among traditional methods, incoherent energy detection and threshold crossing are the two most common. Incoherent energy detection uses the point with the highest signal energy as the TAT. While simple to implement and effective in ideal scenarios where the TAT signal is strongest, its reliability significantly decreases in multipath environments because the TAT is often not the strongest component. Threshold crossing sets an energy threshold and identifies the point where the signal first exceeds that threshold as the TAT. This method is extremely sensitive to threshold selection; slight errors can lead to misidentification of noise or other multipath components as the TAT, amplifying the error.

[0004] In recent years, deep learning methods have also been introduced into the ranging field. For example, inputting the Channel Impulse Response (CIR) into Convolutional Neural Networks (CNNs) for discrimination has significantly improved estimation accuracy. However, the high complexity of CNN models leads to significant computational overhead, placing high demands on hardware performance and posing a considerable challenge for deployment on resource-constrained embedded devices. Furthermore, these methods rely on large amounts of training data; if the amount of data in practical applications is limited, or if the data distribution differs significantly from the training set, the model performance will also be affected.

[0005] Currently, mainstream UWB chips on the market (such as the DW1000 and DW3000 series) typically use a method based on energy mutation detection to estimate the first-path location. This involves calculating local energy changes before and after a certain point, and identifying the location of the first-path as the point of occurrence when the difference exceeds a set threshold. Upsampling is also used to improve temporal resolution, thereby enhancing the accuracy of first-path estimation. However, even with these methods, inaccurate first-path detection still exists in complex indoor multipath environments.

[0006] Therefore, existing technologies still need to be improved and developed. Summary of the Invention

[0007] The main purpose of this application is to provide a UWB ranging method, base station, UWB positioning method and UWB system, aiming to solve the problem that the key to UWB ranging technology in the prior art lies in the determination of the first path. The existing method based on the principle of energy change detection is used to estimate the position of the first path. However, the first path detection is inaccurate in complex multipath environments, resulting in low accuracy of UWB ranging and positioning.

[0008] The first aspect of this application provides a UWB ranging method, which includes the following steps: acquiring CIR information of a target tag and performing preliminary first-path detection on the CIR information to obtain an initial first-path index; obtaining energy features, slope features, and peak features based on the CIR information and the initial first-path index; performing secondary first-path detection based on the energy features, slope features, and peak features to obtain a first-path detection result; and correcting or calculating based on the first-path detection result to obtain a target ranging value.

[0009] Optionally, in one embodiment of this application, the CIR information includes a CIR curve; obtaining energy features, slope features, and peak features based on the CIR information and the initial first diameter index specifically includes: forming a local detection window on the CIR curve based on the initial first diameter index; performing feature analysis on multiple points within the local detection window to obtain energy features, slope features, and peak features corresponding to each of the multiple candidate points.

[0010] Optionally, in one embodiment of this application, the energy feature is an energy value, the slope feature is a slope, and the peak feature is a peak value; the step of performing feature analysis on multiple points within the local detection window to obtain the energy feature, slope feature, and peak feature corresponding to each of the multiple candidate points specifically includes: calculating the energy value of all points within the local detection window, and taking multiple points whose energy value is greater than a set dynamic threshold as multiple candidate points; calculating the slope of each candidate point within the local detection window; and performing peak detection within the local detection window to obtain the peak value of each candidate point.

[0011] Optionally, in one embodiment of this application, the first diameter detection result is the true first diameter position; the second first diameter detection based on the energy feature, the slope feature, and the peak feature to obtain the first diameter detection result specifically includes: fusing the energy feature, slope feature, and peak feature corresponding to each of the multiple candidate points to obtain a comprehensive score corresponding to each of the multiple candidate points; and taking the candidate point corresponding to the highest score among the multiple comprehensive scores as the true first diameter position.

[0012] Optionally, in one embodiment of this application, the step of correcting or calculating based on the first diameter detection result to obtain the target ranging value specifically includes: performing energy ratio analysis based on the true first diameter position and the CIR information to obtain the actual energy ratio; if the actual energy ratio is less than a set energy ratio, then correcting the true first diameter position to obtain the target ranging value; if the actual energy ratio is greater than or equal to the set energy ratio, then calculating the target ranging value based on the true first diameter position.

[0013] Optionally, in one embodiment of this application, the step of correcting the true first diameter position to obtain the target ranging value specifically includes: obtaining a time delay offset based on the true first diameter position and the initial first diameter index; obtaining a corrected ranging value based on the time delay offset and the true first diameter position; and smoothing the corrected ranging value to obtain the target ranging value.

[0014] A second aspect of this application also provides a base station, wherein the base station is a solution base station or a non-solution base station, and the solution base station or the non-solution base station is used to implement the steps of the UWB ranging method described in any of the above schemes.

