Bluetooth key positioning method and device for vehicle, vehicle and storage medium

Abstract

The application discloses a kind of vehicle Bluetooth key positioning method, device, vehicle and storage medium.The method comprises: obtaining initial acquisition data in vehicle, and calculating initial distance value between Bluetooth key and the vehicle according to the initial acquisition data;According to the initial acquisition data, determine the current initial area positioning result;According to the current initial area positioning result, the initial distance value is corrected, and target distance value is obtained;According to the target distance value, determine the current target area positioning result.The technical scheme proposed in the application can make the distance value for determining the final key area more accurate, thereby improving the accuracy of Bluetooth key area positioning result, greatly improve the performance of vehicle Bluetooth key positioning system, enhance the use experience of Bluetooth key.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method, device, vehicle, and storage medium for locating Bluetooth keys for automobiles. Background Technology

[0002] With the rapid development of technology, car keys have been continuously optimized, from mechanical keys to remote control keys, and then to proximity keys, and now Bluetooth keys have emerged. A Bluetooth car key system is a digital key system that uses Bluetooth positioning technology to unlock and / or lock car doors when the user is close to the vehicle.

[0003] Most Bluetooth positioning methods currently rely on Received Signal Strength Indication (RSSI) for location tracking. This involves determining the location based on the relationship between the strength of the Bluetooth signal and the distance between the transmitting and receiving points. The positioning accuracy of Bluetooth RSSI is typically between 2 and 5 meters. However, in practical applications, factors such as anchor point location and environment can affect the Bluetooth signal during propagation, leading to fluctuations and outliers in the signal value. This weakens the correlation between the signal attenuation model and distance, further amplifying the positioning error. Consequently, this results in location drift, incorrect area identification, and negatively impacts the user experience of Bluetooth keys. Summary of the Invention

[0004] This invention provides a method, device, vehicle, and storage medium for locating vehicle Bluetooth keys, which can solve the problem of inaccurate Bluetooth key area positioning results based on Bluetooth RSSI.

[0005] According to one aspect of the present invention, a method for locating a vehicle Bluetooth key is provided, comprising:

[0006] Acquire initial data from the vehicle and calculate the initial distance between the Bluetooth key and the vehicle based on the initial data. The initial data includes the RSSI values ​​of the received signal strength of the Bluetooth signal transmitted by the Bluetooth key at a preset number of Bluetooth anchor points in the vehicle.

[0007] The initial location result is determined based on the initial data collected. The initial location result includes a first key area and a third key area. The key areas are divided based on the distance between the Bluetooth key and the vehicle. The boundary values ​​of the distance ranges corresponding to the first key area, the second key area and the third key area increase sequentially.

[0008] The initial distance value is corrected based on the current initial area positioning results to obtain the target distance value;

[0009] The current target area location result is determined based on the target distance value. The target area location result includes the first key area, the second key area, and the third key area.

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

[0011] An initial distance calculation module is used to acquire initial data in the vehicle and calculate the initial distance between the Bluetooth key and the vehicle based on the initial data. The initial data includes the received signal strength (RSSI) values ​​of a preset number of Bluetooth anchor points in the vehicle that receive the Bluetooth signal emitted by the Bluetooth key.

[0012] An initial area determination module is used to determine the current initial area positioning result based on the initial collected data. The initial area positioning result includes a first key area and a third key area. The key areas are divided based on the distance between the Bluetooth key and the vehicle. The boundary values ​​of the distance ranges corresponding to the first key area, the second key area, and the third key area increase sequentially.

[0013] An initial distance correction module is used to correct the initial distance value based on the current initial area positioning result to obtain the target distance value;

[0014] The target area determination module is used to determine the current target area positioning result based on the target distance value, wherein the target area positioning result includes the first key area, the second key area and the third key area.

[0015] According to another aspect of the present invention, a vehicle is provided, the vehicle comprising:

[0016] At least one processor;

[0017] and memory that is communicatively connected to at least one processor;

[0018] The memory stores a computer program that can be executed by at least one processor, which enables the at least one processor to execute the vehicle Bluetooth key positioning method according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute and implement the vehicle Bluetooth key positioning method of any embodiment of the present invention.

[0020] The technical solution of this invention involves acquiring initial data from the vehicle, calculating the initial distance between the Bluetooth key and the vehicle based on the initial data, determining the current initial area positioning result based on the initial data, wherein the initial area positioning result includes two non-adjacent key areas in the final target area positioning result, correcting the initial distance value based on the current initial area positioning result to obtain the target distance value, and then determining the current target area positioning result based on the target distance value. By adopting the above technical solution, non-adjacent key areas are pre-distinguished, and the initial distance value is specifically corrected based on the distinction result, thereby making the distance value used to determine the final key area more accurate. This improves the accuracy of Bluetooth key area positioning results based on Bluetooth RSSI, greatly enhances the performance of the vehicle Bluetooth key positioning system, and improves the user experience of Bluetooth keys.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a vehicle Bluetooth key positioning method according to Embodiment 1 of the present invention;

[0024] Figure 2 This is a flowchart of a vehicle Bluetooth key positioning method applicable to Embodiment 2 of the present invention;

[0025] Figure 3 It is a distance-RSSI curve;

[0026] Figure 4 This is a distance-RSSI curve corresponding to a preset ranging model provided in Embodiment 2 of the present invention;

[0027] Figure 5 This is a flowchart of another vehicle Bluetooth key positioning method applicable to Embodiment 3 of the present invention;

[0028] Figure 6 This is a schematic diagram of the structure of a vehicle Bluetooth key positioning device according to Embodiment 4 of the present invention;

[0029] Figure 7 This is a schematic diagram of the vehicle structure for implementing the vehicle Bluetooth key positioning method of this invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," "initial," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Example 1

[0033] Figure 1 This is a flowchart of a vehicle Bluetooth key positioning method provided in Embodiment 1 of the present invention. This embodiment is applicable to determining the area positioning result of a vehicle Bluetooth key (hereinafter referred to as Bluetooth key) based on Bluetooth RSSI, so as to achieve contactless entry or automatic vehicle unlocking. This method can be executed by a vehicle Bluetooth key positioning device, which can be implemented in hardware and / or software, and can be configured in the vehicle. Figure 1 As shown, the method includes:

[0034] S110. Acquire the initial data collected in the vehicle and calculate the initial distance value between the Bluetooth key and the vehicle based on the initial data collected.

