Position fingerprint library management method, computer device, storage medium and program product

Abstract

The application relates to a position fingerprint library management method, computer equipment, a storage medium and a program product. In a case where a reference device associated with a vehicle and a digital key are carried by the same object, at least two signal strength feature data of the digital key at each sampling point in a sampling area are acquired; position information of each sampling point is determined according to signal interaction information between the reference device and a first signal receiver on the vehicle at each sampling point; and a position fingerprint library of the digital key is managed according to the at least two signal strength feature data and the position information of each sampling point. On the one hand, the signal collection dimension is increased, so that the determined position fingerprint library of the digital key is more accurate; on the other hand, the accuracy of vehicle control based on the digital key no longer depends on the positioning accuracy of the digital key itself, and the accuracy of the vehicle control is also improved.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a location fingerprint database management method, computer equipment, storage medium, and program product. Background Technology

[0002] A digital key is a vehicle access control tool based on digital technology. It utilizes smart devices such as smartphones and smartwatches as carriers, and employs wireless communication technologies such as Bluetooth, Near Field Communication (NFC), and cellular networks to enable remote or near-field interaction with the vehicle, thereby completing a series of operations such as unlocking, starting, and authorizing vehicle sharing. Bluetooth positioning technology plays a crucial role in the application of digital keys.

[0003] In traditional technologies, digital key positioning systems typically rely on distance determination methods based on signal strength to achieve Bluetooth positioning. This method roughly estimates the distance between the key and the vehicle by measuring the strength of the Bluetooth signal. However, due to environmental factors such as obstacles and electromagnetic interference, the distance estimation based on Bluetooth signal strength is inaccurate, and vehicle control based on this estimated distance is also not precise enough. Summary of the Invention

[0004] Therefore, it is necessary to provide a location fingerprint database management method, computer equipment, storage medium, and program product to address the aforementioned technical problems, which can improve the accuracy of determining the distance between the digital key and the vehicle.

[0005] In a first aspect, this application provides a method for managing a location fingerprint database, the method comprising:

[0006] If it is determined that the reference device associated with the vehicle and the digital key are carried by the same object, at least two signal strength characteristic data of the digital key are acquired at each sampling point within the sampling area; and,

[0007] Based on the signal interaction information between the reference device at each sampling point and the first signal receiver on the vehicle, the location information of each sampling point is determined; wherein, the at least two signal strength characteristic data of each sampling point include the signal strength of at least two wireless signals of different power emitted by the digital key at the sampling point and received by the second signal receiver on the vehicle.

[0008] The location fingerprint database of the digital key is managed based on the at least two signal strength feature data of each sampling point and the location information.

[0009] In one embodiment, the at least two wireless signals of different power are transmitted by the same signal transmitter in the digital key.

[0010] In one embodiment, the sampling area includes multiple unit areas of the same size, and the location information of each sampling point includes the position coordinates of the sampling point relative to the vehicle;

[0011] Based on the at least two signal strength feature data of each sampling point and the location information, the location fingerprint database of the digital key is managed, including:

[0012] For each sampling point, based on the location coordinates of the sampling point, a unit region matching the location coordinates is determined from each unit region and used as the associated unit region of the sampling point;

[0013] The location fingerprint database of the digital key is managed based on the at least two signal strength feature data of each sampling point and the associated unit region.

[0014] In one embodiment, when the parking location to which the sampling area belongs is a location without a location fingerprint database, the location fingerprint database of the digital key is managed based on the at least two signal strength feature data of each sampling point and the associated unit area, including:

[0015] Based on the at least two signal strength feature data of each sampling point and the associated unit region, at least two signal strength feature data of each associated unit region are determined;

[0016] Each of the associated unit regions is bound to the corresponding at least two signal strength feature data to create a location fingerprint database of the digital key at the parking location.

[0017] In one embodiment, the reference device is the physical key of the vehicle.

[0018] In one embodiment, the physical key supports ultra-wideband (UWB) wireless communication.

[0019] In one embodiment, the location fingerprint database of the digital key is managed based on the at least two signal strength feature data of each sampling point and the location information, including:

[0020] If the current meteorological environment data of the digital key does not match the reference meteorological environment data for constructing the location fingerprint database of the parking location of the digital key in the sampling area, the at least two signal strength feature data of each sampling point under the current meteorological environment data are converted to the at least two signal strength feature data of each sampling point under the reference meteorological environment data based on the meteorological environment influence model.

[0021] The location fingerprint database of the digital key is managed based on the location information of each sampling point and the at least two signal strength feature data under the reference meteorological environment data;

[0022] After managing the location fingerprint database of the digital key based on the at least two signal strength feature data of each sampling point and the location information, the method further includes:

[0023] Upon detecting a positioning command for the digital key, acquire at least two signal strength characteristic data of the digital key at its current location under real-time meteorological environmental data;

[0024] Convert the at least two signal strength feature data of the current location point under the real-time meteorological environment data to the at least two signal strength feature data of the current location point under the reference meteorological environment data;

[0025] The current location information of the digital key is determined based on the location fingerprint database of the parking location and the at least two signal strength feature data of the current location under the reference meteorological environment data.

[0026] In one embodiment, the location fingerprint database of the digital key is managed based on the at least two signal strength feature data of each sampling point and the location information, including:

[0027] When the current meteorological environment data of the digital key matches the reference meteorological environment data for constructing the location fingerprint database of the digital key at the parking location in the sampling area, the location fingerprint database of the digital key is managed according to the location information of each sampling point and the at least two signal strength feature data under the current meteorological environment data.

[0028] After managing the location fingerprint database of the digital key based on the at least two signal strength feature data of each sampling point and the location information, the method further includes:

[0029] Upon detecting a positioning command for the digital key, acquire at least two signal strength characteristic data of the digital key at its current location under real-time meteorological environmental data;

[0030] Convert the at least two signal strength feature data of the current location point under the real-time meteorological environment data to the at least two signal strength feature data of the current location point under the reference meteorological environment data;

[0031] The current location information of the digital key is determined based on the location fingerprint database of the parking location and the at least two signal strength feature data of the current location under the reference meteorological environment data.

[0032] In one embodiment, the meteorological environmental data includes at least two types of environmental factor data, and the method further includes:

[0033] If the difference between the key environmental factor data in the current meteorological environment data and the key environmental factor data in the reference meteorological environment data is greater than the factor error corresponding to the key environmental factor, then it is determined that the current meteorological environment data of the digital key does not match the reference meteorological environment data when constructing the location fingerprint database of the digital key at the parking location.

[0034] Among them, the key environmental factors have a greater impact on signal strength than other environmental factors.

[0035] In one embodiment, determining that the reference device and digital key associated with the vehicle are carried by the same object includes:

[0036] Obtain the field strength signal strength between the reference device and the digital key;

[0037] If the field strength signal strength is greater than a preset strength threshold, it is determined that the reference device and digital key associated with the vehicle are carried by the same object.

[0038] Secondly, this application also provides a location fingerprint database management device, the device comprising:

[0039] A determining module is configured to, when determining that the reference device associated with the vehicle and the digital key are carried by the same object, acquire at least two signal strength characteristic data of the digital key at each sampling point within a sampling area; and, based on signal interaction information between the reference device at each sampling point and a first signal receiver on the vehicle, determine the location information of each sampling point; wherein the at least two signal strength characteristic data of each sampling point include the signal strength of at least two wireless signals of different power emitted by the digital key at the sampling point and received by a second signal receiver on the vehicle.

[0040] The management module is used to manage the location fingerprint database of the digital key based on the at least two signal strength feature data of each sampling point and the location information.