[0015] A third aspect of this application also provides a UWB positioning method based on the UWB ranging method described in any one of the above schemes, wherein the method is applied to a calculation base station; the UWB positioning method includes: acquiring local message information and sending it to a non-calculation base station, and receiving remote message information from the non-calculation base station; wherein the non-calculation base station includes a first base station and a second base station; obtaining bidirectional ranging parameters based on the local message information and the remote message information; receiving the target ranging value of the first base station and the target ranging value of the second base station in the same ranging period based on the bidirectional ranging parameters; and obtaining positioning data based on the target ranging value of the calculation base station, the target ranging value of the first base station, and the target ranging value of the second base station in the same ranging period.

[0016] Optionally, in one embodiment of this application, the local message information includes a local receive request timestamp, a local send response timestamp, and a local ranging end timestamp; the remote message information includes a first remote receive request timestamp, a first remote send response timestamp corresponding to the first base station, and a second remote receive request timestamp and a second remote send response timestamp corresponding to the second base station; the bidirectional ranging parameters include local bidirectional ranging parameters, a first remote bidirectional ranging parameter, and a second remote bidirectional ranging parameter; obtaining the bidirectional ranging parameters based on the local message information and the remote message information specifically includes: calculating the difference between the local receive request timestamp and the first remote receive request timestamp, and calculating the difference between the local receive request timestamp and the second remote receive request timestamp; obtaining the local ranging end message. Based on the difference between the local ranging end message and the first receive request timestamp, a first remote ranging end message of the first base station is obtained, and based on the difference between the local ranging end message and the second receive request timestamp, a second remote ranging end message of the second base station is obtained. Based on the local receive request timestamp, the local send response timestamp, and the local ranging end timestamp, the local bidirectional ranging parameters between the solving base station and the target tag are calculated. Based on the first remote receive request timestamp, the first remote send response timestamp, and the first remote ranging end message, the first remote bidirectional ranging parameters between the first base station and the target tag are calculated. Based on the second remote receive request timestamp, the second remote send response timestamp, and the second remote ranging end message, the second remote bidirectional ranging parameters between the second base station and the target tag are calculated.

[0017] A fourth aspect of this application also provides a UWB system, wherein the UWB system includes a solution base station, a non-solution base station, and a target tag, the non-solution base station includes a first base station and a second base station, the target tag is a device installed on a target object, and the solution base station, the first base station, the second base station are arranged opposite to the target tag; the solution base station is used to implement the steps of the UWB positioning method as described in the above scheme.

[0018] Beneficial effects: This application provides a UWB ranging method, a base station, a UWB positioning method, and a UWB system. This application improves the accuracy of the initial diameter extraction by combining local peak values ​​and rise slopes with coarse initial diameter detection for secondary CIR initial diameter detection. Thus, this application can improve the ranging and positioning accuracy of UWB technology in complex indoor environments, reduce errors, and improve system stability to meet the application requirements of scenarios with stringent accuracy requirements. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of a preferred embodiment of the UWB ranging method of this application; Figure 2 This is a schematic diagram illustrating the structural principle of distance correction in a preferred embodiment of the UWB distance measurement method of this application. Figure 3 This is a diagram showing the Kalman filter effect in a preferred embodiment of the UWB ranging method of this application; Figure 4 This is a schematic diagram illustrating the effect of secondary first diameter detection in a preferred embodiment of the UWB ranging method of this application; Figure 5 This is a flowchart of a preferred embodiment of the UWB positioning method of this application; Figure 6 This is a schematic diagram of the distance measurement and testing interaction principle in a preferred embodiment of the UWB positioning method of this application; Figure 7 This is a schematic diagram of the interaction timing principle of the multi-base station ranging protocol in a preferred embodiment of the UWB positioning method of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and effects of this application clearer and more explicit, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. The described embodiments are only possible technical implementations of this application and not all possible implementations. Based on the embodiments in this application, those skilled in the art can obtain other embodiments without creative effort, and these embodiments are also within the protection scope of this application.

[0022] In relevant UWB ranging technologies, the principle of energy mutation detection is still used, but the initial diameter detection is inaccurate in complex indoor multipath environments.

[0023] In variations of UWB ranging technologies based on end-to-end deep learning models, a possible alternative design is to directly input the raw CIR data into a deep neural network, train the model to output the first-path index, or directly output the ranging error to correct the original distance estimate. This method avoids explicit analysis and modeling of the CIR. However, this approach has the following significant drawbacks: it fails to effectively utilize the output information of existing first-path detection modules, resulting in low information utilization efficiency; it requires high computing power and a robust model deployment environment, making it unsuitable for deployment on resource-constrained embedded platforms; accuracy improvement relies on training with a large number of samples, and its generalization ability is limited, resulting in poor stability and interpretability. Therefore, although several alternative design paths exist, these solutions face significant challenges in practical deployment, making it difficult to achieve a balance between accuracy and resources. In contrast, this application not only offers high first-path detection and ranging accuracy but also requires less additional computation, enabling efficient operation in embedded devices with low runtime latency. Furthermore, the principle of secondary first-path detection in this application is based on actual signal and channel characteristics, possessing good interpretability and engineering feasibility.

