Digital key positioning method, device, equipment and storage medium

Abstract

The present invention discloses a digital key positioning method, device, equipment and storage medium. The method includes: obtaining the ranging value between all anchor points on the vehicle and the digital key in the current epoch; determining the positioning mode of the extended Kalman filter EKF according to the number of valid anchor points among all the anchor points; the valid anchor point is the anchor point to which the ranging value can be referenced; performing time update according to the target positioning solution or initial positioning solution of the previous epoch by the EKF to obtain the predicted positioning solution of this epoch; determining whether to perform measurement update according to the positioning mode of the EKF, if so, performing measurement update on the predicted positioning solution to obtain the target positioning solution of the digital key in this epoch, otherwise the predicted positioning solution is used as the target positioning solution of the digital key in this epoch. The method can improve the accuracy of positioning the digital key by determining the positioning mode of the EKF according to the number of valid anchor points and determining the positioning solution of the digital key by the EKF.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of digital key technology, and in particular to a digital key positioning method, device, equipment and storage medium. Background Art

[0002] Ultra Wide Band (UWB) digital car key is an innovative technology for modern car safety and convenience. UWB uses ultra-wideband wireless communication technology to provide high-precision positioning and powerful data transmission capabilities. Compared with traditional Bluetooth Low Energy (BLE) digital keys, UWB technology has greatly improved positioning accuracy and stability, bringing a better experience for the application of digital keys in daily life.

[0003] However, UWB positioning still has some shortcomings in special environments, especially when applied to digital keys. Since the number and distribution of UWB anchor points must take into account the structure and cost of the vehicle itself, 4-5 anchor points are usually arranged around the vehicle body and inside the vehicle. This will cause the digital key to be easily in the signal blind spot of some of the anchor points. In fact, only 2-3 anchor points, or even 1 anchor point, can be used for positioning, and it is likely to be a non-line-of-sight signal. Although the UWB technology has high ranging accuracy, high-precision positioning is still a big challenge when there are few anchor points and the signal is blocked. Summary of the invention

[0004] The present invention provides a digital key positioning method, device, equipment and storage medium to solve the problem that the positioning method in the prior art cannot accurately position when the number of anchor points is small.

[0005] According to one aspect of the present invention, a digital key positioning method is provided, the method comprising:

[0006] Get the distance values ​​between all anchor points on the vehicle and the digital key in the current epoch;

[0007] Determine the positioning mode of the extended Kalman filter EKF according to the number of valid anchor points among all the anchor points; the valid anchor point is an anchor point to which the ranging value can be referenced, and the positioning mode includes a recursive mode, a partial observation mode and a full observation mode;

[0008] The EKF performs time updating according to the target positioning solution or the initial positioning solution of the previous epoch to obtain the predicted positioning solution of the current epoch;

[0009] Determine whether to perform measurement update according to the positioning mode of the EKF. If so, the predicted positioning solution is measured and updated to obtain the target positioning solution of the digital key in this epoch. Otherwise, the predicted positioning solution is used as the target positioning solution of the digital key in this epoch.

[0010] According to another aspect of the present invention, a digital key positioning device is provided, the device comprising:

[0011] The acquisition module is used to obtain the distance values ​​between all anchor points on the vehicle and the digital key in the current epoch;

[0012] A first determination module is used to determine a positioning mode of an extended Kalman filter EKF according to the number of valid anchor points among all the anchor points; the valid anchor points are anchor points to which the ranging value can be referenced, and the positioning mode includes a recursive mode, a partial observation mode, and a full observation mode;

[0013] An updating module, used for performing time updating according to the target positioning solution or the initial positioning solution of the previous epoch through the EKF to obtain a predicted positioning solution of this epoch;

[0014] The second determination module is used to determine whether to perform measurement update according to the positioning mode of the EKF. If so, the predicted positioning solution is measured and updated to obtain the target positioning solution of the digital key in this epoch; otherwise, the predicted positioning solution is used as the target positioning solution of the digital key in this epoch.

[0015] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising: at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the digital key positioning method described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the digital key positioning method described in any embodiment of the present invention when executed.

[0019] A digital key positioning method, device, equipment and storage medium according to an embodiment of the present invention, the method includes: obtaining the distance measurement value between all anchor points on the vehicle and the digital key in the current epoch; determining the positioning mode of the extended Kalman filter EKF according to the number of valid anchor points among all the anchor points; the valid anchor point is the anchor point that the distance measurement value can refer to, and the positioning mode includes a recursive mode, a partial observation mode and a full observation mode; the EKF performs time update according to the target positioning solution or the initial positioning solution of the previous epoch to obtain the predicted positioning solution of this epoch; according to the positioning mode of the EKF, determine whether to perform measurement update, if so, measure and update the predicted positioning solution to obtain the target positioning solution of the digital key in this epoch, otherwise, use the predicted positioning solution as the target positioning solution of the digital key in this epoch. The method can improve the accuracy of positioning the digital key by determining the positioning mode of the EKF according to the number of valid anchor points and determining the positioning solution of the digital key through the EKF, and solves the problem that the positioning method in the prior art cannot accurately locate when the number of anchor points is small.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0022] Figure 1 A schematic diagram of a flow chart of a digital key positioning method provided in Embodiment 1 of the present invention;

[0023] Figure 2 A schematic diagram of a flow chart of a digital key positioning method provided in Embodiment 2 of the present invention;

[0024] Figure 3 A schematic diagram of a flow chart of a digital key positioning method provided by an embodiment of the present invention;

[0025] Figure 4 A result diagram of a static test performed by an existing method provided by an embodiment of the present invention;

[0026] Figure 5 A result diagram of a static test performed by the method provided by an embodiment of the present invention;

[0027] Figure 6 A result diagram of an experiment of approaching and moving away from a vehicle using an existing method provided in an embodiment of the present invention;