[0035] In this embodiment, the initial data collection includes the received signal strength (RSSI) values ​​of a preset number of Bluetooth anchor points in the vehicle that receive Bluetooth signals emitted by the Bluetooth key.

[0036] The RSSI value includes the received signal strength indicator. Theoretically, as the distance between the receiving node and the signal node increases, the received signal strength decreases in a logarithmic manner. Bluetooth RSSI positioning can determine the distance between the signal node and the receiving node by measuring the strength of the Bluetooth signal received by the receiving node, thereby achieving positioning.

[0037] In this embodiment, Bluetooth anchor points can be pre-installed at designated locations on the vehicle, such as the front, rear, or doors. The vehicle Bluetooth key can be configured as a signal node to transmit Bluetooth signals; specifically, the vehicle Bluetooth key can be a mobile device such as a smartphone or smartwatch. The Bluetooth anchor points can be configured as receiving nodes to receive Bluetooth signals from the vehicle Bluetooth key. For example, the preset number of Bluetooth anchor points is not limited and can be one or more, for example, eight.

[0038] The initial distance value can be calculated using the initial collected data and the ranging model. The expression for the ranging model can be RSSI = A - 10nlog(d), where d is the distance, A is a constant, and n is the path loss exponent.

[0039] For example, when Bluetooth ranging is required, the Bluetooth key transmits a Bluetooth signal, the vehicle collects the corresponding data of the Bluetooth signal received by a preset number of Bluetooth anchor points, obtains the received signal strength RSSI value of the Bluetooth signal, and calculates the initial distance value based on the initial collected data and the ranging model.

[0040] S120. Determine the current initial area positioning result based on the initial collected data.

[0041] In this embodiment, the key area can be understood as the area where the Bluetooth key is located relative to the vehicle. The initial area positioning result includes a first key area and a third key area. The key area is divided based on the distance between the Bluetooth key and the target vehicle. During the division, it is divided into at least three areas, which are respectively denoted as the first key area, the second key area and the third key area. The boundary values ​​of the distance ranges corresponding to the first key area, the second key area and the third key area increase sequentially.

[0042] For example, the division criteria could be: within 2 meters of the vehicle body is the unlocking zone, 2-4 meters is the reserved zone, 4-7 meters is the locking zone, 7-10 meters is the welcoming zone, and more than 10 meters is the connecting zone. The names and distances of these zones can be defined according to the actual needs of the vehicle manufacturer and / or vehicle user; this embodiment does not impose any limitations on this.

[0043] The first key area includes, but is not limited to, the unlocking area; the second key area includes, but is not limited to, the locking area; and the third key area includes, but is not limited to, the welcoming area.

[0044] For example, when determining the current initial area location result based on the initial collected data, a logical judgment-based method can be chosen, such as comparing the initial collected data or the processed initial collected data with a corresponding threshold, and determining the current initial area location result based on the comparison result; alternatively, a machine learning method can be chosen, such as using a classification algorithm to determine the classification result of the initial collected data. The specific determination method used is not limited here.

[0045] S130. Correct the initial distance value based on the current initial area positioning result to obtain the target distance value.

[0046] In this embodiment of the invention, after obtaining the current initial area positioning result, the initial distance value can be modified in a targeted manner.

[0047] For example, if the current initial area positioning result is the first key area, the initial distance value is subjected to a first correction process to obtain a target distance value; if the current initial area positioning result is the third key area, the initial distance value is subjected to a second correction process to obtain a target distance value. The first and second correction processes are different; that is, different correction methods are used for different initial area positioning results. The specific correction method is not limited. For example, it may include increasing or decreasing, increasing or decreasing a preset value, or increasing or decreasing by a preset multiple, etc.

[0048] Optionally, a first correction process is performed, resulting in a target distance value that is less than the initial distance value; a second correction process is performed, resulting in a target distance value that is greater than the initial distance value. For example, the first correction process involves multiplying the initial distance value by a first correction coefficient, where the first correction coefficient is less than 1; the second correction process involves multiplying the initial distance value by a second correction coefficient, where the second correction coefficient is greater than 1.

[0049] S140. Determine the current target area positioning result based on the target distance value.

[0050] The target area location result includes the first key area, the second key area, and the third key area.

[0051] For example, after making targeted corrections to the initial distance value based on the current initial area positioning result, a more accurate target distance value can be obtained. Then, the target distance value is compared with the distance range corresponding to each key interval to determine which key interval the target distance value falls within. This key interval is then identified as the target key interval, which is the current target area positioning result.

[0052] The technical solution of this embodiment involves acquiring initial data from the vehicle and calculating the initial distance between the Bluetooth key and the vehicle based on this data. The initial data includes the Received Signal Strength (RSSI) values ​​of a preset number of Bluetooth anchor points in the vehicle receiving Bluetooth signals emitted by the Bluetooth key. Based on the initial data, a current initial area positioning result is determined. This initial area positioning result includes a first key area and a third key area, divided based on the distance between the Bluetooth key and the vehicle. The boundary values ​​of the distance ranges corresponding to the first, second, and third key areas increase sequentially. The initial distance value is then corrected based on the current initial area positioning result to obtain a target distance value. Finally, the current target area positioning result is determined based on the target distance value, including the first, second, and third key areas. By employing the above technical solution, the acquired data is calculated, and the data information is optimized according to a preset correction method, ultimately leading to an accurate target area positioning result. By adopting the above technical solution, non-adjacent key areas are pre-differentiated, and the initial distance value is specifically corrected based on the differentiation results. This makes the distance value used to determine the final key area more accurate, thereby improving the accuracy of Bluetooth key area positioning results based on Bluetooth RSSI. This greatly improves the performance of the vehicle Bluetooth key positioning system and enhances the user experience of Bluetooth keys.