[0024] In related UWB positioning technologies (positioning based on distance measurements obtained from UWB ranging), when a UWB device moves in an indoor environment, its multipath propagation state constantly changes, leading to significant fluctuations in ranging values ​​and their errors, resulting in poor stability. UWB system positioning calculations rely on distance information between multiple base stations and tags. This information typically needs to be transmitted between devices via communication protocols before a location can be calculated on a single device. In other words, current common solutions for positioning calculations involve a base station obtaining its current ranging value from the tag, while simultaneously obtaining ranging data from other base stations from the previous round via communication protocols, and using this to calculate the tag's position. This approach is simple in structure and low in implementation cost, but due to the misalignment of sampling times between different base stations, especially in scenarios with frequent tag movement, the mixing of results from different ranging periods can cause significant positioning errors, severely impacting system accuracy and real-time performance. It is important to note that in a UWB positioning system, ranging is the foundation of positioning, and positioning is the purpose of ranging.

[0025] First, let's introduce the terms used in the embodiments of this application: The English abbreviation UWB stands for Ultra-Wideband. The English abbreviation TOA stands for Time of Arrival. The abbreviation CIR stands for Channel Impulse Response. The English abbreviation CNN stands for Convolutional Neural Networks.

[0026] The key to UWB ranging technology lies in the determination of the first diameter. Existing methods and algorithms based on the principle of energy mutation detection are used to estimate the first diameter position. However, in complex multipath environments, the first diameter detection is inaccurate, resulting in low accuracy of UWB ranging and positioning. This application improves the accuracy of first diameter extraction by combining local peak values ​​and rise slopes for secondary CIR first diameter detection on the basis of coarse first diameter detection. Thus, this application can improve the ranging and positioning accuracy of UWB technology in complex indoor environments, reduce errors, and improve system stability to meet the application requirements of scenarios with stringent accuracy requirements.

[0027] The UWB ranging method of this application, based on primary diameter secondary detection and CIR energy analysis, firstly uses a DW series chip to perform preliminary primary diameter detection, obtaining a coarse primary diameter index. Then, using this index as the center, and combining the received CIR curve, secondary detection is performed based on multiple features such as energy threshold, signal slope, and local peaks to accurately determine the primary diameter position. Furthermore, this application further constructs a mapping relationship between the primary diameter detection error and the actual ranging error, quantifies the error, and establishes a correction model, thereby effectively improving ranging accuracy. Simultaneously, by analyzing the proportion of primary diameter signal energy in the total energy, the strength of multipath effects in the current environment is assessed, providing a basis for environmental adaptive adjustments. To address the fluctuation problem of ranging results, this method introduces a Kalman filter algorithm to smooth the ranging data, reducing random fluctuations in the measurement output and improving system stability.

[0028] The UWB positioning method of this application, in terms of positioning implementation, optimizes the communication protocol design and increases the information carried in the message, so that the base station responsible for location calculation can obtain the ranging data of each base station and the tag in the same ranging period, avoiding the error caused by mixing data from different periods, thereby significantly improving the positioning accuracy, especially suitable for dynamic scenarios where the target moves frequently.

[0029] The technical solutions of this application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0030] The UWB ranging method described in the preferred embodiment of this application, such as Figure 1 As shown, the UWB ranging method includes the following steps: In step S101, the CIR information of the target label is obtained, and the initial first diameter is initially detected based on the CIR information to obtain the initial first diameter index.

[0031] It is worth noting that, see Figure 2 The UWB ranging method of this application includes primary diameter secondary detection and ranging error modeling and correction. First, the UWB communication module completes basic data communication and CIR acquisition, and extracts CIR information through a preprocessing module. Based on the primary diameter detection function built into the DW series chip, an initial primary diameter index is obtained. Then, the primary diameter secondary detection stage begins. This module searches for 20 points (the number is not limited to this, and more or fewer points can be set) of the CIR curve near the initial index, and accurately determines the true primary diameter position by combining the local peak intensity and the trend of the rising slope. This step effectively suppresses the interference of multipath echoes after the primary diameter on the primary diameter determination. The detected primary diameter energy is compared with the total CIR energy to measure the strength of multipath interference, thereby determining whether to activate the ranging correction mechanism. When multipath influence is significant in the environment, corrections are made based on the initial primary diameter offset and multipath intensity. Furthermore, to reduce the jitter effect in dynamic scenes, this application introduces a Kalman filter module to smooth the corrected ranging value, improving the stability of the ranging result. The fluctuation of the filtered ranging value can be reduced by approximately 10%. Finally, all corrected and filtered ranging results are used by the positioning solution module to perform coordinate positioning in conjunction with multi-base station data.