[0041] Thirdly, this application also provides a computer device, the computer device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0042] If it is determined that the reference device associated with the vehicle and the digital key are carried by the same object, at least two signal strength characteristic data of the digital key are acquired at each sampling point within the sampling area; and,

[0043] Based on the signal interaction information between the reference device at each sampling point and the first signal receiver on the vehicle, the location information of each sampling point is determined; wherein, the at least two signal strength characteristic data of each sampling point include the signal strength of at least two wireless signals of different power emitted by the digital key at the sampling point and received by the second signal receiver on the vehicle.

[0044] The location fingerprint database of the digital key is managed based on the at least two signal strength feature data of each sampling point and the location information.

[0045] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0046] If it is determined that the reference device associated with the vehicle and the digital key are carried by the same object, at least two signal strength characteristic data of the digital key are acquired at each sampling point within the sampling area; and,

[0047] Based on the signal interaction information between the reference device at each sampling point and the first signal receiver on the vehicle, the location information of each sampling point is determined; wherein, the at least two signal strength characteristic data of each sampling point include the signal strength of at least two wireless signals of different power emitted by the digital key at the sampling point and received by the second signal receiver on the vehicle.

[0048] The location fingerprint database of the digital key is managed based on the at least two signal strength feature data of each sampling point and the location information.

[0049] Fifthly, this application also provides a computer program product, which includes a computer program that, when executed by a processor, performs the following steps:

[0050] If it is determined that the reference device associated with the vehicle and the digital key are carried by the same object, at least two signal strength characteristic data of the digital key are acquired at each sampling point within the sampling area; and,

[0051] Based on the signal interaction information between the reference device at each sampling point and the first signal receiver on the vehicle, the location information of each sampling point is determined; wherein, the at least two signal strength characteristic data of each sampling point include the signal strength of at least two wireless signals of different power emitted by the digital key at the sampling point and received by the second signal receiver on the vehicle.

[0052] The location fingerprint database of the digital key is managed based on the at least two signal strength feature data of each sampling point and the location information.

[0053] The aforementioned location fingerprint database management method, computer equipment, storage medium, and program product acquire at least two signal strength characteristic data of the digital key at each sampling point within a sampling area, when it is determined that the reference device associated with the vehicle and the digital key are carried by the same object; and determine the location information of each sampling point based on the signal interaction information between the reference device and the first signal receiver on the vehicle at each sampling point; and then manage the location fingerprint database of the digital key based on the at least two signal strength characteristic data and the location information of each sampling point. This location fingerprint database management method, on the one hand, leverages the mobile association and binding characteristics of the reference device and digital key. It utilizes the signal interaction between the vehicle and the reference device to determine the distance between the digital key and the vehicle, replacing the distance estimation based on the signal strength of the interaction between the digital key and the vehicle. This bypasses the low positioning accuracy of digital keys. By associating the signal strength feature data determined by the interaction between the vehicle and the digital key with the positioning determined by the interaction between the vehicle and the reference device, during the application phase of the location fingerprint database, the digital key vehicle control function is based on the signal strength feature data between the digital key and the vehicle, unaffected by the accuracy of the signal strength-to-distance conversion. In other words, the accuracy of vehicle control based on the digital key no longer depends on the positioning accuracy of the digital key itself, thus improving the precision of vehicle control. On the other hand, by introducing the function of the digital key to emit signals of different power, multiple signal strength feature data can be acquired for each sampling point, increasing the signal acquisition dimension and enriching the feature data in the location fingerprint database, thereby improving the precision of vehicle control. Attached Figure Description

[0054] Figure 1A This is a flowchart illustrating a location fingerprint database management method in one embodiment;

[0055] Figure 1B This is a schematic diagram of sampling points in one embodiment;

[0056] Figure 2 This is a flowchart illustrating the management of a location fingerprint database for a digital key in one embodiment;

[0057] Figure 3This is a flowchart illustrating the process of determining the associated unit region to which the location coordinates of a sampling point belong in one embodiment.

[0058] Figure 4 This is a schematic diagram illustrating the division of the sampling area into multiple region blocks in one embodiment;

[0059] Figure 5 This is a flowchart illustrating the process of determining the associated unit region to which the location coordinates of a sampling point belong in another embodiment;

[0060] Figure 6 This is a schematic diagram illustrating the division of the sampling area into multiple sub-regions in one embodiment;

[0061] Figure 7 This is a flowchart illustrating the process of determining the associated unit region to which the location coordinates of a sampling point belong in yet another embodiment;

[0062] Figure 8 This is a schematic diagram of the area range of the target region block in one embodiment;

[0063] Figure 9 This is a flowchart illustrating the process of determining the associated unit region to which the location coordinates of a sampling point belong in another embodiment;

[0064] Figure 10 This is a flowchart illustrating the process of establishing a location fingerprint database for a digital key in one embodiment;

[0065] Figure 11 This is a schematic diagram illustrating the setting of target locations that allow the establishment of a location fingerprint database in one embodiment;

[0066] Figure 12A This is a schematic diagram of signal strength characteristics under different meteorological environments in one embodiment.

[0067] Figure 12B This is a flowchart illustrating the management and use of a location fingerprint database in one embodiment;

[0068] Figure 13 This is a flowchart illustrating the management and use of the location fingerprint database in another embodiment;

[0069] Figure 14 This is a schematic diagram of a process for determining that the reference device and the digital key are carried by the same object in one embodiment;

[0070] Figure 15 This is a flowchart illustrating the location fingerprint database management method in another embodiment;

[0071] Figure 16 This is a schematic diagram of the location fingerprint database management device in one embodiment;

[0072] Figure 17This is a schematic diagram of the hardware structure of a computer device in one embodiment;

[0073] Figure 18 This is a schematic diagram of the hardware structure of a computer device in another embodiment. Detailed Implementation

[0074] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0075] The location fingerprint database management method provided in this application can be applied to contactless vehicle control scenarios. This method can be executed by a computer device, specifically by a controller deployed on the vehicle, or by a server.

[0076] In one embodiment, such as Figure 1A As shown, a location fingerprint database management method is provided, illustrated by a controller deployed on a vehicle, comprising the following steps:

[0077] S101, if it is determined that the reference device associated with the vehicle and the digital key are carried by the same object, at least two signal strength characteristic data of the digital key at each sampling point in the sampling area are obtained; and, based on the signal interaction information between the reference device at each sampling point and the first signal receiver on the vehicle, the location information of each sampling point is determined.

[0078] The reference device associated with the vehicle can be a standalone device capable of controlling the vehicle and possessing high positioning accuracy, such as a physical vehicle key. For example, when the reference device is a physical key, the sampling frequency of the physical key in fingerprint database management scenarios is higher than that in fingerprint database usage scenarios. Thus, in fingerprint database management scenarios—specifically, scenarios involving fingerprint database creation and updates—the higher sampling frequency of the physical key results in denser sampling points, leading to richer location information from the collected sampling points and improved fingerprint database positioning accuracy.

[0079] A digital key can be a device that enables remote control of a vehicle by registering it with a vehicle application; such as a mobile phone or watch.

[0080] In some optional implementations, the reference device and digital key may have one or more signal transmission functions, that is, the reference device and digital key may transmit one or more wireless signals, such as Bluetooth signals, Wireless Fidelity (WiFi) signals, etc. Optionally, in the scenario of the embodiments of this application, the reference device and digital key may transmit the same or different wireless signals. Correspondingly, the first signal receiver and the second signal receiver in the embodiments of this application may be the same signal receiver or different signal receivers.

[0081] In some alternative implementations, if the reference device is a physical key, the physical key can support ultra-wideband (UWB) wireless communication. UWB wireless communication technology has the characteristics of high positioning accuracy, which makes the location information of the determined sampling point more accurate, thereby improving the reliability of the location fingerprint database of the digital key.