[0028] Figure 7 A result diagram of an experiment of approaching and moving away from a vehicle using the method provided in an embodiment of the present invention;

[0029] Figure 8 A result diagram of a car-walking experiment performed by an existing method provided in an embodiment of the present invention;

[0030] Fig. 9 A result diagram of a walk-around test performed by the method provided in an embodiment of the present invention;

[0031] Fig.10 A schematic diagram of the structure of a digital key positioning device provided in Embodiment 3 of the present invention;

[0032] Fig.11 Schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only an embodiment of a part of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work should belong to the scope of protection of the present invention. It should be understood that the various steps recorded in the method implementation of the present invention can be performed in different orders and / or in parallel. In addition, the method implementation may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0034] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0035] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, any variations of the terms "including" and "having" are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0036] It should be noted that the modifications of "one" and "plurality" mentioned in the present invention are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0037] The names of the messages or information exchanged between multiple devices in the embodiments of the present invention are only used for illustrative purposes, and are not used to limit the scope of these messages or information.

[0038] Embodiment 1

[0039] Figure 1 The present invention provides a flowchart of a digital key positioning method according to the first embodiment of the present invention. The method is applicable to the situation of positioning a digital key. The method can be performed by a digital key positioning device, wherein the device can be implemented by software and / or hardware and is generally integrated on an electronic device. In this embodiment, the electronic device includes but is not limited to: a vehicle computer or other computers and other devices. Figure 1 As shown, a digital key positioning method provided in Embodiment 1 of the present invention includes the following steps:

[0040] S110. Obtaining distance values ​​between all anchor points on the vehicle and the digital key in the current epoch.

[0041] Among them, epochs can refer to different moments of data collection, and this embodiment will process the data collected in each epoch. The vehicle can be a vehicle corresponding to the data key. The anchor point can be a UWB anchor point, and the number of anchor points can be set according to actual conditions. The anchor point can be installed on a device associated with the data key (such as a vehicle). The ranging value can be the distance between the anchor point and the digital key, and each anchor point has a corresponding ranging value.

[0042] In this embodiment, the ranging values ​​between all anchor points on the vehicle and the digital key in the current epoch may be obtained, for example, the Channel Impulse Response (CIR) information of all anchor points may be obtained, and the ranging values ​​between the anchor points and the digital key may be obtained according to the CIR information.

[0043] In one embodiment, after obtaining the ranging values ​​between all anchor points on the vehicle and the digital key in the current epoch, the method further includes: determining an initial positioning solution of the digital key based on the ranging values ​​of valid anchor points among all anchor points; when the EKF needs to be initialized, using the initial positioning solution as the initial value of the state quantity of the EKF, and initializing the parameters of the EKF.

[0044] Among them, the parameters of EKF may include system matrix, observation matrix, system noise and initial value of state covariance.

[0045] In this embodiment, the initial positioning solution of the digital key can be determined by solving equations or least squares algorithm according to the ranging values ​​of the effective anchor points. For example, when the number of ranging values ​​is two, the equation can be solved; when the number of ranging values ​​is three or more, the least squares algorithm can be used. After that, it can be determined whether the EKF needs to be initialized. When the EKF needs to be initialized, the calculated initial positioning solution is used as the initial value of the state quantity of the EKF, and the parameters of the EKF are initialized.

[0046] This embodiment uses the initial positioning solution as the initial value of the EKF state quantity when the EKF needs to be initialized, so that when the time update is performed later, the initial positioning solution can be regarded as the target positioning solution of the previous epoch, thereby improving the accuracy of the time update.

[0047] S120. Determine a positioning mode of an extended Kalman filter EKF according to the number of valid anchor points among all the anchor points; the valid anchor points are anchor points to which the ranging values ​​can be referenced, and the positioning modes include a recursive mode, a partial observation mode, and a full observation mode.

[0048] Among them, the valid anchor point may refer to an anchor point to which the ranging value can refer. Specifically, whether the anchor point is valid can be determined by whether the ranging value of the anchor point is 0, or by whether the block index flag in the anchor point CIR information increases continuously. This embodiment does not limit this. The Extended Kalman Filter (EKF) is an efficient nonlinear system recursive filter that can estimate the state of the system from a series of measurements that do not completely contain noise through the relationship between the system and the measurement. The positioning mode can be a mode for positioning the data key. Depending on the number of valid anchor points, the EKF in this embodiment has multiple different positioning modes.

[0049] In this embodiment, whether the anchor point is valid can be determined based on whether the ranging value can be used as a reference, and the EKF positioning mode can be determined by the number of valid anchor points among all anchor points. For example, when the ranging value of the anchor point is 0, the ranging value at this time cannot be used to locate the digital key, the ranging value may be wrong, and the anchor point is considered to be an invalid anchor point.

[0050] In one embodiment, determining the positioning mode of the extended Kalman filter EKF according to the number of valid anchor points among all the anchor points includes: when the number of valid anchor points is 0, determining that the positioning mode of the EKF is a recursive mode; when the number of valid anchor points is less than the dimension of the EKF state quantity and is not equal to 0, determining that the positioning mode of the EKF is a partial observation mode; when the number of valid anchor points is greater than or equal to the dimension of the EKF state quantity, determining that the positioning mode of the EKF is a full observation mode.

[0051] The EKF state quantity can be understood as a positioning solution, and the dimension of the state quantity is the number of position parameters in the positioning solution. When the positioning solution is a two-dimensional coordinate, the dimension of the EKF state quantity is 2.