[0053] Optionally, in some embodiments, the system may also include controlling the vehicle to perform corresponding operations based on the current target area positioning results.

[0054] For example, when the target distance value is determined to be a preset distance value within the first key area, an automatic unlocking operation is performed; when the target distance value is determined to be a preset distance value within the second key area, an automatic locking operation is performed; when the target distance value is determined to be a preset distance value within the third key area, a welcoming operation is performed. The welcoming operation includes, but is not limited to, automatically activating a preset headlight mode and the target vehicle emitting a warning sound. Activating the preset headlight mode may include low beam headlights, hazard warning lights, side marker lights, and alternating low and high beam headlights, etc. The warning sound emitted by the target vehicle may include a brief horn blast and intermittent, continuous, brief horn blasts within a preset time period.

[0055] Example 2

[0056] Figure 2 This is a flowchart of a vehicle Bluetooth key positioning method provided in Embodiment 2 of the present invention. The technical solution of this embodiment further optimizes the calculation of the initial distance value based on the above optional technical solutions. The initial collected data is input into the preset ranging model to obtain the initial anchor point distance value corresponding to each Bluetooth anchor point. The initial distance value between the Bluetooth key and the vehicle is calculated based on the initial anchor point distance value, which can more accurately calculate the initial distance value.

[0057] Optionally, the initial area positioning result can be determined based on the initial collected data, including: inputting the initial collected data into a preset positioning model, and determining the current initial area positioning result based on the output of the preset positioning model, whereby the preset positioning model includes a machine learning model. Using a machine learning model for initial area positioning can improve positioning efficiency and accuracy.

[0058] like Figure 2 As shown, the method includes:

[0059] S210. Acquire initial data from the vehicle.

[0060] S220. Input the initial collected data into the preset ranging model to obtain the initial anchor point distance value corresponding to each Bluetooth anchor point.

[0061] For example, the RSSI value corresponding to each Bluetooth anchor point in the initial data collection is input into a preset ranging model to obtain the initial anchor point distance value for each Bluetooth anchor point. Assuming the preset number is 8, then 8 initial anchor point distance values ​​are obtained here.

[0062] Optionally, the initial data can be filtered before being input into the preset ranging model. The filtering method is not limited; for example, Gaussian filtering can be performed first, followed by median filtering.

[0063] For example, a preset ranging model can be determined in advance by fitting, such as collecting calibration data, using the calibration data to determine the data to be fitted for model fitting, and using the data to be fitted to fit the parameter values ​​in the ranging model to obtain the preset ranging model.

[0064] As in the example above, the expression for the ranging model can be RSSI = A - 10nlog(d), and A and n can be fitted using the data to be fitted.

[0065] Optionally, the above calibration data is the Bluetooth signal strength RSSI. Theoretically, as the distance between the Bluetooth anchor and the Bluetooth key increases, the received signal strength attenuates in a logarithmic manner. However, in actual use, many environmental factors can cause Bluetooth signals to be affected by shadow fading, multipath propagation, reflection, etc., leading to fluctuations or singular values ​​in the Bluetooth signal value. This weakens the correlation between the signal attenuation model and distance, and the signal attenuation is very likely to be negatively correlated with distance.

[0066] In this embodiment of the invention, in order to eliminate the above-mentioned effects, the process of determining the data to be fitted can be improved.

[0067] Optionally, the data to be fitted for determining the preset ranging model can be obtained in the following ways:

[0068] 1) For each Bluetooth anchor point in the preset number of Bluetooth anchor points, collect multiple sets of calibration data. Each set of calibration data includes multiple sets of calibration data with the same preset distance in different directions. Different sets of calibration data correspond to different preset distances. The direction is the relative direction between the Bluetooth key and the Bluetooth anchor point.

[0069] Optionally, the aforementioned direction can be any direction within a 360-degree range with the anchor point coordinates as the origin. There are at least two of the aforementioned different directions, such as 30 degrees, 60 degrees, 90 degrees, and 120 degrees. There are at least two of the aforementioned different preset distances, such as 1 meter, 2 meters, ..., 10 meters.

[0070] 2) Perform a preset filtering process on the calibration data to obtain filtered calibration data.

[0071] Optionally, the calibration data with large fluctuations can be removed to obtain the filter calibration data.

[0072] For example, the preset filtering methods include, but are not limited to, Gaussian filtering, mean filtering, and median filtering.

[0073] 3) For each preset distance, the corresponding filtered calibration data are fused and calculated using a preset calculation method to obtain the corresponding data to be fitted.

[0074] The preset calculation method can be to average the data from points at equal distances in different directions, and then use this averaged data to fit the values ​​of A and n. For example, assuming that RSSI values ​​at equal distances in four different directions are collected for each anchor point, the average value of the RSSI values ​​in the four different directions is calculated for each preset distance corresponding to each anchor point.

[0075] By using the data to be fitted in the above manner, the resulting ranging model can better match the actual environment, offset some of the effects of multipath propagation and shadow fading, obtain relatively stable ranging results in multiple directions, and keep the error within a small range.