[0032] Understandably, the target tag is a small electronic device attached to the target object, capable of transmitting and receiving UWB signals.

[0033] In one possible implementation, the CIR information includes CIR curves.

[0034] Specifically, during the initial first diameter detection process, the built-in algorithm of the DW series chip is used to perform preliminary analysis of the CIR curve, quickly locate the first significant energy point, and generate a rough first diameter index to provide a benchmark for subsequent secondary fine detection, narrow the search range, and improve efficiency.

[0035] In step S102, energy characteristics, slope characteristics, and peak characteristics are obtained based on the CIR information and the initial first diameter index.

[0036] Understandably, during the secondary refined retrieval process, the search scope centers on the initial index, analyzing 20 neighboring points of the CIR curve (channel impulse response). Feature fusion is employed: energy thresholding to filter signal points with energy higher than the noise floor; slope variation to detect the steepness of the signal's rising edge, distinguishing the main path from subsequent multipath echoes; and local peaks to identify significant peaks in the CIR curve, eliminating spurious peaks caused by interference. This results in the accurate output of the first path location, suppressing misjudgments caused by multipath effects.

[0037] In one possible implementation, a local detection window is formed on the CIR curve based on the initial first diameter index; feature analysis is performed on multiple points within the local detection window to obtain the energy features, slope features, and peak features corresponding to each of the multiple candidate points.

[0038] Specifically, the window range is centered on the initial index, extending 10 points forward and 10 points backward (a total of 20 points) to form a local detection window. It is understandable that multipath echoes following the main path are usually adjacent to the main path on the time axis; therefore, local search can cover potential interference while avoiding the computational overhead of global search. The window size can be adjusted according to the multipath density of the actual environment, but a range of 20 points is sufficient to cover the multipath distribution in most scenarios.

[0039] In one possible implementation, the energy feature is an energy value, the slope feature is a slope, and the peak feature is a peak value. The energy values ​​of all points within the local detection window are calculated, and multiple points whose energy values ​​are greater than a set dynamic threshold are selected as multiple candidate points. The slope of each candidate point within the local detection window is calculated. Peak detection is performed within the local detection window to obtain the peak value of each candidate point.

[0040] Specifically, within a local detection window, energy threshold screening is performed. By calculating the energy values ​​of all points within the window, a dynamic threshold (e.g., 3 times the noise mean) is set to filter out candidate points with energy values ​​higher than the threshold, thereby eliminating noise interference and focusing on the effective signal area. Signal slope analysis (rising edge steepness) is then performed. By calculating the forward difference (the difference between the energy of the current point and the energy of the previous point) for each candidate point, the point with the largest slope is selected as the potential principal path, thus distinguishing between the principal path and delayed multipaths and avoiding misjudgments. Local peak detection (energy concentration) is performed. By performing sliding window peak detection within the window, candidate points with energy values ​​significantly higher than neighboring points are selected, thereby eliminating false peaks caused by noise or interference.

[0041] In this application, a secondary detection mechanism for the first diameter is introduced, which differs from the coarse first diameter detection function built into the DW series chips. This application introduces for the first time a CIR secondary first diameter detection method based on local peaks and rising slope, which greatly improves the accuracy of first diameter extraction.

[0042] In step S103, a second initial diameter detection is performed based on the energy characteristics, the slope characteristics, and the peak characteristics to obtain the initial diameter detection result.

[0043] It is understood that this application adopts a Kalman filter smoothing mechanism, introduces a filtering algorithm on the basis of corrected distance, inputs the corrected distance measurement value, predicts the current state based on the system model in the prediction stage, and merges the predicted value and the actual measurement value in the update stage, which significantly reduces the jitter of the distance measurement result in dynamic environment (suppresses random fluctuations), achieves the effect of reducing the fluctuation of the distance measurement value by about 10%, and improves the stability of the system in dynamic scenarios.

[0044] In one possible implementation, the first diameter detection result is the true first diameter position. The energy features, slope features, and peak features corresponding to each of the multiple candidate points are fused to obtain a comprehensive score for each candidate point; the candidate point with the highest score among the multiple comprehensive scores is taken as the true first diameter position.

[0045] Specifically, energy, slope, and peak features are weighted and fused to construct a comprehensive scoring function, thereby outputting the candidate point with the highest score as the true first diameter position.