[0082] In some alternative implementations, to enrich the feature data in the location fingerprint database and improve the accuracy of vehicle control, the digital key in this application embodiment can transmit multiple wireless signals, for example, at least two wireless signals with different power levels. Exemplarily, the at least two wireless signals with different power levels can be transmitted by different or the same signal transmitter in the digital key. For ease of management of the location fingerprint database, in this application embodiment, the at least two wireless signals with different power levels are transmitted by the same signal transmitter in the digital key. This allows for the reception of at least two wireless signals with different power levels from the digital key at the same location, which improves the reliability of the signal strength feature data of the received wireless signals compared to receiving a single-power wireless signal.

[0083] The sampling area can be a region within a preset range of the vehicle, excluding the interior area. For example, it could be a circle with a preset radius centered on the vehicle; or an area corresponding to a graphic of a preset size centered on the vehicle; or it could be a pre-defined designated area, such as a pre-set home address, company address, or frequently visited location. Each sampling point within the sampling area can be any location within the sampling area, or a location point traversed by an object carrying the reference device and digital key within the sampling area. For example, see... Figure 1B , Figure 1B A schematic diagram of sampling points is provided, where each point represents the location reached when the digital key and reference device are simultaneously carried by the same object. E1 represents the vehicle interior area, E2 represents the unit area, and E3 represents the sampling area.

[0084] In this embodiment, the object carrying the reference device and the digital key can be a user with vehicle control authority. For example, the strength of the field signal between the reference device and the digital key can be used to determine whether the reference device and the digital key are carried by the same object.

[0085] Optionally, if it is determined that the reference device associated with the vehicle and the digital key are carried by the same object, at least two signal strength characteristic data of the digital key at each sampling point within the sampling area can be obtained through a second signal receiver on the vehicle. The at least two signal strength characteristic data at each sampling point include the signal strength of at least two wireless signals of different powers emitted by the digital key at the sampling point, received by the second signal receiver on the vehicle.

[0086] Furthermore, the location information of each sampling point can be determined based on the signal interaction information between the reference device and the first signal receiver on the vehicle at each sampling point. For example, the reference device transmits a wireless signal to the vehicle, and the first signal receiver receives the wireless signal transmitted by the reference device, determining the identity and location information of the reference device based on the received wireless signal. The location information can be the coordinates of the reference device relative to the vehicle.

[0087] S102, manage the location fingerprint database of the digital key based on at least two signal strength feature data and location information of each sampling point.

[0088] In this context, "location fingerprint" can be understood as associating a location in the actual environment with certain characteristic information. For the same location, the characteristic information is unique, just like its "fingerprint." In this embodiment, the location fingerprint of the digital key can be understood as linking the location information of the digital key relative to the vehicle with the corresponding signal strength characteristic data. One location information corresponds to one or a set of signal strength characteristic data. The location fingerprint database can be understood as a collection of location fingerprints of the digital key at multiple sampling points, including the correspondence between the location information of each sampling point and at least two types of signal strength characteristic data. When determining the relative distance between the digital key and the vehicle based on the location fingerprint database, the location information can be matched based on at least two types of signal strength characteristic data of the digital key received by the vehicle's controller. Then, the relative distance between the digital key and the vehicle can be determined based on the location information, facilitating the automatic execution of preset actions on the vehicle when it is determined that the digital key is within the vehicle's controllable range.

[0089] Optionally, managing the location fingerprint database can involve creating or updating it. In some embodiments, if no location fingerprint database for the digital key has been established for the parking locations within the sampling area, a location fingerprint database for the digital key at the parking locations within the sampling area can be established based on at least two signal strength feature data and location information from each sampling point. If a location fingerprint database for the digital key has already been established for the parking locations within the sampling area, it can be updated based on at least two signal strength feature data and location information from each sampling point.

[0090] The aforementioned location fingerprint database management method acquires at least two signal strength feature data of the digital key at each sampling point within the sampling area when it is determined that the reference device associated with the vehicle and the digital key are carried by the same object; and determines the location information of each sampling point based on the signal interaction information between the reference device and the first signal receiver on the vehicle at each sampling point; and then manages the location fingerprint database of the digital key based on the at least two signal strength feature data and the location information of each sampling point. The above scheme, on the one hand, leverages the mobile association and binding characteristics of the reference device and the digital key. It utilizes the signal interaction between the vehicle and the reference device to determine the distance between the digital key and the vehicle, replacing the distance estimation based on the signal strength of the interaction between the digital key and the vehicle. This bypasses the low positioning accuracy of the digital key. By associating the signal strength feature data determined by the interaction between the vehicle and the digital key with the positioning determined by the interaction between the vehicle and the reference device, during the location fingerprint database application phase, the digital key vehicle control function is based on the signal strength feature data between the digital key and the vehicle, unaffected by the accuracy of the signal strength-to-distance conversion. In other words, the accuracy of vehicle control based on the digital key no longer depends on the positioning accuracy of the digital key itself, thus improving the precision of vehicle control. On the other hand, by introducing the function of the digital key to emit signals of different power, multiple signal strength feature data can be acquired for each sampling point, increasing the signal acquisition dimension and enriching the feature data in the location fingerprint database, thereby improving the precision of vehicle control.

[0091] In some alternative implementations, to improve the accuracy of the location fingerprint database, the sampling area can be divided into multiple unit regions of the same size. Please see below. Figure 1B The unit region can be a region of a preset size obtained by equally dividing the sampling area. Correspondingly, the location information of each sampling point can include the position coordinates of the sampling point relative to the vehicle.

[0092] Based on this, see Figure 2 , Figure 2 A flowchart illustrating the management of a location fingerprint database for digital keys is provided, specifically including the following steps:

[0093] S201, For each sampling point, based on the location coordinates of the sampling point, determine the unit region with the same location coordinates from each unit region, and use it as the associated unit region of the sampling point.

[0094] For example, the range of each unit region can be predetermined. This can be achieved by determining the range of values ​​for the x-coordinate and y-coordinate of each unit region. Then, for each sampling point, assuming its position coordinates are (x, y), the range within which (x, y) falls can be determined based on the position coordinates (x, y) and the range of each unit region. The unit region corresponding to the range within which (x, y) falls is then used as the unit region matching the position coordinates, and this unit region is then used as the associated unit region of the sampling point.

[0095] S202, manage the location fingerprint database of the digital key based on at least two signal strength characteristic data of each sampling point and the associated unit area.

[0096] Optionally, at least two signal strength feature data points and associated unit areas can be linked at each sampling point. If a location fingerprint database for the digital key at the parking location to which the sampling area belongs has not been established, a location fingerprint database for the digital key at the parking location to which the sampling area belongs can be established based on at least two signal strength feature data points and associated unit areas at each sampling point. If a location fingerprint database for the parking location to which the sampling area belongs has already been established, the at least two signal strength feature data points associated with the corresponding unit areas in the established location fingerprint database for the digital key can be updated based on at least two signal strength feature data points and associated unit areas at each sampling point.

[0097] In this embodiment of the application, by dividing the sampling area into multiple unit areas of the same size, and then managing the location fingerprint database of the digital key based on at least two signal strength feature data of each sampling point and the associated unit area, the accuracy of the location fingerprint database can be improved.

[0098] In order to more quickly determine the associated unit region to which the location coordinates of the sampling point belong, in some examples of this embodiment, the sampling area can be divided into at least two region blocks, and each region block includes at least two unit regions.

[0099] Based on this, see Figure 3 , Figure 3 A flowchart is provided to determine the associated unit region to which the location coordinates of a sampling point belong, specifically including the following steps:

[0100] S301, determine the target region block from each region block based on the location coordinates of the sampling points and the region location range of each region block.

[0101] For example, see Figure 4 , Figure 4 A schematic diagram is provided for dividing a sampling area into multiple region blocks. For example, the sampling area can be divided into region block A, region block B, region block C, region block D, and region block E.