[0076] In related technologies, a unified ranging model is used to determine the distance value corresponding to the RSSI value. However, the inventors found that in practical applications, during the propagation of Bluetooth wireless signals, after a certain distance, a small decrease in the RSSI value corresponds to a large increase in the distance. Therefore, the fitting accuracy of the model decreases as the distance increases. In order to improve the accuracy of the ranging model, this embodiment of the invention chooses to perform piecewise fitting on the ranging model.

[0077] Optionally, the preset ranging model includes at least two ranging sub-models, with different ranging sub-models corresponding to different numerical ranges based on RSSI values. The RSSI values ​​in the initial collected data are input into the ranging sub-model corresponding to the numerical range to determine the corresponding initial anchor point distance value based on the output of the ranging sub-model.

[0078] Specifically, the implementation method can be as follows: Generate a distance-RSSI curve based on the data to be fitted. This curve can be called a signal propagation curve. Analyze the characteristics of the signal propagation curve and select one or more distance thresholds with good discrimination for segmentation (for example, it can be determined based on the degree of slope change at each point on the curve). Determine the RSSI value corresponding to the distance threshold in the curve as the RSSI threshold, resulting in multiple RSSI intervals. The RSSI value and corresponding distance value in a single RSSI interval correspond to a set of data to be fitted, thus determining multiple sets of data to be fitted. Each set of data to be fitted corresponds to a ranging sub-model. Fitting is performed using each set of data to be fitted to obtain multiple ranging sub-models, thus dividing the ranging model into a preset number. Taking a preset number of 2 as an example, by setting an RSSI threshold for the RSSI in the data to be fitted, fitting samples with RSSI values ​​less than the threshold and samples with RSSI values ​​greater than the threshold separately, a two-segmented ranging model is obtained.

[0079] For example, Figure 3This is a distance-RSSI curve generated using all initial data to be fitted. Two segmented sub-models are employed. When the signal propagates to approximately 5m-5.5m, a small change in signal strength leads to a large change in distance, with the correlation becoming more pronounced as the distance increases. Therefore, 5.5m can be selected as the aforementioned distance threshold, and the RSSI value at 5.5m, approximately -67.8dB, is chosen as the RSSI threshold. It should be noted that the -67.8dB signal strength threshold is not fixed and can be selected individually for different vehicle models and anchor points based on specific circumstances.

[0080] For example, after determining the RSSI threshold, a piecewise fitting method is used to obtain two piecewise distance-RSSI curves. The two piecewise distance-RSSI curves are then merged to obtain the distance-RSSI curve corresponding to the preset ranging model. Figure 4 This is a distance-RSSI curve corresponding to a preset ranging model provided in Embodiment 2 of the present invention. For example... Figure 3 As shown, the RSSI values ​​for 3 meters and 6 meters are both around -65 dB, and the two distance values ​​differ significantly, leading to inaccurate distance values ​​determined based on -65 dB. Figure 4 As shown, the RSSI values ​​for 3 meters and 6 meters are different. When measuring distance, a more accurate distance value can be determined based on the RSSI value and the pre-set distance measurement model for each segment.

[0081] Optionally, the data to be fitted for determining each ranging sub-model can also be obtained through the methods described in 1), 2), and 3) above.

[0082] For example, in the initial acquired data after filtering, the RSSI value corresponding to each Bluetooth anchor point is first determined, and then the RSSI value is input into the ranging sub-model corresponding to the determined numerical range to obtain the corresponding initial anchor point distance value. Different RSSI values ​​may be input into different ranging sub-models to obtain more accurate distance values.

[0083] S230. Calculate the initial distance between the Bluetooth key and the vehicle based on the initial anchor point distance value.

[0084] For example, the initial distance between the Bluetooth key and the vehicle can be calculated by combining a preset number of initial anchor point distance values. The specific calculation method is not limited, such as calculating the average value, calculating the weighted average value, or taking the median value, etc.

[0085] S240. Input the initial collected data into the preset positioning model, and determine the current initial area positioning result based on the output of the preset positioning model.

[0086] The preset positioning model includes a machine learning model, which can be a neural network model. The specific model structure is not limited. For example, it can be formed by using layer structures such as convolutional layers, pooling layers, fully connected layers, residual modules, etc., as well as the connection relationships between each layer structure.

[0087] The preset positioning model is trained in the following way: sample data is input into the preset machine learning model to obtain sample positioning results, wherein the sample data carries positioning result labels, the positioning result labels include the first key area and the third key area, and the sample data includes sample RSSI values ​​corresponding to the preset number of Bluetooth anchor points in the vehicle; a loss relationship is calculated based on the sample positioning results and the positioning result labels, and the preset machine learning model is trained based on the loss relationship.

[0088] For example, a location result label can be set for the corresponding sample data based on the actual location of the Bluetooth key when the sample data is collected. For instance, if the Bluetooth key is located within the first key area, the location result label of the collected sample data is the first key area.

[0089] For example, a machine learning model is trained based on the loss relationship. During training, the goal is to minimize the loss relationship. Training techniques such as backpropagation are used to continuously optimize the weight parameter values ​​in one or more branches of the machine learning model until a preset training cutoff condition is met. The specific training cutoff condition can be set according to actual needs, and this embodiment of the disclosure does not limit it. For example, it can be set based on the number of iterations, the degree of convergence of the loss value, or the model accuracy.

[0090] S250. Correct the initial distance value based on the current initial area positioning result to obtain the target distance value.

[0091] For example, if the current initial area positioning result is the first key area, the initial distance value is subjected to a first correction process to obtain a target distance value, wherein the target distance value is less than the initial distance value; if the current initial area positioning result is the third key area, the initial distance value is subjected to a second correction process to obtain a target distance value, wherein the target distance value is greater than the initial distance value.

[0092] Optionally, the first correction process can be multiplied by a coefficient less than 1 or subtracted by a first preset value to obtain a target distance value less than the initial distance value; the second correction process can be multiplied by a coefficient greater than 1 or added by a second preset value to obtain a target distance value greater than the initial distance value.