[0046] In step S104, the target distance value is obtained by correcting or calculating based on the initial diameter detection result.

[0047] In one possible implementation, energy percentage analysis is performed based on the true first diameter position and the CIR information to obtain the actual energy percentage; if the actual energy percentage is less than a set energy percentage, the true first diameter position is corrected to obtain the target ranging value; if the actual energy percentage is greater than or equal to the set energy percentage, the target ranging value is calculated based on the true first diameter position.

[0048] Specifically, in the first-path secondary detection stage, after accurately identifying the true first-path position, the signal energy value corresponding to that path is extracted. The first-path energy is obtained through CIR (Channel Impulse Response) curve integration or peak sampling. The energy is then integrated across the entire CIR curve to obtain the total channel energy. The proportion of first-path energy to total energy is calculated, i.e., actual energy proportion = first-path energy / total channel energy. An evaluation is then performed. If the actual energy proportion is low (e.g., <30%), indicating strong multipath interference, a ranging correction mechanism (e.g., a compensation algorithm based on first-path offset) is activated. If the actual energy proportion is high (e.g., >70%), indicating weak environmental interference, the detection result is used directly.

[0049] It should be noted that the ranging value is the physical distance between the tag and the base station calculated based on the actual first-path location. Furthermore, in the process of directly using the first-path detection results to calculate the target ranging value, the target ranging value... d The calculation formula is: d = ct 首径 ;in, c At the speed of light,t 首径 The time corresponding to the actual first diameter position. d This is the distance measurement value.

[0050] In one possible implementation, a time delay offset is obtained based on the true first diameter position and the initial first diameter index; a corrected ranging value is obtained based on the time delay offset and the true first diameter position; and the corrected ranging value is smoothed to obtain the target ranging value.

[0051] Specifically, the time delay offset Δ caused by multipath is estimated by using the difference between the second detection result of the first path and the initial index. t Δ t=t 二次检测首径 - t 初始首径 .in, t 二次检测首径 The time corresponding to the actual first diameter position to be corrected. t 初始首径 This corresponds to the time of the initial first-path index. The target ranging value is then calculated using the actual first-path position to be corrected and the time delay offset. d 修正后 = d 待修正 -Δ tc ;in, d 修正后 This is the corrected target ranging value. d 待修正 The distance measurement value to be corrected; d 待修正 = ct 二次检测首径 .

[0052] Understandably, single-base station ranging is used to obtain the straight-line distance from the tag to the base station. Specifically, each UWB base station calculates the straight-line distance (i.e., the ranging value) from the tag to the base station by measuring the signal propagation time between the tag and the base station. Formula: di = ct ,in di For the tag to the i The distance between base stations c At the speed of light, t This is the signal propagation time, so each base station generates a distance measurement value independently.

[0053] See Figure 3 Kalman filter effect diagram and Figure 4 The schematic diagram of the effect of secondary first-path detection shows that this application is based on the error correction strategy of multipath environment assessment. By extracting features such as the first-path energy ratio and the initial first-path offset, the ranging error is modeled and corrected, thereby reducing the ranging deviation in complex environments.

[0054] Based on the above embodiments, this application also provides a base station, wherein the base station is a solution base station or a non-solution base station, and the solution base station or the non-solution base station is used to implement the steps of the UWB ranging method described in any of the above schemes.

[0055] The base station provided in this application is applied to the above-mentioned UWB ranging method and thus has all the beneficial effects of the above-mentioned UWB ranging method, which will not be repeated here.

[0056] Based on the above embodiments, this application also provides a UWB positioning method based on any one of the above schemes, wherein the UWB positioning method is applied to a base station.

[0057] The UWB ranging method described in the preferred embodiment of this application, such as Figure 5 As shown, the UWB ranging method includes the following steps: In step S201, local message information is acquired and sent to the non-decomputing base station, and remote message information is received from the non-decomputing base station. The non-decomputing base station includes a first base station and a second base station.

[0058] The local message information includes a local receive request timestamp, a local send response timestamp, and a local ranging end timestamp; the remote message information includes a first remote receive request timestamp and a first remote send response timestamp corresponding to the first base station, and a second remote receive request timestamp and a second remote send response timestamp corresponding to the second base station; the bidirectional ranging parameters include local bidirectional ranging parameters, first remote bidirectional ranging parameters, and second remote bidirectional ranging parameters.

[0059] In step S202, bidirectional ranging parameters are obtained based on the local message information and the remote message information.