[0052] In this embodiment, the positioning mode is divided into a recursive mode, a partial observation mode and a full observation mode. The recursive mode may refer to a mode for inferring the current positioning solution based on the positioning solution of the previous epoch, because in the recursive mode, the number of valid anchor points is 0, and positioning cannot be performed based on the ranging value at this time, so the recursive mode is to infer the current solution through the solution of the previous epoch. When the number of valid anchor points (ranging values) is less than the dimension of the EKF state quantity (the dimension of the state quantity to be solved), it cannot be completely solved at this time, so the EKF positioning mode can only be set to a partial solution mode. When the number of valid anchor points is greater than or equal to the dimension of the EKF state quantity, it means that the state quantity can be solved based on the ranging value, and the positioning mode can be set to the full observation mode at this time. By setting different positioning modes, this embodiment can solve in different ways according to the different numbers of valid anchor points detected in actual situations, which can increase the accuracy of positioning.

[0053] S130, performing time update according to the target positioning solution or the initial positioning solution of the previous epoch through the EKF to obtain a predicted positioning solution of the current epoch.

[0054] The target positioning solution may be a positioning solution obtained by calculation such as time update. The initial positioning solution may be a positioning solution determined by the ranging value of the effective anchor point. The time update may be a method of calculating the prior estimation value of the state variable and the prior estimation value of the error covariance at the current moment based on the state estimation value at the previous moment. The predicted positioning solution may be a prediction of the positioning solution.

[0055] In this embodiment, time updating can be performed through EKF, that is, the target positioning solution or initial positioning solution of the previous epoch is used as the initial value of the state quantity to predict the state quantity of this epoch, and the predicted state quantity is used as the predicted positioning solution.

[0056] S140. Determine whether to perform measurement update according to the positioning mode of the EKF. If so, perform measurement update on the predicted positioning solution to obtain the target positioning solution of the digital key in this epoch. Otherwise, use the predicted positioning solution as the target positioning solution of the digital key in this epoch.

[0057] In this embodiment, the type of the EKF positioning model can be used to determine how to obtain the target positioning solution of the digital key in this epoch by predicting the positioning solution.

[0058] A digital key positioning method provided in the first embodiment of the present invention includes: obtaining the distance measurement value between all anchor points on the vehicle and the digital key in the current epoch; determining the positioning mode of the extended Kalman filter EKF according to the number of valid anchor points among all the anchor points; the valid anchor point is the anchor point to which the distance measurement value can be referenced, and the positioning mode includes a recursive mode, a partial observation mode and a full observation mode; performing time update according to the target positioning solution or the initial positioning solution of the previous epoch by the EKF to obtain the predicted positioning solution of this epoch; determining whether to perform measurement update according to the positioning mode of the EKF, if so, performing measurement update on the predicted positioning solution to obtain the target positioning solution of the digital key in this epoch, otherwise using the predicted positioning solution as the target positioning solution of the digital key in this epoch. The method can improve the accuracy of positioning the digital key by determining the positioning mode of the EKF according to the number of valid anchor points and determining the positioning solution of the digital key by the EKF, and solves the problem that the positioning method in the prior art cannot accurately locate when the number of anchor points is small.

[0059] Embodiment 2

[0060] Figure 2 This is a flow chart of a digital key positioning method provided by the second embodiment of the present invention. The second embodiment is optimized on the basis of the above embodiments. For details not yet fully described in this embodiment, please refer to the first embodiment. Figure 2 As shown, a digital key positioning method provided by Embodiment 2 of the present invention includes the following steps:

[0061] S210: Obtain the distance measurement values ​​between all anchor points on the vehicle and the digital key in the current epoch.

[0062] S220. Determine a positioning mode of an extended Kalman filter EKF according to the number of valid anchor points among all the anchor points; the valid anchor points are anchor points to which the ranging values ​​can be referenced, and the positioning modes include a recursive mode, a partial observation mode, and a full observation mode.

[0063] S230, performing time update according to the target positioning solution or the initial positioning solution of the previous epoch through the EKF to obtain a predicted positioning solution of the current epoch.

[0064] S240: Determine whether to perform measurement update according to the positioning mode of the EKF.

[0065] Among them, measurement update is a calculation process in Kalman filtering, which can include processes such as calculating Kalman gain, state update and covariance update. Measurement update is responsible for combining the prior estimate and the new measurement variable to construct an improved posterior estimate.

[0066] In this embodiment, whether measurement update is required may be determined according to the type of the EKF positioning mode.

[0067] In one embodiment, when the positioning mode of the EKF is the recursive mode, it is determined that measurement update is not required; when the positioning mode of the EKF is the partial observation mode or the full observation mode, it is determined that measurement update is required. In this embodiment, when the positioning mode is the recursive mode, only time update is performed, and when the positioning mode is the partial observation mode and the full observation mode, time update and measurement update are performed.

[0068] S250: If yes, then measure and update the EKF to obtain a positioning solution change, and update the predicted positioning solution according to the positioning solution change to obtain the target positioning solution of the digital key in this epoch; otherwise, use the predicted positioning solution as the target positioning solution of the digital key in this epoch.

[0069] The positioning solution change amount may be a change in the positioning solution.

[0070] In this embodiment, when the positioning mode of the EKF is a partial observation mode or a full observation mode, the EKF can continue to perform measurement updates to obtain the change in the positioning solution, and the predicted positioning solution can be updated according to the change in the positioning solution to obtain the target positioning solution of the digital key in this epoch. When the positioning mode of the EKF is a recursive mode, since measurement updates cannot be performed in the recursive mode, the predicted positioning solution can be directly used as the target positioning solution of the digital key in this epoch.