[0093] Specifically, the preset correction formula is d1 = D * f (or d1 = Dm, or d1 = D + n), where d1 is the target distance value, D is the initial distance value, f is the scaling factor, m is the first preset value, and n is the second preset value, both m and n are greater than 0. m and n can be two equal or unequal values. When the output result of the initial area positioning is the first key area, the distance D is reduced, i.e., d1 = D * fa or d1 = Dm, where fa is the scaling factor for the first key area, and fa is less than 1; when the output result is the third key area, the distance D is increased, i.e., d1 = D * fb or d1 = D + n, where fb is the scaling factor for the third key area, and fb is greater than 1.

[0094] For example, when the output result of the above area is the unlocked area, then fa is a coefficient less than 1, which reduces the distance D, i.e., d1 = D * fa; when the output result of the area is the welcome area, then fb is a coefficient greater than 1, which enlarges the distance D, i.e., d1 = D * fb. The scaling factors fa and fb can be selected according to the actual situation, such as 0.8 and 1.2 respectively.

[0095] S260. Determine the current target area location result based on the target distance value.

[0096] The target area location result includes the first key area, the second key area, and the third key area.

[0097] Based on the target distance value finally obtained from the distance correction processing model in the above steps, it is possible to locate which area of ​​the first key area, second key area, and third key area the key is currently located in, thereby achieving accurate positioning of the Bluetooth key.

[0098] The vehicle Bluetooth key positioning method provided in this invention utilizes a preset ranging model to accurately obtain the initial anchor point distance value corresponding to each Bluetooth anchor point. Then, based on the initial anchor point distance value, an accurate initial distance value is calculated, laying the foundation for accurately determining the target distance value. Subsequently, a preset positioning model based on a machine learning model can improve the efficiency and accuracy of determining the initial area positioning result. After correcting the initial distance value based on the initial area positioning result, the final key area positioning is performed, effectively improving the accuracy of the final positioning result. This allows the vehicle to respond accurately based on the finally located key area, enhancing the user experience.

[0099] In some embodiments, calculating the initial distance between the Bluetooth key and the vehicle based on the initial anchor point distance values ​​includes: determining weighting coefficients corresponding to the initial anchor point distance values, wherein at least two initial anchor point distance values ​​are negatively correlated with their corresponding weighting coefficients; and calculating a weighted average of the initial anchor point distance values ​​based on the weighting coefficients to obtain the initial distance between the Bluetooth key and the vehicle. The advantage of this configuration is that the initial distance value can be calculated more accurately.

[0100] Specifically, after obtaining the initial anchor point distance values ​​corresponding to a preset number of anchor points' RSSI values ​​using a preset ranging model, the initial anchor point distance values ​​are sorted. Based on the sorting result, each initial anchor point distance value is assigned a confidence level, which is used as a weighting coefficient. Finally, the weighted average distance D, i.e., the initial distance between the Bluetooth key and the vehicle, is calculated from the initial anchor point distance values ​​of the preset number of anchor points based on the confidence levels. A higher distance ranking indicates stronger signal strength and a higher confidence level. The specific confidence level value can be set according to actual conditions.

[0101] Specifically, the aforementioned credibility is a weight. Let the credibility be a, the initial anchor point distance be b, and the weighted average distance D be calculated as follows: D = a1*b1 + a2*b2 + a3*b3...

[0102] For example, the preset number of anchor points is 8. The initial anchor point distance values ​​of the 8 anchor points are sorted, and confidence levels a1 to a8 are assigned according to the sorting results. The initial distance value is then calculated using the weighted average distance calculation formula mentioned above.

[0103] Example 3

[0104] Figure 5 This is a flowchart of another vehicle Bluetooth key positioning method provided in Embodiment 3 of the present invention; the technical solution of this embodiment is another implementation of the optional technical solution in the above embodiments to determine the current initial area positioning result based on the initial collected data. A threshold is preset, and the initial collected data is compared with the preset threshold. Based on the comparison result between the initial collected data and the preset threshold, the initial distance value can be calculated more accurately.

[0105] Optionally, determining the current initial area positioning result based on the initial acquired data includes: comparing the maximum RSSI value in the initial acquired data with a preset threshold, and determining the current initial area positioning result based on the comparison result. If the comparison result is greater than or equal to the preset threshold, the current initial area positioning result is determined to be the first key area; if the comparison result is less than the preset threshold, the current initial area positioning result is determined to be the third key area. Positioning the initial area through threshold comparison can improve positioning efficiency and accuracy.

[0106] like Figure 4 As shown, the method includes:

[0107] S310, Acquire initial data from the vehicle.

[0108] The initial data collection includes the RSSI values ​​of the received signal strength of a preset number of Bluetooth anchor points in the vehicle that receive the Bluetooth signal emitted by the Bluetooth key.

[0109] S320. Input the initial collected data into the preset ranging model to obtain the initial anchor point distance value corresponding to each Bluetooth anchor point.

[0110] The data to be fitted for determining the preset ranging model can be obtained in the following ways:

[0111] 1) For each Bluetooth anchor point in the preset number of Bluetooth anchor points, collect multiple sets of calibration data. Each set of calibration data includes multiple sets of calibration data with the same preset distance in different directions. Different sets of calibration data correspond to different preset distances. The direction is the relative direction between the Bluetooth key and the Bluetooth anchor point.

[0112] 2) Perform a preset filtering process on the calibration data to obtain filtered calibration data.

[0113] 3) For each preset distance, the corresponding filtered calibration data are fused and calculated using a preset calculation method to obtain the corresponding data to be fitted.

[0114] Optionally, the preset ranging model includes at least two ranging sub-models, with different ranging sub-models corresponding to different numerical ranges based on RSSI values. The RSSI values ​​in the initial collected data are input into the ranging sub-model corresponding to the numerical range to determine the corresponding initial anchor point distance value based on the output of the ranging sub-model.