[0060] It is worth noting that, such as Figure 6 As shown, in the basic interaction process of the symmetrical two-way ranging (TWR) mechanism, the UWB tag sequentially sends ranging request messages, and after receiving ranging response messages, sends a ranging end message. The UWB base station (either a calculating base station or a non-calculating base station) determines the ranging end time based on the round-trip time of the messages. T round1 , T reply1 (etc.) calculate propagation delay T prop Then, multiplying by the speed of light constant, the distance from the tag to the base station is derived. This mechanism effectively counteracts clock drift through two-way interaction, improving ranging accuracy, while utilizing the time difference of the local clock to avoid cumbersome time synchronization operations.

[0061] and ; It can be deduced that: ; Rearranging the terms, we get: ; The final result is: .

[0062] in, Indicates a delay in propagation; Indicates the round-trip time from tag request to base station response; Indicates the round-trip time from the end of the tag to the base station reception; This indicates the delay between the base station's response and the tag's reception. This indicates the delay from the end of tag transmission to the base station receiving the tag.

[0063] As can be seen from the previous formula, the key to calculating flight time is to obtain the time difference, which is obtained by subtracting the timestamps of the sent and received messages locally on each device.

[0064] like Figure 7 As shown, the non-resolution base stations include the first base station and the second base station. The tag carries its calculated time difference in the ranging end message, but the base station can only resolve the ranging distance for that round after receiving the last timestamp (the ranging end message). In a multi-base station deployment, the positioning resolution base station cannot directly obtain the timestamp information of other base stations by default. One solution is for each base station to carry the ranging value of the previous ranging cycle when sending the ranging response message. This method is simple and easy to implement, but because it mixes ranging results from different ranging cycles, it introduces positioning deviations due to inconsistent ranging times.

[0065] In one possible implementation, the difference between the local receive request timestamp and the first remote receive request timestamp is calculated, and the difference between the local receive request timestamp and the second remote receive request timestamp is calculated; a local ranging end message is obtained; based on the difference between the local ranging end message and the first receive request timestamp, a first remote ranging end message of the first base station is obtained; based on the difference between the local ranging end message and the second receive request timestamp, a second remote ranging end message of the second base station is obtained; based on the local receive request timestamp, the local transmit response timestamp, and the local ranging end timestamp, the local bidirectional ranging parameters between the solving base station and the target tag are calculated; based on the first remote receive request timestamp, the first remote transmit response timestamp, and the first remote ranging end message, a first remote bidirectional ranging parameter between the first base station and the target tag is calculated; based on the second remote receive request timestamp, the second remote transmit response timestamp, and the second remote ranging end message, a second remote bidirectional ranging parameter between the second base station and the target tag is calculated.

[0066] It is worth noting that in the timestamp broadcast synchronization mechanism of this application, each base station, when sending a response message, packages and broadcasts the timestamp of the current round of receiving request and the timestamp of sending response, which other base stations receive and cache. The solving base station can use the difference between its own and other base stations' receiving request timestamps to indirectly obtain the receiving time of the ranging end message of other base stations, thereby calculating the two required time differences. The positioning solving base station first calculates and records the timestamp difference between itself and other base stations when receiving ranging request messages; after receiving the ranging end message, it can deduce the ranging end timestamp of other base stations by subtracting the previously recorded difference. Thus, the positioning solving base station can obtain the three key timestamps of other base stations in this ranging cycle, thereby calculating the two time differences and further solving the ranging value between other base stations and the tag. This mechanism realizes the acquisition of synchronous ranging data from multiple base stations within the same ranging cycle, avoids the error introduced by mixing data from different cycles, and significantly improves positioning accuracy. This application adopts a cross-base station timestamp broadcast cooperative positioning mechanism, thereby proposing a cross-base station cooperative ranging method that does not require strict clock synchronization. This allows the positioning calculation base station to indirectly obtain the key timestamps of other base stations, and then calculate the ranging values ​​of other base stations, thus solving the error accumulation problem caused by the asynchronous ranging cycle in traditional systems.

[0067] Specifically, see Figure 6 The tag sends a ranging request message and records a timestamp. T 1. Calculate the response message sent by the base station after receiving the request and record the timestamp. T 2 (receive request, i.e., local receive request timestamp) andT 3 (Send response, i.e., local response timestamp); After receiving the response, the tag sends an end message and records the timestamp. T 4 (receiving response) and T 5 (End of transmission); The base station receives the end message and records the timestamp. T 6 (i.e., the local ranging end timestamp). Time difference calculation: = T 3 -T 1 (Round-trip time from tag request to tag reception message); = T 4 -T 3 (Delay from base station response to base station sending of message); = T6-T5 (Round-trip time from the end of tag reception to the tag sending of the message); = T 5 -T 4 (Delay from base station sending a message to base station receiving it). See also Figure 6 and Figure 7 The tag receiving the ranging response message is the time when the tag receives the message; the tag sending the ranging end message is the time when the tag sends the message; and the base station sending the ranging response message is the time when the base station sends the message. It is important to distinguish between the sending and receiving times, as there is a time difference (i.e., time of flight) between these two times. Figure 7 middle, The round-trip time from tag request to tag receiving and parsing base station messages. The round-trip time from when the tag requests the message from the first base station to when the tag receives the message. The round-trip time from when the tag requests a message from the second base station to when the tag receives the message from the second base station; The delay between the end of tag reception and the tag sending a message to the calculation base station. The delay between the end of tag reception and the tag sending a message to the first base station. The delay between the end of tag reception and the tag sending a message to the second base station; To calculate the delay between the base station's response and the base station's message transmission, The delay from the first base station's response to the first base station sending the message. The delay in the second base station's response to the second base station sending the message; To calculate the round-trip time from when a base station sends a message to when it receives it, The round-trip time from when the first base station sends a message to when the first base station receives it. The round-trip time for sending a message from the second base station to receiving it from the second base station.