[0071] A digital key positioning method provided in the second embodiment of the present invention specifically obtains the target positioning solution of the digital key in this epoch after measuring and updating the predicted positioning solution, including: obtaining the positioning solution change through EKF measurement update, updating the predicted positioning solution according to the positioning solution change, and obtaining the target positioning solution of the digital key in this epoch. This method dynamically selects the positioning mode of EKF according to the number of observations, and determines whether measurement update is required according to the type of positioning mode. Therefore, when the number of observations is less than the state quantity dimension and neither equation solving nor least squares method can be solved, the positioning result can still be output by EKF, which increases the number of positioning when the signal is lost for a short time under weak signal, and improves the flexibility of EKF output positioning solution.

[0072] Based on the above embodiment, a variant embodiment of the above embodiment is proposed. It should be noted that in order to make the description concise, only the differences from the above embodiment are described in the variant embodiment.

[0073] In one embodiment, the measurement update by EKF to obtain the change in positioning solution includes: taking the ranging values ​​of all valid anchor points of this epoch as observation quantities; determining the observation noise corresponding to the observation quantity according to the sliding standard deviation and the line of sight state of the observation quantity; and performing the measurement update of EKF in turn using each observation quantity and the corresponding observation noise through a sequential processing method to obtain the change in positioning solution.

[0074] Among them, the observation value may refer to the sample value obtained by measurement or determination. The sliding standard deviation may be calculated by sliding window or by other means. The line of sight (LOS) may be a state used to indicate whether the line of sight between the anchor point and the digital key is blocked. Observation noise may be random interference introduced during the measurement process, which affects the accuracy and reliability of the measurement value. Sequential processing method is a commonly used strategy in data processing and analysis. This method can gradually complete the entire processing process by decomposing the task into a series of ordered steps.

[0075] In this embodiment, when the measurement is updated through EKF, the ranging values ​​of all valid anchor points in this epoch can be used as observation quantities, and the observation noise corresponding to the observation quantity can be dynamically estimated through the sliding standard deviation of the observation quantity and the line-of-sight state. Then, each observation quantity and the corresponding observation noise are used in turn through a sequential processing method to perform measurement updates until the final positioning solution change is obtained.

[0076] In this embodiment, when the positioning mode is a partial observation mode and a full observation mode, the observations are first sorted according to the LOS state and sliding standard deviation (stability) of the observations, and then sequentially processed one by one. By sequentially processing, the use of the observations can be made more flexible. When the number of observations needs to be changed, there is no need to repeat the calculation, which reduces the amount of calculation.

[0077] In one embodiment, after using each observation quantity and the corresponding observation noise to perform measurement update of the EKF, the method further includes: if the residual of this measurement update is greater than the residual threshold, dynamically adjusting the observation noise corresponding to the observation quantity according to the residual, and reusing the observation quantity and the adjusted observation noise for measurement update; if the residual corresponding to the observation quantity is still greater than the residual threshold after the observation quantity is re-measured and updated more than a preset number of times, then discarding the observation quantity.

[0078] The residual may be the difference between the change in the positioning solution and the estimated change. The residual threshold may be set according to actual conditions. When the residual is greater than the residual threshold, it indicates that the error caused by the observation is large. The preset number of times may be set according to actual conditions, and may be set to 1 or 2 times.

[0079] In this embodiment, after each observation is used to perform measurement update to obtain the change in positioning solution, the residual of the observation can be calculated by the change in positioning solution and the preset estimated change. If the residual is greater than the residual threshold, it means that the error caused by this update is large. At this time, the observation noise corresponding to the observation can be dynamically adjusted according to the residual; and the adjusted observation noise is used again to perform measurement update of the observation. If the residual of the observation obtained after the update still does not meet the requirements, the observation can be discarded and the change in positioning solution obtained by the observation is not used.

[0080] In one embodiment, the method also includes: calculating the degrees of freedom based on the dimensions of the EKF state quantity and the dimensions of the observation quantity actually used; updating the positioning mode of the EKF of this epoch based on the degrees of freedom; when the updated positioning mode is a recursive mode or a partial observation mode, recording the number of continuous positioning epochs in the recursive mode or the partial observation mode; when the number of continuous positioning epochs is greater than an epoch number threshold, exiting the recursive mode or the partial observation mode in the next epoch.

[0081] The degree of freedom may be the difference between the dimension of the observation quantity and the dimension of the state quantity. The number of continuous positioning epochs may be the number of epochs of continuous positioning in a certain mode. The epoch number threshold may be set according to actual conditions.

[0082] In this embodiment, after the measurement update, there may be discarded observations, and the number of observations actually used may change. Therefore, the degree of freedom can be calculated by the dimension of the EKF state quantity and the dimension of the observation quantity actually used, and the actual positioning mode of the EKF is updated again by the degree of freedom, and subsequent calculations are performed according to the actual positioning mode. When the updated positioning mode is a recursive mode or a partial observation mode, the number of continuous positioning epochs in the recursive mode or the partial observation mode can be recorded. When the number of continuous positioning epochs is greater than the epoch number threshold, the obtained positioning solution may have errors, and the recursive mode or the partial observation mode needs to be exited in the next epoch.

[0083] This embodiment records the number of continuous positioning epochs in the recursive mode or the partial observation mode. When the number of continuous positioning epochs is greater than the epoch number threshold, the update of the mode is stopped, thereby reducing the risk of gradually increasing positioning solution drift errors in the case of long-term recursive mode or partial observation mode.

[0084] In one embodiment, after obtaining the target positioning solution of the digital key in this epoch, the method also includes: performing static detection on the digital key to obtain a static detection result; when the static detection result is static, determining whether to release the static constraint based on the constraint duration of this static state and the interval distance between the target positioning solution of this epoch and the initial constraint positioning solution; if not, using the initial constraint positioning solution as the new target positioning solution of this epoch.

[0085] Among them, static detection can be a detection of whether the digital key is static, and the method of static detection is not limited in this embodiment. Static detection results may include static and dynamic. For example, static detection can be performed by the standard deviation of the ranging value of the anchor point and the number of anchor points. The constraint duration can be the duration when the digital key is static. The initial constraint positioning solution can be a target positioning solution for initially judging that the digital key is static during a static constraint process.