[0102] For example, coordinate points (x0, y0) and (x1, y1) can be pre-defined. For instance, the coordinate point at the lower left of the outer boundary of the vehicle's interior area can be designated as (x0, y0), and the coordinate point at the upper right of the outer boundary of the vehicle's interior area can be designated as (x1, y1). The area range of each region block is determined using these coordinate points (x0, y0) and (x1, y1). For example, the range of region block A can be a range where the x-coordinate is greater than x1 and the y-coordinate is greater than y1; the range of region block C can be a range where the x-coordinate is greater than x1 and the y-coordinate is less than or equal to y1; the range of region block E can be a range where the x-coordinate is greater than x0 and less than x1, and the y-coordinate is less than y0; the range of region block B can be a range where the x-coordinate is less than x1 and the y-coordinate is greater than y1; and the range of region block D can be a range where the x-coordinate is less than x0 and the y-coordinate is less than y1. The coordinates of the region boundaries can be considered as belonging to any region block adjacent to those boundaries.

[0103] For example, the region to which the location coordinates of the sampling point belong can be determined based on the location coordinates of the sampling point and the regional location range of each region, and that region can be used as the target region.

[0104] S302, Based on the location coordinates of the sampling point, determine the unit region within the target area block that matches the location coordinates, and use it as the associated unit region of the sampling point.

[0105] For example, the target region block includes multiple unit regions. After determining the target region block, it is possible to traverse within the target region block to determine the unit region to which the location coordinates of the sampling point belong, that is, the unit region that matches the location coordinates, and use the unit region as the associated unit region of the sampling point.

[0106] In this embodiment of the application, by dividing the sampling area into multiple area blocks, the target area block to which the location coordinates of the sampling point belong is first determined, and then the associated unit area to which the location coordinates of the sampling point belong is determined within the target area block. This can narrow the range of unit area determination and improve the efficiency of determining the associated unit area to which the location coordinates of the sampling point belong.

[0107] Optionally, to more quickly determine the associated unit region to which the location coordinates of the sampling point belong, the vehicle's location can be taken as the center of the sampling area. That is, the vehicle is located at the center of the sampling area. Then, based on the control range corresponding to different functions of the digital key, the sampling area can be divided into multiple sub-areas, each containing multiple unit regions. Correspondingly, the location information of each sampling point also includes the region identifier of the sub-area to which the sampling point belongs, thereby determining the associated unit region to which the location coordinates of the sampling point belong within the sub-area.

[0108] Based on this, see Figure 5 , Figure 5 A flowchart illustrating another method for determining the associated unit region to which the location coordinates of a sampling point belong is provided, specifically including the following steps:

[0109] S501, determine the sub-region to which the sampling point belongs based on the area identifier corresponding to the sampling point.

[0110] For example, see Figure 6 , Figure 6 A schematic diagram illustrating the division of a sampling area into multiple sub-regions is provided. For example, the sampling area can be divided into sub-region 0, sub-region 1, sub-region 2, sub-region 3, and sub-region 4. Sub-region 0 is the vehicle interior area, sub-region 1 is the unlocking area, sub-region 2 is the locking area, sub-region 3 is the welcoming area, and sub-region 4 is the invalid area. The area identifier can be either an area number or an area name.

[0111] Optionally, the region identifier corresponding to each sampling point can be determined based on the region identifier of the sub-region to which the sampling point belongs, which is included in the location information of each sampling point; then, the sub-region to which each sampling point belongs can be determined based on the region identifier corresponding to each sampling point.

[0112] S502, based on the location coordinates of the sampling point, determine the unit region with the same location coordinates within the sub-region to which the sampling point belongs, and use it as the associated unit region of the sampling point.

[0113] For example, based on the location coordinates of the sampling point, the sub-region to which the sampling point belongs can be traversed to determine the unit region containing the location coordinates of the sampling point, that is, the unit region matching the location coordinates, and the unit region is used as the associated unit region of the sampling point.

[0114] In this embodiment of the application, by dividing the sampling area into multiple sub-regions, the sub-region to which each sampling point belongs is first determined based on the region identifier of the sub-region to which the sampling point belongs, which is included in the location information of each sampling point; then, the associated unit region to which the location coordinates of the sampling point belong is determined within the sub-region to which it belongs, which can narrow the range of unit region determination and thus improve the efficiency of determining the associated unit region to which the location coordinates of the sampling point belong.

[0115] In some alternative implementations, to further improve the efficiency of determining the associated unit region to which the location coordinates of the sampling point belong, the sampling region can be first divided into sub-regions, and then each sub-region can be divided into region blocks. For example, when the sampling region includes both sub-regions and region blocks, the sub-regions can include at least two region blocks.

[0116] Based on this, see Figure 4 and Figure 6 Suppose the sampling area is first divided into sub-regions 0, 1, 2, 3, and 4; the vehicle interior is designated as sub-region 0. Sub-regions 1, 2, 3, and 4 are then further divided into blocks A, B, C, D, and E. For example, the extent of each sub-region can be determined first, and then each sub-region can be further divided into blocks A, B, C, D, and E within its boundaries. For each sub-region, a reference point can be determined, which is used to define the extent of each block within that sub-region. When determining the reference point for sub-region 1, the reference point can be determined on the adjacent boundary between sub-region 1 and sub-region 0. For example, the coordinates of the upper right and lower left of the outer boundary of sub-region 0 can be used as the reference point for sub-region 1. When determining the reference point for sub-region 2, the reference point can be determined on the adjacent boundary between sub-region 2 and sub-region 1. For example, the coordinates of the upper right and lower left of the outer boundary of sub-region 1 can be used as the reference point for sub-region 2. When determining the reference point for sub-region 3, the reference point can be determined on the adjacent boundary between sub-region 3 and sub-region 2. For example, the coordinates of the upper right and lower left of the outer boundary of sub-region 2 can be used as the reference point for sub-region 3. When determining the reference point for sub-region 4, the reference point can be determined on the adjacent boundary between sub-region 4 and sub-region 3. For example, the coordinates of the upper right and lower left of the outer boundary of sub-region 3 can be used as the reference point for sub-region 4.

[0117] See Figure 7 , Figure 7Another flow chart for determining the associated unit area to which the position coordinates of the sampling point belong is provided. For example, first, based on the area identifier of the sub-region to which the sampling point belongs included in the position information of the sampling point, the sub-region to which the sampling point belongs can be determined. Assume that the sub-region to which the sampling point belongs is sub-region 1.

[0118] Among them, in sub-region 1, the coordinate points (x0, y0) and (x1, y1) are used to determine the area range of each area block. The position coordinates of the sampling point are (x, y). It should be noted that the sampling area does not include the area inside the vehicle, that is, the sampling point will not fall into the area inside the vehicle.

[0119] Based on this, the following steps can be executed:

[0120] S701, judge whether x is less than x1. If not, execute S702; if so, execute S705.

[0121] S702, judge whether y is less than y1. If so, execute S703; if not, execute S704.

[0122] S703, determine that the target area block to which the sampling point belongs is area block C.

[0123] S704, determine that the target area block to which the sampling point belongs is area block A.

[0124] S705, judge whether y is less than y1. If not, execute S706; if so, execute S707.

[0125] S706, determine that the target area block to which the sampling point belongs is area block B.

[0126] S707, judge whether x is less than x0. If so, execute S708; if not, execute S709.

[0127] S708, determine that the target area block to which the sampling point belongs is area block D. [[ID=3l]]

[0128] S709, determine that the target area block to which the sampling point belongs is area block E.

[0129] That is, first, the size between the abscissa x of the position coordinates of the sampling point and the abscissa x1 of the coordinate point (x1, y1) can be judged, and then the candidate area range to which the sampling point belongs can be determined from sub-region 1. For example, if x ≥x1, determine that the candidate area range is the range composed of area block A and area block C; if x < x1, determine that the candidate area range is the range composed of area block B, area block D and area block E.