[0068] This application employs a timestamp broadcast synchronization mechanism (key to multi-base station collaboration) to address the positioning error caused by the mixing of data from different ranging periods in traditional methods. This is achieved by each base station including the request reception time for the current ranging round in its response message. T 2) and response sending time ( T 3); Collect timestamps from other base stations and record the request reception time difference between the local machine and each base station ( ΔT=T local2 -T remote2 ), T local2 Indicates the timestamp received by the local request. T remote2 Indicates the remote request to receive timestamp; when the base station finishes receiving the message ( T local2 After (indicating the local ranging end timestamp), via ΔT Calculate the end time of other base stations ( T remote6 =T local6 -ΔT ),in, T remote6 This indicates the timestamp indicating the end of remote ranging.

[0069] Understandably, the solution base station calculates the difference between its own and other base stations' (first base station, second base station) receive request timestamps, and then, after receiving the ranging end message sent by the tag, uses the calculated receive request timestamp difference to infer the time when other base stations received the ranging end message; the solution base station calculates the bidirectional ranging parameters between all base stations and the tag using the three core timestamps of all base stations. , This ensures that all data belong to the same ranging period.

[0070] In step S203, the target ranging value of the first base station and the target ranging value of the second base station are received under the same ranging period according to the bidirectional ranging parameters.

[0071] After determining the same ranging period, the target ranging value corresponding to each base station is obtained according to the above UWB ranging method.

[0072] In step S204, positioning data is obtained based on the target ranging value of the calculated base station, the target ranging value of the first base station, and the target ranging value of the second base station under the same ranging period.

[0073] Specifically, during the positioning calculation process, the synchronous ranging values ​​of all base stations are input, and a multilateral positioning algorithm (such as the least squares method) is used to calculate the tag position (the marked positioning coordinates) by combining the base station coordinates. As a result, the positioning accuracy of this application is significantly improved in dynamic scenarios, making it suitable for scenarios where the target moves frequently.

[0074] It should be noted that two-dimensional positioning requires at least three non-collinear base stations, each providing one ranging value (corresponding to one circle), and the intersection of the three circles uniquely determines the planar coordinates. Three-dimensional positioning requires at least four non-coplanar base stations, each providing one ranging value (corresponding to one sphere), and the intersection of the four spheres uniquely determines the spatial coordinates. In this application embodiment, the non-resolver base stations can be two, three, or more.

[0075] Based on the above embodiments, this application also provides a UWB system, wherein the UWB system includes a solution base station, a non-solution base station, and a target tag, the non-solution base station includes a first base station and a second base station, the target tag is a device installed on a target object, and the solution base station, the first base station, the second base station are arranged opposite to the target tag; the solution base station is used to implement the UWB positioning method as described in the above scheme.

[0076] The UWB system provided in this application is applied to the above-mentioned UWB positioning method and thus has all the beneficial effects of the above-mentioned UWB positioning method, which will not be repeated here.

[0077] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0078] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0079] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0080] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable storage medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable storage medium could be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0081] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0082] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it includes one or a combination of the steps of the method embodiments.

[0083] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0084] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

[0085] It should be understood that the application of this application is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A UWB ranging method, characterized in that, The UWB ranging method includes: Obtain the CIR information of the target label, and perform preliminary first path detection on the CIR information to obtain the initial first path index; Energy characteristics, slope characteristics, and peak characteristics are obtained based on the CIR information and the initial first diameter index; Based on the energy characteristics, slope characteristics, and peak characteristics, a second initial diameter detection is performed to obtain the initial diameter detection result. The target distance value is obtained by correcting or calculating based on the initial diameter detection results.