[0086] In this embodiment, the digital key can also be statically detected. Specifically, the standard deviation of the distance measurement value of the anchor point and the number of anchor points can be used to perform static detection to obtain a static detection result. When the static detection result is static, it can be further determined whether to release the static constraint based on the static constraint duration and the interval distance between the target positioning solution of this epoch and the initial constraint positioning solution. For example, if the constraint duration is greater than a certain threshold, such as 3 seconds, or the interval distance is greater than a certain threshold, such as 1 meter, the static constraint is released, the new target positioning solution is used as the final result, and the constraint duration T is reset. If the static constraint is not released, it means that the position of the digital key has not changed, and the calculated target positioning solution may have errors, then the initial constraint positioning solution is used as the new target positioning solution of this epoch. Exemplarily, when the digital key is detected to be static, the EKF can be statically constrained, the state quantity X(i) of the epoch is recorded and the number of epochs of this continuous static state is counted. When the digital key is continuously static, during static detection, the distance between the state quantity X(k) and X(i) updated each time can be tracked, and whether it is static can be comprehensively considered. When it is determined that the digital key is static, the fixed coordinate value X(i) is output, and X(i) is used as the target positioning solution of this epoch to reduce drift in static positioning.

[0087] In one embodiment, after obtaining the target positioning solution of the digital key in this epoch, the method also includes: performing quality control on the target positioning solution to obtain a quality control result; determining the confidence of the target positioning solution based on the current covariance matrix and positioning mode of the EKF; when the confidence and the quality control result both meet the conditions, filtering the target positioning solution and outputting the positioning result of this epoch after filtering; otherwise, reinitializing the EKF in the next epoch.

[0088] Among them, quality control can be a way to determine whether the target positioning solution meets the quality requirements. The quality control results can include pass and fail. The confidence level can indicate the authenticity of the target positioning solution.

[0089] In this embodiment, the target positioning solution can be quality controlled to obtain a quality control result. This embodiment does not limit the way of performing quality control. For example, the target positioning solution can be quality controlled based on the target positioning solution of the most recent N epochs and the ranging values ​​of all anchor points in this epoch to obtain a quality control result. Afterwards, the confidence of the target positioning solution can be estimated based on the current covariance matrix and positioning mode of the EKF. When the confidence reaches a certain threshold and the quality control result is passed, the target positioning solution can be filtered and the positioning result of this epoch after filtering can be output; otherwise, the EKF can be reinitialized in the next epoch. When filtering the target positioning solution, this embodiment can input the target positioning solution as an observation into a Kalman equation (KF) filter for KF filtering.

[0090] The embodiment of the present invention provides several specific implementation methods based on the technical solutions of the above embodiments. As a specific implementation method of this embodiment, Figure 3 A flowchart of a digital key positioning method provided by an embodiment of the present invention is shown in FIG. Figure 3 As shown, the specific process of each positioning epoch is as follows:

[0091] Step 1: Receive the CIR information of all UWB anchor points in the current k-th epoch and proceed to step 2.

[0092] Step 2: Obtain the distance measurement value of the anchor point according to the CIR information. According to the number of valid anchor points N, use the equation solution or the least squares algorithm to obtain the initial positioning solution [x(0), y(0)] and proceed to step 3.

[0093] Step 3: Determine whether EKF needs to be initialized. If so, go to step 4; otherwise, go to step 5.

[0094] Step 4: Initialize EKF, take [x(0), y(0)] as the initial value of the state quantity, set parameters such as system matrix F, observation matrix H, system noise Q and initial value of state covariance P(0), and proceed to step 5.

[0095] The state quantity of EFK in this embodiment is the two-dimensional position coordinate of the digital key, which is expressed as follows:

[0096]

[0097] Among them, the state matrix (system matrix) of the motion system is:

[0098]

[0099] The observation equation is nonlinear and needs to be linearized. The observation matrix is:

[0100]

[0101] in, and They are:

[0102]

[0103]

[0104] System noise and observation noise can be set according to actual conditions.

[0105] Step 5: Determine whether the number of valid anchor points in this epoch is 0. If so, proceed to step 6; otherwise, proceed to step 7.

[0106] Step 6: At this point, set the EKF positioning mode to recursive mode and proceed to step 10.

[0107] Step 7: Determine whether the number of valid anchor points in this epoch is 1. If so, proceed to step 8; otherwise, proceed to step 9.

[0108] Step 8: At this point, set the EKF positioning mode to partial observation mode and proceed to step 10.

[0109] Step 9: At this point, set the EKF positioning mode to full observation mode and proceed to step 10.

[0110] Step 10: Perform EKF time update, perform one-step state prediction based on the state quantity X(k-1) of the previous epoch, obtain X(k|k-1), and obtain one-step predicted state covariance P(k|k-1) through the state covariance P(k-1) of the previous epoch, and enter step 11. Among them, the time update can be updated by the following formula, including the state one-step prediction and one-step prediction covariance calculation:

[0111]

[0112]

[0113] Among them, F is the system matrix, P is the covariance matrix, and Q is the system noise.

[0114] Step 11: Determine whether the EKF positioning mode is recursive mode. If so, go to step 13; otherwise, go to step 12.

[0115] Step 12: Take the ranging values ​​of all valid anchor points in this epoch as the observation value Z, set the observation noise R, perform EKF measurement update, obtain deltaX and the updated covariance matrix P(k), and go to step 13.

[0116] Among them, the observed value is the ranging value of N valid anchor points in the current epoch:

[0117]

[0118] The measurement update, including filter gain calculation, covariance estimation and state estimation, can be performed using the following formula:

[0119]

[0120]

[0121]

[0122] Among them, X is the state quantity, Z is the observation quantity, P is the covariance matrix, Q is the system noise matrix, R is the observation noise matrix, and K is the Kalman filter gain.