[0115] Optionally, the data to be fitted for determining each ranging sub-model can also be obtained through the methods described in 1), 2), and 3) above.

[0116] S330. Determine the weight coefficients corresponding to the initial anchor point distance values.

[0117] Determine the weight coefficients corresponding to the above initial anchor point distance values, wherein at least two initial anchor point distance values ​​are negatively correlated with their corresponding weight coefficients.

[0118] S340. Based on the weighting coefficients, calculate the weighted average of the initial anchor point distance values ​​to obtain the initial distance value between the Bluetooth key and the vehicle.

[0119] S350. Compare the initial collected data with the preset threshold, and determine the initial area positioning result based on the comparison result.

[0120] For example, a threshold is preset to separate two non-adjacent areas. A pre-classification model for the area is set up, and the maximum RSSI value in the initial collected data is input into the pre-classification model for comparison with the preset threshold. If the comparison result is greater than or equal to the preset threshold, the current initial area positioning result is determined to be the first key area (such as the unlocking area); if the comparison result is less than the preset threshold, the current initial area positioning result is determined to be the third key area (such as the welcoming area).

[0121] The preset threshold is the value with the most suitable discrimination after data collection.

[0122] For example, data is collected in the unlock area and the welcome area separately (e.g., 200 frames each). The RSSI values ​​of the 8 anchor points in each frame are sorted to obtain a queue, and the extreme values ​​are taken. For the unlock area, the minimum value is taken, resulting in 200 unlock area data points, denoted as the first set; for the welcome area, the maximum value is taken, resulting in 200 welcome area data points, denoted as the second set. The data distribution characteristics of the first and second sets are analyzed, and the value with the most suitable discrimination is selected as the threshold.

[0123] For example, the preset threshold can be set according to the actual situation. For instance, in the implementation of this invention, -61.5dB can be selected as the threshold. When the RSSI value is -61.5dB, its discrimination is most suitable as the threshold. The threshold of -61.5dB signal strength is not fixed. It should be selected separately for different vehicle models and different anchor points according to the actual situation.

[0124] When the maximum RSSI value in the initial data acquisition is greater than or equal to -61.5dB, the current initial area positioning result is the first key area, i.e., the unlocking area; when the maximum RSSI value in the initial data acquisition is less than -61.5dB, the current initial area positioning result is the third key area, i.e., the welcoming area.

[0125] A car's keyless entry system (Passive Keyless Entry, or PKE for short) typically divides the area around the vehicle into several zones. For example, in this embodiment of the invention, the area within 2 meters of the vehicle body is designated as the unlocking zone, 2-4 meters as the reserved zone, 4-7 meters as the locking zone, 7-10 meters as the welcoming zone, and greater than 10 meters as the connection zone. This invention does not impose any limitations on the distance divisions or naming conventions.

[0126] For example, the first key area is the unlocking area in this embodiment of the invention, the second key area is the locking area in this embodiment of the invention, and the third key area is the welcoming area in this invention. Each key area can also be any area such as an unlocking area, a reserved area, a locking area, a welcoming area, or a connecting area; this embodiment of the invention does not limit this.

[0127] S360. Correct the initial distance value based on the current initial area positioning result to obtain the target distance value.

[0128] For example, if the current initial area positioning result is a first key area, the initial distance value is corrected in the first way to obtain a target distance value, wherein the target distance value is less than the initial distance value; if the current initial area positioning result is a third key area, the initial distance value is corrected in the second way to obtain a target distance value, wherein the target distance value is greater than the initial distance value.

[0129] S370. Determine the target area location result based on the target distance value.

[0130] The current target area location result is determined based on the target distance value. The target area location result includes the first key area, the second key area, and the third key area.

[0131] This invention acquires initial data from the vehicle and inputs it into a preset ranging model to obtain the initial anchor point distance value for each Bluetooth anchor point. It then determines the weight coefficients corresponding to these initial anchor point distance values ​​and calculates a weighted average of the initial anchor point distance values ​​based on these weight coefficients. This yields the initial distance between the Bluetooth key and the vehicle. The acquired data is then input into a region pre-classification model to compare the maximum RSSI value in the initial acquired data with a preset threshold, obtaining the initial region positioning result. The initial distance value is then corrected based on the initial region positioning result to finally determine the target region positioning result. This method improves the accuracy and reduces the error in calculating the distance to a single anchor point, and is applicable in different directions. In different directions, the distance measurement results for the same location remain stable without significant deviation. Even when the overall distance is unknown, it can pre-distinguish the unlocking area and the welcoming area with an accuracy rate exceeding 96%. Based on the pre-distinguished unlocking and welcoming areas, an optimized and corrected distance can be calculated, which more closely matches the actual distance. The accuracy rate of locating the key in the unlocking area, locking area, and welcoming area all reached 99%, compared to only 68% before using the method of this invention. The method of this invention has greatly improved the accuracy of Bluetooth key positioning, and greatly enhanced the user experience of the keyless entry system.

[0132] Example 4

[0133] Figure 6 This is a schematic diagram of a vehicle Bluetooth key positioning device provided in Embodiment 4 of the present invention. Figure 6 As shown, the device includes: an initial distance calculation module 61, an initial region determination module 62, an initial distance correction module 63, and a target region determination module 64.

[0134] The initial distance calculation module 61 is used to acquire initial data in the vehicle and calculate the initial distance between the Bluetooth key and the vehicle based on the initial data. The initial data includes the received signal strength (RSSI) values ​​of a preset number of Bluetooth anchor points in the vehicle that receive the Bluetooth signal emitted by the Bluetooth key.