2. The UWB ranging method according to claim 1, characterized in that, The CIR information includes the CIR curve; The process of obtaining energy features, slope features, and peak features based on the CIR information and the initial first-path index specifically includes: A local detection window is formed on the CIR curve based on the initial first diameter index; Feature analysis is performed on multiple points within the local detection window to obtain the energy features, slope features, and peak features corresponding to each candidate point.

3. The UWB ranging method according to claim 2, characterized in that, The energy characteristic is the energy value, the slope characteristic is the slope, and the peak characteristic is the peak value; The step of performing feature analysis on multiple points within the local detection window to obtain the energy features, slope features, and peak features corresponding to each candidate point specifically includes: Calculate the energy value of all points within the local detection window, and select multiple points whose energy value is greater than a set dynamic threshold as multiple candidate points; Calculate the slope of each candidate point within the local detection window; Peak detection is performed within the local detection window to obtain the peak value of each candidate point.

4. The UWB ranging method according to claim 2, characterized in that, The initial diameter detection result is the true initial diameter position; The step of performing secondary first-diameter detection based on the energy characteristics, slope characteristics, and peak characteristics to obtain the first-diameter detection result specifically includes: The energy features, slope features and peak features corresponding to each of the multiple candidate points are respectively fused to obtain the comprehensive score corresponding to each of the multiple candidate points; The candidate point corresponding to the highest score among the multiple comprehensive scores is taken as the true first diameter position.

5. The UWB ranging method according to claim 4, characterized in that, The step of correcting or calculating based on the initial diameter detection result to obtain the target ranging value specifically includes: Based on the actual first diameter position and the CIR information, an energy percentage analysis is performed to obtain the actual energy percentage. If the actual energy percentage is less than the set energy percentage, the true first diameter position is corrected to obtain the target ranging value. If the actual energy percentage is greater than or equal to the set energy percentage, then the target ranging value is calculated based on the true first diameter position.

6. The UWB ranging method according to claim 5, characterized in that, The step of correcting the true initial diameter position to obtain the target ranging value specifically includes: The time delay offset is obtained based on the actual first diameter position and the initial first diameter index; The corrected ranging value is obtained based on the time delay offset and the true first diameter position; The corrected ranging value is smoothed to obtain the target ranging value.

7. A base station, characterized in that, The base station is either a solution base station or a non-solution base station, and the solution base station or the non-solution base station is used to implement the steps of the UWB ranging method according to any one of claims 1 to 6.

8. A UWB positioning method based on the UWB ranging method according to any one of claims 1-6, characterized in that, The method is applied to base station calculations; the UWB positioning method includes: Acquire local message information and send it to a non-decomputing base station, and receive remote message information from the non-decomputing base station; wherein, the non-decomputing base station includes a first base station and a second base station; Based on the local message information and the remote message information, the bidirectional ranging parameters are obtained; Based on the bidirectional ranging parameters, the target ranging value of the first base station and the target ranging value of the second base station are received in the same ranging period; Positioning data is obtained by calculating the target ranging value of the base station, the target ranging value of the first base station, and the target ranging value of the second base station under the same ranging period.

9. The UWB positioning method according to claim 8, characterized in that, The local message information includes a local receive request timestamp, a local send response timestamp, and a local ranging end timestamp. The remote message information includes a first remote receive request timestamp, a first remote send response timestamp, and a second remote receive request timestamp and a second remote send response timestamp, corresponding to the first base station. The bidirectional ranging parameters include local bidirectional ranging parameters, first remote bidirectional ranging parameters, and second remote bidirectional ranging parameters. The step of obtaining the bidirectional ranging parameters based on the local message information and the remote message information specifically includes: Calculate the difference between the local receive request timestamp and the first remote receive request timestamp, and calculate the difference between the local receive request timestamp and the second remote receive request timestamp. Obtain a local ranging end message; based on the difference between the local ranging end message and the timestamp of the first receiving request, obtain a first remote ranging end message of the first base station; and based on the difference between the local ranging end message and the timestamp of the second receiving request, obtain a second remote ranging end message of the second base station. Based on the local receive request timestamp, the local send response timestamp, and the local ranging end timestamp, the local bidirectional ranging parameters between the solving base station and the target tag are calculated. Based on the first remote receive request timestamp, the first remote send response timestamp, and the first remote ranging end message, the first remote bidirectional ranging parameters between the first base station and the target tag are calculated. Based on the second remote receive request timestamp, the second remote send response timestamp, and the second remote ranging end message, the second remote bidirectional ranging parameters between the second base station and the target tag are calculated.

10. A UWB system, characterized in that, The UWB system includes a solution base station, a non-solution base station, and a target tag. The non-solution base station includes a first base station and a second base station. The target tag is a device installed on a target object. The solution base station, the first base station, and the second base station are arranged opposite to the target tag. The solution base station is used to implement the steps of the UWB positioning method as described in claim 8 or 9.

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