[0130] Furthermore, according to the magnitude relationship between the ordinate y in the position coordinates of the sampling point and the ordinate y1 of the coordinate point (x1, y1), the target region block to which the sampling point belongs can be determined within the candidate region range. For example, if x < x1, and y < y1, then it is determined that the target region block to which the sampling point belongs is region block A; if x > x1, and y < y1, then it is determined that the target region block to which the sampling point belongs is region block C.

[0131] If x < x1, and y > y1, then it is determined that the target region block to which the sampling point belongs is region block B.

[0132] If x < x1, and y < y1, then it is necessary to further combine the magnitude relationship between the abscissa x in the position coordinates of the sampling point and the abscissa x0 of the coordinate point (x0, y0) in the region block to which the sampling point belongs, and determine the target region block to which the sampling point belongs within the candidate region range. For example, if x < x0, then it is determined that the target region block to which the sampling point belongs is region block D; otherwise, it is determined that the target region block to which the sampling point belongs is region block E.

[0133] Furthermore, the associated unit region matching the same position coordinates can be determined in the target region block.

[0134] Exemplarily, referring to Figure 8 , Figure 8 a schematic diagram of the region range of the target region block is provided. Among them, the spacing corresponding to the target region block can be preset. For example, the spacing is set to d, and then the region range of the target region block is determined to be from (x_0, y_0) to (x_0 + nd, y_0 + md). For example, (x_0, y_0) is the coordinate point of the lower left corner of the target region block, n is the number of spacing divisions of the region block in the x-axis direction, and m is the number of spacing divisions of the region block in the y-axis direction.

[0135] Based on the determination of the target region block, referring to Figure 9 , Figure 9 a schematic diagram for determining the associated unit region to which the position coordinates of the sampling point belong is provided.

[0136] Exemplarily, it is implemented through the following steps:

[0137] S901, assign n to i.

[0138] S902, determine whether x is less than x_0 + id. If so, execute S903; if not, execute S905.

[0139] S903, assign i - 1 to i.

[0140] S904, determine if i equals 0. If yes, execute S905; otherwise, return to execute S902.

[0141] S905, determine that the location coordinates of the sampling point are in the (i+1)th column.

[0142] S906, assign m to j.

[0143] S907, determine if y is less than y_0+jd. If yes, execute S908; otherwise, execute S910.

[0144] S908 assigns the value of j-1 to j.

[0145] S909, determine if j equals 0. If yes, execute S910; otherwise, return to execute S907.

[0146] S910, determine the associated unit region to which the sampling point belongs as row i+1 and column j+1.

[0147] We can assign i to n, and check if the x-coordinate of the sampling point is less than x_0+id. If it is, we can assign i to i-1 and check if i is equal to 0. If it is not equal, we continue to check if the x-coordinate of the sampling point is less than x_0+id. If i is equal to 0, or the x-coordinate of the sampling point does not meet the condition of being less than x_0+id, we determine that the sampling point is located in the (i+1)th column.

[0148] In some examples of this embodiment, the initial value of j can be assigned to m, and it can be determined whether the ordinate y in the position coordinates of the sampling point is less than y_0+jd. If so, j is assigned to j-1, and it can be determined whether j is equal to 0. If it is not equal to 0, it can be determined whether the ordinate y in the position coordinates of the sampling point is less than y_0+jd. If the ordinate y in the position coordinates of the sampling point does not meet the condition of being less than y_0+jd, or j is equal to 0, then the associated unit region to which the sampling point belongs is determined to be the (i+1)th row and the (j+1)th column.

[0149] In this embodiment of the application, by dividing the sampling area into multiple sub-regions and each sub-region into multiple region blocks, the determination range of the unit region can be further reduced, thereby improving the efficiency of determining the associated unit region to which the location coordinates of the sampling point belong.

[0150] In some alternative implementations, when the parking location to which the sampling area belongs is a location without a location fingerprint database, a location fingerprint database for the digital key at the parking location can be created by binding each associated unit area with at least two corresponding signal strength feature data.

[0151] Based on this, see Figure 10 , Figure 10 A flowchart illustrating the process of establishing a location fingerprint database for a digital key is provided, specifically including the following steps:

[0152] S1001, Based on at least two signal strength feature data of each sampling point and the associated unit region, determine at least two signal strength feature data of each associated unit region.

[0153] To avoid the impact of signal strength errors, for each sampling point, multiple second signal receivers can be used to receive at least two wireless signals from the digital key within the sampling area. Based on the signal strength of the at least two wireless signals received by each second signal receiver at the sampling point, the mean and standard deviation of each signal strength under each wireless signal at the sampling point are determined. Then, the signal strength, mean and standard deviation of each signal strength under each wireless signal at the sampling point are used as the signal strength feature data of each signal strength at the sampling point.

[0154] For example, taking signal strength characteristic data as an example, if N second signal receivers are deployed on the vehicle, then for each sampling point, the N second signal receivers will acquire the received signal strength indication (Rssi) values ​​of the N wireless signals transmitted by the digital key, and calculate the average of the N Rssi values, Rssi. mean and standard deviation Rssi std The calculation formula is as follows:

[0155]

[0156] Furthermore, the N Rssi values ​​and the mean Rssi mean and standard deviation Rssi std This serves as a signal strength characteristic data for that sampling point.

[0157] For example, an associated unit region may correspond to only one sampling point or multiple sampling points. When an associated unit region corresponds to only one sampling point, at least two signal strength feature data of the sampling point can be used as at least two signal strength feature data of the associated unit region. When an associated unit region corresponds to multiple sampling points, the average value of each signal strength feature data of the multiple sampling points can be used as each signal strength feature data of the associated unit region.

[0158] S1002, bind each associated unit area with at least two corresponding signal strength feature data to create a location fingerprint database of the digital key at the parking location.

[0159] Furthermore, each associated unit area can be bound to at least two corresponding signal strength characteristic data to create a location fingerprint database for the digital key at the parking location. This allows the relative position of the digital key and the vehicle to be determined based on at least two signal strength characteristic data of the digital key, and subsequently, the decision to execute preset actions corresponding to contactless vehicle control can be made based on the relative position of the digital key and the vehicle.

[0160] In this embodiment of the application, when the parking location to which the sampling area belongs is a location where no location fingerprint database is set up, a location fingerprint database of the digital key at the parking location can be established based on at least two signal strength feature data of each sampling point and the associated unit area. This realizes the establishment of a location fingerprint database of the digital key for the parking location. That is, in the process of establishing a location fingerprint database of the digital key for the parking location, the influence of the parking location on the received signal strength is taken into account. This ensures that when determining the relative position between the digital key and the vehicle at the parking location based on the location fingerprint database, there will be no error caused by environmental factors, thereby improving the accuracy of determining the distance between the digital key and the vehicle.

[0161] In some alternative implementations, if the parking location to which the sampling area belongs is a location where a location fingerprint database has already been set up, the location fingerprint database of the digital key can be updated based on at least two signal strength feature data of each sampling point and the associated unit area.

[0162] Based on this, for each associated unit area, at least two signal strength feature data points belonging to the associated unit area can be used to update at least two signal strength feature data points in the location fingerprint database corresponding to the parking location. This means replacing at least two signal strength feature data points in the location fingerprint database with those points, or adding at least two signal strength feature data points not stored in the database. For example, the environment of the parking location to which the sampling area belongs may change; for instance, a building may be added or demolished at the parking location. This could cause inconsistencies in the signal strength feature data received by the second signal receiver from the digital key at the same sampling point. Therefore, the location fingerprint database for the digital key can be updated based on at least two signal strength feature data points and the associated unit area.