[0135] The initial area determination module 62 is used to determine the current initial area positioning result based on the initial collected data; wherein, the initial area positioning result includes a first key area and a third key area, the key area is divided based on the distance between the Bluetooth key and the vehicle, and the boundary values ​​of the distance ranges corresponding to the first key area, the second key area and the third key area increase sequentially;

[0136] The initial distance correction module 63 is used to correct the initial distance value according to the current initial area positioning result to obtain the target distance value;

[0137] The target area determination module 64 is used to determine the current target area positioning result based on the target distance value. The target area positioning result includes the first key area, the second key area, and the third key area.

[0138] The vehicle Bluetooth key positioning device provided in this embodiment of the invention pre-distinguishes non-adjacent key areas and makes targeted corrections to the initial distance value based on the discrimination results, thereby making the distance value used to determine the final key area more accurate. This improves the accuracy of Bluetooth key area positioning results based on Bluetooth RSSI, greatly enhances the performance of the vehicle Bluetooth key positioning system, and strengthens the user experience of Bluetooth keys.

[0139] Optionally, the initial distance correction module 63 includes:

[0140] The first correction unit is used to perform a first correction process on the initial distance value when the current initial area positioning result is the first key area, to obtain the target distance value, wherein the target distance value is less than the initial distance value;

[0141] The second correction unit is used to perform a second correction process on the initial distance value when the current initial area positioning result is the third key area, to obtain the target distance value, wherein the target distance value is greater than the initial distance value.

[0142] Optionally, the initial region determination module 62 includes:

[0143] The first data input unit is used to input the initial collected data into the preset positioning model and determine the current initial area positioning result based on the output result of the preset positioning model.

[0144] The preset localization model includes a neural network model, which is trained in the following way:

[0145] The sample data is input into a preset neural network model to obtain the sample positioning result. The sample data carries a positioning result label, which includes the first key area and the third key area. The sample data includes the sample RSSI values ​​corresponding to the preset number of Bluetooth anchors in the vehicle.

[0146] The loss relationship is calculated based on the sample localization results and the localization result labels, and the preset neural network model is trained based on the loss relationship.

[0147] Optionally, the initial region determination module 62 includes:

[0148] A numerical comparison unit is used to compare the maximum RSSI value in the initial collected data with a preset threshold.

[0149] The first determining unit is configured to determine the current initial area positioning result as the first key area if the comparison result is greater than or equal to the preset threshold.

[0150] The second determining unit is used to determine the current initial area positioning result as the third key area if the comparison result is less than the preset threshold.

[0151] Optionally, the initial distance calculation module 61 includes:

[0152] The second data input unit is used to input the initial collected data into a preset ranging model to obtain the initial anchor point distance value corresponding to each Bluetooth anchor point. The preset ranging model contains at least two ranging sub-models, and different ranging sub-models correspond to different numerical ranges based on RSSI values. The RSSI value in the initial collected data is input into the ranging sub-model corresponding to its numerical range to determine the corresponding initial anchor point distance value based on the output result of the ranging sub-model.

[0153] The distance calculation unit is used to calculate the initial distance value between the Bluetooth key and the vehicle based on the initial anchor point distance value.

[0154] Optionally, the initial distance calculation module 61 includes:

[0155] The second data input unit is used to input the initial collected data into the preset ranging model to obtain the initial anchor point distance value corresponding to each Bluetooth anchor point.

[0156] A distance calculation unit is used to calculate the initial distance value between the Bluetooth key and the vehicle based on the initial anchor point distance value;

[0157] The data to be fitted for determining the preset ranging model is obtained in the following way:

[0158] For each of the preset number of Bluetooth anchor points, multiple sets of calibration data are collected. Each set of calibration data includes multiple sets of calibration data with the same preset distance in different directions. Different sets of calibration data correspond to different preset distances. The direction is the relative direction between the Bluetooth key and the Bluetooth anchor point.

[0159] The calibration data is subjected to a preset filtering process to obtain filtered calibration data;

[0160] For each preset distance, the corresponding filtered calibration data is fused and calculated using a preset calculation method to obtain the corresponding data to be fitted.

[0161] Optionally, the distance calculation unit includes:

[0162] The weight coefficient determination subunit is used to determine the weight coefficients corresponding to the initial anchor point distance values, wherein at least two initial anchor point distance values ​​are negatively correlated with their corresponding weight coefficients;

[0163] The initial distance calculation subunit calculates the weighted average of the initial anchor point distance values ​​based on the weighting coefficients to obtain the initial distance value between the Bluetooth key and the vehicle.

[0164] The vehicle Bluetooth key positioning device provided in this embodiment of the invention can execute the vehicle Bluetooth key positioning method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0165] Example 5

[0166] Figure 7 A schematic diagram of the structure of a vehicle 10 that can be used to implement embodiments of the present invention is shown. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the invention described and / or claimed herein.

[0167] like Figure 7 As shown, vehicle 10 includes at least one processor 11 and a memory, such as read-only memory (ROM) 12 and random access memory (RAM) 13, communicatively connected to at least one processor 11. The memory stores computer programs executable by at least one processor. Processor 11 can perform various appropriate actions and processes based on the computer program stored in ROM 12 or loaded from storage unit 18 into RAM 13. RAM 13 can also store various programs and data required for the operation of vehicle 10. Processor 11, ROM 12, and RAM 13 are interconnected via bus 14. Input / output (I / O) interface 15 is also connected to bus 14.

[0168] Multiple components in vehicle 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows vehicle 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0169] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the vehicle Bluetooth key positioning method.

[0170] In some embodiments, the vehicle Bluetooth key location method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on vehicle 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the vehicle Bluetooth key location method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the vehicle Bluetooth key location method by any other suitable means (e.g., by means of firmware).