[0123] Step 13: Calculate the degrees of freedom based on the number of distance values ​​actually used and proceed to step 14.

[0124] Step 14: Update the EKF positioning mode of this epoch according to the degrees of freedom and proceed to step 15.

[0125] Step 15: When the positioning mode is recursive or partial observation, record the number of continuous positioning epochs M in this mode and go to step 16.

[0126] Step 16: Determine whether the number of continuous positioning epochs M is greater than the threshold. If so, proceed to step 17; otherwise, proceed to step 18.

[0127] Step 17: Exit the recursive or partial observation mode at the next epoch and enter step 18.

[0128] Step 18: Use deltaX to update the state variable to obtain X(k), which is the positioning solution [x(k), y(k)] of this epoch, and proceed to step 19.

[0129] Step 19: Perform static detection, perform EKF static constraints based on the results, and proceed to step 20.

[0130] Step 20: Perform quality control on [x(k), y(k)] and proceed to step 21.

[0131] Step 21: Estimate the confidence of this positioning result based on the covariance matrix P(k) and the positioning mode, and proceed to step 22.

[0132] Step 22: Determine whether the confidence of the positioning result is good and has passed the quality control. If so, proceed to step 23; otherwise, positioning cannot be performed this time and the EKF is reset in the next epoch.

[0133] Step 23: Input [x(k), y(k)] as the observation into the KF filter and proceed to step 24.

[0134] Step 24: Perform KF filtering and proceed to step 25.

[0135] Step 25: Output the positioning result of this epoch [x_filter(k), y_filter(k)].

[0136] The technical solution of this embodiment has good adaptability to various conditions in UWB digital key applications, and the positioning performance has been greatly improved compared with traditional algorithms, which can significantly improve the positioning accuracy. It has good scalability and versatility, and can be widely used in different vehicle models and different numbers and distributions of anchor points. It solves the problem in the prior art that the number of anchor points is small and there are non-line of sight (NLOS) anchor points, which makes it impossible to accurately locate.

[0137] This embodiment uses the common UWB digital key positioning method and this method to conduct positioning experiments, which are divided into static experiments, close to and away from the vehicle experiments, and around the vehicle experiments. There are different degrees of interference or occlusion in the experiments, simulating the real scenes of daily use of UWB digital keys. Among them, the common method refers to denoising the signal, solving the positioning solution by solving equations or the least squares method, and then smoothing and filtering the solution results.

[0138] 1) Static experiment

[0139] In this experiment, the tester holds a UWB digital key, and another person stands or walks between him and the vehicle. Due to the obstruction of pedestrians, the UWB signal is intermittently interfered to a certain extent. Figure 4 A result diagram of a static test performed by an existing method provided by an embodiment of the present invention, Figure 5 A result diagram of a static test performed by the method provided by the embodiment of the present invention is as follows: Figure 4 and 5 As shown in the figure, the box is the vehicle, and the diamond is the location of the five anchor points, which are the four corners of the vehicle and the center console. This is a common layout. All experiments use this layout.

[0140] It can be seen that some positioning points of the existing method have abnormal jumps. According to statistics, the maximum positioning error is 184.7cm, and the standard deviation of the positioning error is 28.1cm. In this method, the positioning results show good stability. According to statistics, the maximum positioning error is 7.8cm, and the standard deviation of the positioning error is 0.5cm. It can be seen that this method is significantly better than the common methods in static tests under complex scenes.

[0141] 2) Experiments on approaching and moving away from vehicles

[0142] In this experiment, the tester held the UWB digital key and walked towards the vehicle from about 9 meters away, with an angle of about 60 degrees between the direction of travel and the vehicle. When he reached the center of the front of the vehicle, he turned around and walked away from the vehicle in a direction perpendicular to the front of the vehicle. Figure 6 A result diagram of a vehicle approaching and moving away experiment using an existing method provided by an embodiment of the present invention, Figure 7 The result diagram of the vehicle approaching and moving away experiment provided by the present invention is as follows: Figure 6 and 7 As shown in the figure, in this experiment, the total number of sampling points is 95, the number of positioning points of the common method is 46, and the number of positioning points of this method is 51, which is 5% more than the common method. The reason why there are multiple sampling points without positioning is that when the tester is moving away from the vehicle, due to the posture of holding the digital key, the signals of all UWB anchor points are severely blocked, so the signal is completely lost after a certain distance from the vehicle, and positioning is impossible.

[0143] It can be seen that this method has more stable and consistent positioning results than common methods when approaching the vehicle. When moving away from the vehicle, although the signal is severely lost, it still shows good positioning results in the distance where the UWB signal exists, while common methods have breakpoints and abnormal positioning.

[0144] 3) Car walk test

[0145] In the experiment, the UWB digital key was placed in the tester's pocket and walked around the car three times clockwise. Due to the changes in the position and occlusion relationship between the key and the vehicle, the UWB signal was better in some areas and worse in some areas. Figure 8 A result diagram of a car-walking experiment performed by an existing method according to an embodiment of the present invention is provided. Fig. 9 A result diagram of a car-circling experiment performed by the method provided in an embodiment of the present invention is shown in FIG. Figure 8 and 9As shown in the figure, in this experiment, the total number of sampling points is 286, the number of positioning points of the common method is 291, and the number of positioning points of this method is 355, which is 16.5% more than the common method. It can be seen that in areas with poor signals, the common method has a long period of no positioning and several jump points with large errors. This method is obviously more stable, has no jump points with large errors, and has more positioning points.