[0163] In this embodiment of the application, by using at least two signal strength feature data of the sampling points belonging to the associated unit area, the location fingerprint database corresponding to the parking location is updated with at least two signal strength feature data of the associated unit area. This can update the location fingerprint database of the digital key at the parking location after the environment of the parking location corresponding to the sampling area changes, thus avoiding the problem of the location fingerprint database being unreliable due to environmental changes.

[0164] In some embodiments, there are many conditions that trigger the management of the location fingerprint database of the digital key, and this application embodiment does not limit these conditions.

[0165] For example, in one alternative implementation, if it is determined that the reference device associated with the vehicle and the digital key are carried by the same object, at least two signal strength feature data of the digital key at each sampling point in the sampling area can be automatically acquired to achieve automatic management of the digital key's location fingerprint database.

[0166] In another alternative implementation, at least two signal strength feature data of the digital key at each sampling point in the sampling area may be acquired only if it is determined that the reference device associated with the vehicle and the digital key are carried by the same object, and it is determined that there is a need to manage the location fingerprint database of the digital key, so as to manage the location fingerprint database of the digital key.

[0167] For example, if it is determined that the reference device and digital key associated with the vehicle are carried by the same object, and a fingerprint database management trigger event for the digital key is detected, signal strength characteristic data of the digital key at each sampling point in the sampling area can be obtained.

[0168] For example, detecting a fingerprint database management trigger event for the digital key could be a user triggering a command for fingerprint database management for the digital key on the digital key control interface, or determining that the vehicle meets preset conditions, such as arriving at a designated location.

[0169] In this embodiment, multiple triggering conditions are introduced to manage the location fingerprint database of digital keys. On the one hand, the location fingerprint database of digital keys can be managed in a timely manner, and on the other hand, the flexibility of managing the location fingerprint database of digital keys can be improved.

[0170] In some examples of this embodiment, the fingerprint database management trigger event detected for the digital key associated with the vehicle in the above embodiments can be any of the following:

[0171] Optional: receiving fingerprint database management instructions for digital keys.

[0172] For example, a user can trigger a fingerprint database management command for the digital key through the control interface of the digital key. The digital key can send the fingerprint database management command for the digital key to the vehicle controller. When the controller receives the fingerprint database management command for the digital key, it considers that a fingerprint database management trigger event for the digital key associated with the vehicle has been detected.

[0173] Optionally, the sampling area can be determined by detecting that the vehicle is currently parked at the target location and that the target location meets the fingerprint database management conditions. The sampling area is a region within a preset range of the vehicle. The fingerprint database management conditions can be that the target location is a location where a fingerprint database for digital keys is allowed to be established, or that the digital key has not previously established a fingerprint database at the target location, or that the fingerprint database for the digital key at that target location needs updating. In other words, if the vehicle is detected to be currently parked at the target location and the target location meets the fingerprint database management conditions, it is considered that a fingerprint database management trigger event for the digital key associated with the vehicle has been detected.

[0174] Optionally, it could also involve detecting that at least two signal strength characteristics of the digital key at the verification point do not match at least two signal strength characteristics of the same verification point stored in the location fingerprint database; where the verification point is any sampling point within the sampling area. For example, if the location fingerprint database corresponds to a company, the verification point could be the company entrance or exit, etc. Detecting that at least two signal strength characteristics of the digital key at the verification point do not match at least two signal strength characteristics of the same verification point stored in the location fingerprint database indicates that the location fingerprint database needs to be updated. This can be considered a trigger event for fingerprint database management of the digital key associated with the vehicle.

[0175] In this application embodiment, various application scenarios are provided to determine and detect fingerprint database management trigger events for digital keys associated with vehicles. Under the condition of satisfying the above application scenarios, the location fingerprint database of digital keys can be managed.

[0176] It is understood that the target location mentioned in the above embodiments meets the fingerprint database management conditions, and can be any of the following:

[0177] Optionally, the target location can meet the fingerprint database management conditions by being a location with a location fingerprint database. This can be a location where a location fingerprint database is permitted but not yet established, or a location where a fingerprint database has already been established.

[0178] For example, see Figure 11 , Figure 11 This document provides a diagram illustrating how to set target locations for establishing a location fingerprint database. Users can click the "+" button (New Address) on the digital key display interface to add frequently used addresses. These addresses can be manually entered by the user or automatically located by GPS. These frequently used addresses can then be used as target locations. Examples of frequently used addresses include, but are not limited to, schools and companies.

[0179] Optionally, the target location can also meet the fingerprint database management criteria if the number of times a vehicle parks at the target location within a set time period exceeds a certain threshold. The set time period and threshold can be configured according to actual needs; for example, the set time period could be set to one day, and the threshold to two times. If the number of times a vehicle parks at the target location within the set time period exceeds the threshold, it means the vehicle frequently appears at that location. Therefore, the target location can be considered to meet the fingerprint database management criteria, facilitating the establishment of a location fingerprint database for that location and enabling seamless vehicle control.

[0180] Optionally, the target location can also meet the fingerprint database management conditions if the subject, carrying both the reference device and the digital key, stays in the sampling area for a duration exceeding a set time. The set time can be configured according to actual needs, for example, it can be set to 5 hours. When the subject, carrying both the reference device and the digital key, stays in the sampling area for a duration exceeding the set time, it can be considered that the vehicle frequently appears at the target location. Therefore, the target location can be considered to meet the fingerprint database management conditions, facilitating the establishment of a location fingerprint database for that target location, and ultimately enabling contactless vehicle control.

[0181] In this application embodiment, multiple methods are provided to determine that the target location meets the fingerprint database management conditions, which facilitates the management of the location fingerprint database of the digital key when the target location meets the fingerprint database management conditions.

[0182] In some alternative implementations, different meteorological environmental data can have different effects on the signal strength characteristics of the digital key received by the signal receiver at the same sampling point.

[0183] Based on this, see Figure 12A , Figure 12A This document provides a schematic diagram of signal strength characteristic data under different meteorological environmental data. It assumes that the digital key is located at the same sampling point, i.e., the distance between the digital key and the vehicle is always 'd'. However, due to the varying degrees of influence of different meteorological environmental data on signal strength, a significant error exists between the signal strength characteristic data Rssi1 obtained under meteorological environmental data 1 and the signal strength characteristic data Rssi2 obtained under meteorological environmental data 2 for the same sampling point. Here, signal strength characteristic data Rssi1 and Rssi2 are feature data collected from the wireless signal transmitted by the digital key at the same power. This inconsistency in signal strength characteristic data at the same power obtained under different meteorological environmental data leads to discrepancies between the meteorological environmental data used to establish the location fingerprint database and the meteorological environmental data used in actual use of the location fingerprint database, resulting in inaccurate determination of the digital key's location information.

[0184] Therefore, when creating or updating a location fingerprint database, and when using a location fingerprint database, the impact of meteorological environmental data on the accuracy of the location fingerprint database can be considered to avoid inaccurate location information determination due to inconsistencies in meteorological environmental data when creating or managing the location fingerprint database and when using the location fingerprint database.

[0185] For example, see Figure 12B , Figure 12B A flowchart for managing and using a location fingerprint database is provided, which includes the following steps:

[0186] S1201, when the current meteorological environment data of the digital key does not match the reference meteorological environment data for constructing the location fingerprint database of the parking location of the digital key in the sampling area, based on the influence model of meteorological environment on signal strength, at least two signal strength feature data of each sampling point under the current meteorological environment data are converted to at least two signal strength feature data of each sampling point under the reference meteorological environment data.

[0187] For example, the reference meteorological environmental data can be pre-specified meteorological environmental data. This meteorological environmental data includes, but is not limited to, temperature, humidity, pressure, wind speed, and precipitation.