[0171] Various embodiments 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-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0172] Computer programs used to implement 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, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0173] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0174] To provide interaction with a user, the systems and techniques described herein can be implemented on vehicle 10, which includes: 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 pointing device (e.g., a mouse or trackball) through which the user provides input to vehicle 10. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0175] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0176] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0177] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0178] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for locating a vehicle Bluetooth key, characterized in that, include: Acquire initial data from the vehicle and calculate the initial distance between the Bluetooth key and the vehicle based on the initial data. The initial data includes the received signal strength (RSSI) values ​​of a preset number of Bluetooth anchor points in the vehicle that receive the Bluetooth signals emitted by the Bluetooth key. The initial area positioning result is determined based on the initial collected data. The initial area positioning result includes a first key area and a third key area. The key areas are divided based on the distance between the Bluetooth key and the vehicle. The boundary values ​​of the distance ranges corresponding to the first key area, the second key area and the third key area increase sequentially. The initial distance value is corrected based on the current initial area positioning result to obtain the target distance value; The current target area location result is determined based on the target distance value, wherein the target area location result includes the first key area, the second key area, and the third key area; The step of correcting the initial distance value based on the current initial area positioning result to obtain the target distance value includes: If the current initial area positioning result is the first key area, the initial distance value is subjected to a first correction process to obtain a target distance value, wherein the target distance value is less than the initial distance value; If the current initial area positioning result is the third key area, the initial distance value is subjected to a second correction process to obtain a target distance value, wherein the target distance value is greater than the initial distance value.

2. The method according to claim 1, characterized in that, The step of determining the current initial area positioning result based on the initial collected data includes: The initial collected data is input into a preset positioning model, and the current initial area positioning result is determined based on the output of the preset positioning model. The preset positioning model includes a machine learning model, which is trained in the following way: The sample data is input into a preset machine learning model to obtain the sample positioning result. The sample data carries a positioning result label, which includes the first key area and the third key area. The sample data includes the sample RSSI values ​​corresponding to the preset number of Bluetooth anchors in the vehicle. The loss relationship is calculated based on the sample location results and the location result labels, and the preset machine learning model is trained based on the loss relationship.

3. The method according to claim 1, characterized in that, The step of determining the current initial area positioning result based on the initial collected data includes: The maximum RSSI value in the initial collected data is compared with a preset threshold. If the comparison result is greater than or equal to the preset threshold, then the current initial area positioning result is determined to be the first key area; If the comparison result is less than the preset threshold, then the current initial area positioning result is determined to be the third key area.

4. The method according to claim 1, characterized in that, The calculation of the initial distance value between the Bluetooth key and the vehicle based on the initial collected data includes: The initial collected data is input into a preset ranging model to obtain the initial anchor point distance value corresponding to each Bluetooth anchor point. The preset ranging model contains at least two ranging sub-models, and different ranging sub-models correspond to different numerical ranges based on RSSI values. The RSSI values ​​in the initial collected data are input into the ranging sub-model corresponding to the numerical range to determine the corresponding initial anchor point distance value based on the output of the ranging sub-model. The initial distance between the Bluetooth key and the vehicle is calculated based on the initial anchor point distance value.

5. The method according to claim 1, characterized in that, The initial distance between the Bluetooth key and the vehicle is calculated based on the initial collected data, including: The initial collected data is input into a preset ranging model to obtain the initial anchor point distance value corresponding to each Bluetooth anchor point; Calculate the initial distance between the Bluetooth key and the vehicle based on the initial anchor point distance value; The data to be fitted for determining the preset ranging model is obtained in the following way: For each of the preset number of Bluetooth anchor points, multiple sets of calibration data are collected. Each set of calibration data includes multiple sets of calibration data with the same preset distance in different directions. Different sets of calibration data correspond to different preset distances. The direction is the relative direction between the Bluetooth key and the Bluetooth anchor point. The calibration data is subjected to a preset filtering process to obtain filtered calibration data; For each preset distance, the corresponding filtered calibration data is fused and calculated using a preset calculation method to obtain the corresponding data to be fitted.

6. The method according to claim 4 or 5, characterized in that, The calculation of the initial distance value between the Bluetooth key and the vehicle based on the initial anchor point distance value includes: Determine the weight coefficients corresponding to the initial anchor point distance values, wherein at least two initial anchor point distance values ​​are negatively correlated with their corresponding weight coefficients; Based on the weighting coefficients, the weighted average of the initial anchor point distance values ​​is calculated to obtain the initial distance value between the Bluetooth key and the vehicle.

7. A vehicle Bluetooth key positioning device, characterized in that, include: An initial distance calculation module is used to acquire initial data in the vehicle and calculate the initial distance between the Bluetooth key and the vehicle based on the initial data. The initial data includes the received signal strength (RSSI) values ​​of a preset number of Bluetooth anchor points in the vehicle that receive the Bluetooth signal emitted by the Bluetooth key. An initial area determination module is used to determine the current initial area positioning result based on the initial collected data. The initial area positioning result includes a first key area and a third key area. The key areas are divided based on the distance between the Bluetooth key and the vehicle. The boundary values ​​of the distance ranges corresponding to the first key area, the second key area, and the third key area increase sequentially. An initial distance correction module is used to correct the initial distance value based on the current initial area positioning result to obtain the target distance value; The target area determination module is used to determine the current target area positioning result based on the target distance value, wherein the target area positioning result includes the first key area, the second key area, and the third key area; The initial distance correction module includes: The first correction unit is used to perform a first correction process on the initial distance value when the current initial area positioning result is the first key area, to obtain the target distance value, wherein the target distance value is less than the initial distance value; The second correction unit is used to perform a second correction process on the initial distance value when the current initial area positioning result is the third key area, to obtain the target distance value, wherein the target distance value is greater than the initial distance value.

8. A vehicle, characterized in that, The vehicles include: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the vehicle Bluetooth key positioning method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the vehicle Bluetooth key positioning method according to any one of claims 1-6.

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