[0146] It can be seen that compared with the existing methods, this method has obvious improvements in positioning accuracy, number of positioning solutions and adaptability to complex environments, laying a good foundation for the application of UWB digital keys.

[0147] Embodiment 3

[0148] Fig.10 This is a schematic diagram of the structure of a digital key positioning device provided in the third embodiment of the present invention. The device can be applied to the situation of positioning a digital key, wherein the device can be implemented by software and / or hardware and is generally integrated in an electronic device. Fig.10 As shown, the device comprises:

[0149] An acquisition module 310 is used to obtain the distance measurement values ​​between all anchor points on the vehicle and the digital key in the current epoch;

[0150] A first determination module 320 is used to determine a positioning mode of an extended Kalman filter EKF according to the number of valid anchor points among all the anchor points; the valid anchor points are anchor points to which the ranging value can be referenced, and the positioning modes include a recursive mode, a partial observation mode, and a full observation mode;

[0151] An updating module 330 is used to perform a time update according to the target positioning solution or the initial positioning solution of the previous epoch through the EKF to obtain a predicted positioning solution of this epoch;

[0152] The second determination module 340 is used to determine whether to perform measurement update according to the positioning mode of the EKF. If so, the predicted positioning solution is measured and updated to obtain the target positioning solution of the digital key in this epoch. Otherwise, the predicted positioning solution is used as the target positioning solution of the digital key in this epoch.

[0153] This embodiment provides a digital key positioning device, including: an acquisition module, used to obtain the distance measurement value between all anchor points on the vehicle and the digital key in the current epoch; a first determination module, used to determine the positioning mode of the extended Kalman filter EKF according to the number of valid anchor points among all the anchor points; the valid anchor point is the anchor point that the distance measurement value can refer to, and the positioning mode includes a recursive mode, a partial observation mode and a full observation mode; an update module, used to perform time update according to the target positioning solution or the initial positioning solution of the previous epoch by the EKF to obtain the predicted positioning solution of this epoch; a second determination module, used to determine whether to perform measurement update according to the positioning mode of the EKF, if so, then perform measurement update on the predicted positioning solution to obtain the target positioning solution of the digital key in this epoch, otherwise, the predicted positioning solution is used as the target positioning solution of the digital key in this epoch. By determining the positioning mode of the EKF according to the number of valid anchor points and determining the positioning solution of the digital key by the EKF, the accuracy of positioning the digital key can be improved, and the problem that the positioning method in the prior art cannot accurately locate when the number of anchor points is small is solved.

[0154] Furthermore, the first determination module 320 is specifically used to: when the number of valid anchor points is 0, determine that the positioning mode of EKF is a recursive mode; when the number of valid anchor points is less than the dimension of the EKF state quantity and is not equal to 0, determine that the positioning mode of EKF is a partial observation mode; when the number of valid anchor points is greater than or equal to the dimension of the EKF state quantity, determine that the positioning mode of EKF is a full observation mode.

[0155] Furthermore, the acquisition module 310 is also used to: determine the initial positioning solution of the digital key according to the ranging values ​​of the valid anchor points among all the anchor points; when the EKF needs to be initialized, use the initial positioning solution as the initial value of the state quantity of the EKF, and initialize the parameters of the EKF.

[0156] Furthermore, the second determination module 340 is specifically used to: obtain a positioning solution change by measuring and updating through EKF, update the predicted positioning solution according to the positioning solution change, and obtain a target positioning solution of the digital key in this epoch.

[0157] Furthermore, the measurement update through EKF to obtain the positioning solution change includes: taking the ranging values ​​of all valid anchor points in this epoch as observation quantities; determining the observation noise corresponding to the observation quantity according to the sliding standard deviation and the line-of-sight state of the observation quantity; and using each observation quantity and the corresponding observation noise in turn to perform EKF measurement update through a sequential processing method to obtain the positioning solution change.

[0158] Furthermore, after using each observation quantity and the corresponding observation noise to perform the measurement update of the EKF, it also includes: if the residual of this measurement update is greater than the residual threshold, dynamically adjusting the observation noise corresponding to the observation quantity according to the residual, and reusing the observation quantity and the adjusted observation noise for measurement update; if the residual corresponding to the observation quantity is still greater than the residual threshold after the observation quantity is re-measured and updated more than a preset number of times, then discarding the observation quantity.

[0159] Furthermore, the device is also used to: calculate the degrees of freedom based on the dimensions of the EKF state quantity and the dimensions of the observation quantity actually used; update the positioning mode of the EKF of this epoch based on the degrees of freedom; when the updated positioning mode is the recursive mode or the partial observation mode, record the number of continuous positioning epochs in the recursive mode or the partial observation mode; when the number of continuous positioning epochs is greater than the epoch number threshold, exit the recursive mode or the partial observation mode in the next epoch.

[0160] Furthermore, the second determination module 340 is also used to: perform static detection on the digital key to obtain a static detection result; when the static detection result is static, determine whether to release the static constraint based on the static constraint duration and the interval distance between the target positioning solution of this epoch and the initial constraint positioning solution; if not, use the initial constraint positioning solution as the new target positioning solution of this epoch.

[0161] Furthermore, the second determination module 340 is also used to: perform quality control on the target positioning solution to obtain a quality control result; determine the confidence of the target positioning solution according to the current covariance matrix and positioning mode of the EKF; when the confidence and the quality control result both meet the conditions, filter the target positioning solution and output the positioning result of the current epoch after filtering; otherwise, reinitialize the EKF in the next epoch.

[0162] The above-mentioned digital key locating device can execute the digital key locating method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0163] Embodiment 4

[0164] Fig.11A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0165] like Fig.11 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0166] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0167] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a digital key positioning method.

[0168] In some embodiments, the digital key positioning method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the digital key positioning method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the digital key positioning method in any other appropriate manner (e.g., by means of firmware).