[0188] The impact of meteorological conditions on signal strength can vary. For example, when creating a location fingerprint database, the reference meteorological data might be sunny, with a temperature of 40°C and humidity of 80%. However, on a certain day during the application of the location fingerprint database, the current meteorological data might be heavy rain, with a temperature of 8°C and humidity of 99%. In this case, the difference in meteorological data could interfere with the signal strength characteristic data emitted by the digital key (such as Bluetooth signal strength), leading to a significant deviation between the location information determined based on the signal strength characteristic data and the actual location information.

[0189] Based on this, a model of the impact of meteorological environment on signal strength can be pre-constructed. For example, at least two signal strength feature data corresponding to the digital key at the same sampling point can be collected under a large amount of different meteorological environment data. Using reference meteorological environment data as a standard, the differences between at least two signal strength feature data corresponding to the digital key at the same sampling point under different meteorological environment data can be determined. Then, the environmental differences between different meteorological environment data and reference meteorological environment data, as well as the signal differences between at least two signal strength feature data under reference meteorological environment data and at least two signal strength feature data under different meteorological environment data, can be determined. Thus, the correspondence between environmental differences and signal differences can be established, and a model of the impact of meteorological environment on signal strength can be created based on the correspondence.

[0190] Optionally, at least two signal strength feature data corresponding to the digital key at the same sampling point under a large amount of collected data from different meteorological environments can be input into a neural network model. This allows the neural network model to learn the characteristics between environmental differences and signal differences, thereby obtaining a model of the impact of meteorological environment on signal strength. Alternatively, a mapping relationship can be constructed between at least two signal strength feature data under different meteorological environments and reference meteorological environment data. For example, a function RSSI can be constructed. c =f(W i RSSI d ), where RSSI d Given at least two signal strength characteristics under the current meteorological environment data, RSSI c W represents at least two signal strength feature data under reference meteorological environment data, mapped from at least two signal strength feature data under the current meteorological environment data. i This refers to the difference between the current meteorological environment data and the reference meteorological environment data.

[0191] For example, if the current meteorological environment data of the digital key does not match the reference meteorological environment data used to construct the location fingerprint database of the parking location in the sampling area, at least two signal strength feature data points at each sampling point under the current meteorological environment data can be converted to at least two signal strength feature data points under the reference meteorological environment data, based on a model of the impact of meteorological environment on signal strength. In this way, by converting at least two signal strength feature data points, the current meteorological environment data of the digital key and the reference meteorological environment data are unified, avoiding interference with the signal strength feature data caused by differences in meteorological environment data, thereby improving the reliability of the collected signal strength feature data.

[0192] S1202, manage the location fingerprint database of the digital key based on the location information of each sampling point and at least two signal strength characteristic data under reference meteorological environment data.

[0193] For example, the location fingerprint database of a digital key can be created or updated based on the location information of each sampling point and at least two signal strength feature data under reference meteorological environmental data. For instance, in a location fingerprint database update scenario, for each sampling point, based on the location coordinates of the sampling point, a unit region matching the location coordinates is determined from each unit region as the associated unit region of the sampling point; for each associated unit region, at least two signal strength feature data of the sampling point belonging to the associated unit region under reference meteorological environmental data are used to update the at least two signal strength feature data of the associated unit region in the location fingerprint database of the digital key.

[0194] In the scenario of creating a location fingerprint database, for each sampling point, based on the location coordinates of the sampling point, a unit region matching the location coordinates is determined from each unit region as the associated unit region of the sampling point; based on at least two signal strength feature data of each sampling point and the associated unit region, at least two signal strength feature data of each associated unit region are determined; each associated unit region is bound to the corresponding at least two signal strength feature data to create a location fingerprint database of the digital key at the parking location.

[0195] It is understood that the process of managing the location fingerprint database of the digital key described in the above embodiments is the same as the process of managing the location fingerprint database of the digital key here, and will not be described in detail here.

[0196] S1203, upon detecting a positioning command for the digital key, acquire at least two signal strength characteristic data of the digital key at its current location under real-time meteorological environmental data.

[0197] For example, the location command for a digital key can be a command to instruct the digital key to be located. For instance, it can be automatically triggered when the digital key enters a controllable area of ​​the vehicle; it can also be triggered when the user carries the digital key and performs a preset action (such as waving the digital key); or it can be triggered when the user clicks the location command button in the digital key's operation interface.

[0198] Optionally, upon detecting a positioning command for the digital key, the second signal receiver on the vehicle can acquire at least two signal strength characteristic data of the digital key at its current location under real-time weather environmental data.

[0199] S1204, convert at least two signal strength feature data of the current location point under real-time meteorological environment data to at least two signal strength feature data of the current location point under reference meteorological environment data.

[0200] Optionally, after managing the location fingerprint database of the digital key based on at least two signal strength feature data and location information of each sampling point, when using the location fingerprint database, the real-time meteorological environment data when collecting at least two signal strength feature data of the current location of the digital key may be inconsistent with the reference meteorological environment data. In this case, the at least two signal strength feature data of the current location under the real-time meteorological environment data can be converted to the at least two signal strength feature data of the current location under the reference meteorological environment data based on the meteorological environment's influence on signal strength, so as to avoid the influence of meteorological environment data on signal strength feature data.

[0201] S1205, determine the current location information of the digital key based on the location fingerprint database of the parking location and at least two signal strength characteristic data of the current location under reference meteorological environmental data.

[0202] Optionally, the location information can be used as the current location information of the digital key by comparing the data in the location fingerprint database with the data in the database and using specific algorithms (such as nearest neighbor search, machine learning algorithms, etc.) to find the location information that is most correlated with at least two signal strength feature data of the current location under the reference meteorological environment data.

[0203] In this embodiment, a model for the influence of meteorological environment on signal strength is introduced. This model can unify at least two signal strength feature data under different meteorological environment data to reference meteorological environment data, thus avoiding the influence of meteorological environment data on signal strength feature data. This not only improves the accuracy of the location fingerprint database, but also improves the accuracy of the location information of the digital key determined based on the location fingerprint database, thereby improving the accuracy of vehicle control.

[0204] In some optional implementations, when updating or using the location fingerprint database, if the current meteorological environment data is consistent with the reference meteorological environment data, the location information of the sampling point and at least two signal strength feature data under the current meteorological environment data can be directly used to manage the location fingerprint database of the digital key. This avoids the influence of meteorological environment data when managing the location fingerprint database. Furthermore, during use, at least two signal strength feature data under the real-time meteorological environment data can be converted to the reference meteorological environment data to improve the accuracy of determining the location information of the digital key.

[0205] Based on this, see Figure 13 , Figure 13 An alternative flowchart for managing and using location fingerprint databases is provided, which includes the following steps:

[0206] S1301, when the current meteorological environment data of the digital key matches the reference meteorological environment data for constructing the location fingerprint database of the digital key at the parking location in the sampling area, the location fingerprint database of the digital key is managed based on the location information of each sampling point and at least two signal strength characteristic data under the current meteorological environment data.

[0207] For example, if the current meteorological environment data of the digital key matches the reference meteorological environment data for constructing the location fingerprint database of the parking location of the digital key in the sampling area, the location fingerprint database of the digital key can be managed directly based on the location information of each sampling point and at least two signal strength feature data under the current meteorological environment data.

[0208] For example, in the scenario of updating the location fingerprint database, for each sampling point, based on the location coordinates of the sampling point, a unit region matching the location coordinates is determined from each unit region as the associated unit region of the sampling point; for each associated unit region, at least two signal strength feature data of the sampling point belonging to the associated unit region under the reference meteorological environment data are used to update at least two signal strength feature data of the associated unit region in the location fingerprint database of the digital key.

[0209] In the scenario of creating a location fingerprint database, for each sampling point, based on the location coordinates of the sampling point, a unit region matching the location coordinates is determined from each unit region as the associated unit region of the sampling point; based on at least two signal strength feature data of each sampling point and the associated unit region, at least two signal strength feature data of each associated unit region are determined; each associated unit region is bound to the corresponding at least two signal strength feature data to create a location fingerprint database of the digital key at the parking location.