[0169] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0170] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0171] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0172] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0173] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0174] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0175] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0176] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A digital key positioning method, characterized in that: The method comprises: Get the distance values ​​between all anchor points on the vehicle and the digital key in the current epoch; Determine the positioning mode of the extended Kalman filter EKF according to the number of valid anchor points among all the anchor points; the valid anchor point is an anchor point to which the ranging value can be referenced, and the positioning mode includes a recursive mode, a partial observation mode and a full observation mode; The EKF performs time updating according to the target positioning solution or the initial positioning solution of the previous epoch to obtain the predicted positioning solution of the current epoch; Determine whether to perform measurement update according to the positioning mode of the EKF, and if so, perform measurement update on the predicted positioning solution to obtain the target positioning solution of the digital key in this epoch, otherwise use the predicted positioning solution as the target positioning solution of the digital key in this epoch; The method further comprises: Calculate the degrees of freedom based on the dimensions of the EKF state quantities and the dimensions of the observation quantities actually used; Update the positioning mode of the EKF of this epoch according to the degrees of freedom; When the updated positioning mode is a recursive mode or a partial observation mode, the number of continuous positioning epochs in the recursive mode or the partial observation mode is recorded; When the number of continuous positioning epochs is greater than the epoch number threshold, the recursive mode or partial observation mode is exited at the next epoch.

2. The method according to claim 1, characterized in that Determining the positioning mode of the extended Kalman filter EKF according to the number of valid anchor points among all the anchor points includes: When the number of valid anchor points is 0, determining that the positioning mode of the EKF is a recursive mode; When the number of the valid anchor points is less than the dimension of the EKF state quantity and is not equal to 0, determining that the positioning mode of the EKF is a partial observation mode; When the number of the valid anchor points is greater than or equal to the dimension of the EKF state quantity, it is determined that the positioning mode of the EKF is the full observation mode.

3. The method according to claim 1, characterized in that After obtaining the distance measurement values ​​between all anchor points on the vehicle and the digital key in the current epoch, the method further includes: Determining an initial positioning solution of the digital key according to the ranging values ​​of the valid anchor points among all the anchor points; When the EKF needs to be initialized, the initial positioning solution is used as the initial value of the state quantity of the EKF, and the parameters of the EKF are initialized.

4. The method according to claim 1, characterized in that: The obtaining of the target positioning solution of the digital key in this epoch after measuring and updating the predicted positioning solution includes: The positioning solution change is obtained by measuring and updating through EKF, and the predicted positioning solution is updated according to the positioning solution change to obtain the target positioning solution of the digital key in this epoch.

5. The method according to claim 4, characterized in that The measurement update by EKF to obtain the positioning solution variation includes: The distance measurement values ​​of all valid anchor points in this epoch are taken as the observed values; Determine the observation noise corresponding to the observation amount according to the sliding standard deviation and the sight distance state of the observation amount; Through the sequential processing method, each observation and the corresponding observation noise are used in turn to update the EKF measurement and obtain the change of the positioning solution.

6. The method according to claim 5, characterized in that After performing a measurement update of the EKF using each observation and the corresponding observation noise, the method further includes: If the residual of this measurement update is greater than the residual threshold, dynamically adjusting the observation noise corresponding to the observation amount according to the residual, and reusing the observation amount and the adjusted observation noise for measurement update; If the residual corresponding to the observation value is still greater than the residual threshold after the observation value is remeasured and updated for a number of times greater than a preset number of times, the observation value is discarded.

7. The method according to claim 1, characterized in that After obtaining the target positioning solution of the digital key in this epoch, the method further includes: Performing a static test on the digital key to obtain a static test result; When the static detection result is static, determine whether to release the static constraint according to the constraint duration of this static state and the interval distance between the target positioning solution of this epoch and the initial constraint positioning solution; If not, the initial constrained positioning solution is used as the new target positioning solution for this epoch.

8. The method according to claim 1, characterized in that After obtaining the target positioning solution of the digital key in this epoch, the method further includes: Performing quality control on the target positioning solution to obtain a quality control result; Determining the confidence of the target positioning solution according to the current covariance matrix and positioning mode of the EKF; When both the confidence and the quality control results meet the conditions, the target positioning solution is filtered and the positioning result of the current epoch after filtering is output; otherwise, the EKF is reinitialized in the next epoch.

9. A digital key positioning device, characterized in that: The device comprises: The acquisition module is used to obtain the distance values ​​between all anchor points on the vehicle and the digital key in the current epoch; A first determination module is used to determine a positioning mode of an extended Kalman filter EKF according to the number of valid anchor points among all the anchor points; the valid anchor points are anchor points to which the ranging value can be referenced, and the positioning mode includes a recursive mode, a partial observation mode, and a full observation mode; An updating module, used for performing time updating according to the target positioning solution or the initial positioning solution of the previous epoch through the EKF to obtain a predicted positioning solution of this epoch; A second determination module is used to determine whether to perform measurement update according to the positioning mode of the EKF, and if so, to obtain the target positioning solution of the digital key in this epoch after measuring and updating the predicted positioning solution, otherwise to use the predicted positioning solution as the target positioning solution of the digital key in this epoch; The device is also used for: Calculate the degrees of freedom based on the dimensions of the EKF state quantities and the dimensions of the observation quantities actually used; Update the positioning mode of the EKF of this epoch according to the degrees of freedom; When the updated positioning mode is a recursive mode or a partial observation mode, the number of continuous positioning epochs in the recursive mode or the partial observation mode is recorded; When the number of continuous positioning epochs is greater than the epoch number threshold, the recursive mode or partial observation mode is exited at the next epoch.

10. An electronic device, characterized in that: The device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the digital key positioning method described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the digital key positioning method described in any one of claims 1 to 8 when executed.

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