[0210] It is understood that the process of managing the location fingerprint database of the digital key described in the above embodiments is the same as the process of managing the location fingerprint database of the digital key here, and will not be described in detail here.

[0211] S1302, upon detecting a positioning command for the digital key, acquire at least two signal strength characteristic data of the digital key at its current location under real-time meteorological environmental data.

[0212] For example, the location command for a digital key can be a command to instruct the digital key to be located. For instance, it can be automatically triggered when the digital key enters a controllable area of ​​the vehicle; it can also be triggered when the user carries the digital key and performs a preset action (such as waving the digital key); or it can be triggered when the user clicks the location command button in the digital key's operation interface.

[0213] Optionally, upon detecting a positioning command for the digital key, the second signal receiver on the vehicle can acquire at least two signal strength characteristic data of the digital key at its current location under real-time weather environmental data.

[0214] S1303, convert at least two signal strength feature data of the current location point under real-time meteorological environment data to at least two signal strength feature data of the current location point under reference meteorological environment data.

[0215] Optionally, after managing the location fingerprint database of the digital key based on at least two signal strength feature data and location information of each sampling point, when using the location fingerprint database, the real-time meteorological environment data when collecting at least two signal strength feature data of the current location of the digital key may be inconsistent with the reference meteorological environment data. In this case, the at least two signal strength feature data of the current location under the real-time meteorological environment data can be converted to the at least two signal strength feature data of the current location under the reference meteorological environment data based on the meteorological environment's influence on signal strength, so as to avoid the influence of meteorological environment data on signal strength feature data.

[0216] S1304, determine the current location information of the digital key based on the location fingerprint database of the parking location and at least two signal strength characteristic data of the current location under reference meteorological environmental data.

[0217] Optionally, the location information can be used as the current location information of the digital key by comparing the data in the location fingerprint database with the data in the database and using specific algorithms (such as nearest neighbor search, machine learning algorithms, etc.) to find the location information that is most correlated with at least two signal strength feature data of the current location under the reference meteorological environment data.

[0218] In this embodiment, even if the meteorological environment data when managing the location fingerprint database is consistent with the reference meteorological environment data, when using the location fingerprint database, it is still necessary to convert at least two signal strength feature data of the current location point under the real-time meteorological environment data to at least two signal strength feature data of the current location point under the reference meteorological environment data. This avoids the influence of meteorological environment data on signal strength feature data, which can not only improve the accuracy of the location fingerprint database, but also improve the accuracy of the location information of the digital key determined based on the location fingerprint database, thereby improving the accuracy of vehicle control.

[0219] In some alternative implementations, meteorological environmental data may include at least two types of environmental factor data, such as temperature, humidity, pressure, wind speed, and precipitation.

[0220] For example, factor errors can be set for various environmental factors based on empirical data. These factor errors are used to determine whether the current meteorological environment data of the digital key matches a reference meteorological environment. For instance, if the meteorological environment data is temperature and humidity, the factor error for temperature is 5°C, and the factor error for humidity is 10%.

[0221] Understandably, humidity has a significant impact on Bluetooth signal strength; in high-humidity environments, Bluetooth signal strength will decrease noticeably. This is because increased humidity causes moisture in the air to absorb and scatter Bluetooth signals, thus reducing transmission distance and stability. From a signal transmission perspective, raindrops on rainy days may increase the signal transmission path, weakening the signal received by the receiver. From a device hardware perspective, increased humidity reduces the efficiency of hardware devices, thereby decreasing the strength of the received signal. The relationship between temperature and Bluetooth signal strength exhibits a peak-and-trough pattern: in low-temperature environments, Bluetooth device current and voltage become unstable, affecting normal operation and reducing transmission speed; in high-temperature environments, Bluetooth devices are prone to increased power consumption and decreased transmission speed.

[0222] If humidity has a greater impact on signal strength than temperature, then humidity can be considered a key environmental factor.

[0223] When determining whether current meteorological environmental data matches reference meteorological environmental data, one can compare only the key environmental factor data in the current meteorological environmental data and whether the difference between the key environmental factor data in the current meteorological environmental data and the key environmental factor data in the reference meteorological environmental data is greater than the factor error corresponding to the key environmental factor. For example, compare whether the absolute value of the difference between the humidity in the current meteorological environmental data and the humidity in the reference meteorological environmental data is greater than 10%. If so, it is determined that the current meteorological environmental data does not match the reference meteorological environmental data; if not, it is determined that the current meteorological environmental data matches the reference meteorological environmental data.

[0224] For example, if the difference between the key environmental factor data in the current meteorological environmental data and the key environmental factor data in the reference meteorological environmental data is greater than the factor error corresponding to the key environmental factor, then it is determined that the current meteorological environmental data of the digital key does not match the reference meteorological environmental data used to construct the location fingerprint database of the digital key at the parking location. Furthermore, the impact of key environmental factors on signal strength is greater than that of other environmental factors.

[0225] In this embodiment, the difference between the key environmental factors in the current meteorological environmental data and the key environmental factors in the reference meteorological environment is compared with the magnitude of the factor error corresponding to the key environmental factors to determine whether the current meteorological environmental data matches the reference meteorological environmental data. This simplifies the steps of determining whether the current meteorological environmental data matches the reference meteorological environmental data and improves the efficiency of determining whether the current meteorological environmental data matches the reference meteorological environmental data.

[0226] In some alternative implementations, the reference device and digital key associated with the vehicle mentioned in the above embodiments are carried by the same object and can be determined by the wireless signal strength between the reference device and the digital key.

[0227] For example, see Figure 14 , Figure 14 A flowchart is provided to determine that a reference device associated with a vehicle and a digital key are carried by the same object, specifically including the following steps:

[0228] S1401, acquire the field strength signal strength between the reference device and the digital key.

[0229] For example, when both the digital key and the reference device are activated and in a communicable state, they emit wireless signals for mutual identification and communication. These signals propagate through space, forming a specific field strength distribution. This field strength can be used to determine whether the digital key and the reference device are in the same physical location, i.e., whether they are carried by the same person. Thus, the field strength signal strength between the reference device and the digital key can be obtained, and based on this signal strength, it can be determined whether the reference device and the digital key are carried by the same object.

[0230] S1402, if the field strength signal strength is greater than the preset strength threshold, then it is determined that the reference device and digital key associated with the vehicle are carried by the same object.

[0231] Furthermore, a preset strength threshold can be set in advance. If the field strength signal between the digital key and the reference device exceeds this preset strength threshold, it is considered that the digital key and the reference device are being carried simultaneously.

[0232] In this embodiment, by monitoring the field strength signal between the reference device and the digital key, it is determined whether the reference device and the digital key are carried by the same object, thereby facilitating the collection of sampling point location information when it is determined that the fingerprint database of the digital key needs to be managed.

[0233] In some alternative implementations, see [link to relevant documentation]. Figure 15 , Figure 15 A flowchart illustrating another method for managing location fingerprint databases is provided, which includes the following steps:

[0234] S1501, acquire the field strength signal strength between the reference device and the digital key.

[0235] S1502, if the field strength signal strength is greater than the preset strength threshold, then it is determined that the reference device and digital key associated with the vehicle are carried by the same object.

[0236] S1503, determine that the reference device and digital key associated with the vehicle are carried by the same object, acquire at least two signal strength characteristic data of the digital key at each sampling point in the sampling area; and determine the location information of each sampling point based on the signal interaction information between the reference device and the first signal receiver on the vehicle at each sampling point.

[0237] S1504 manages the location fingerprint database of the digital key based on at least two signal strength characteristic data and location information of each sampling point.

[0238] Specifically, S1504 can be implemented in the following ways:

[0239] Step 1: For each sampling point, based on the location coordinates of the sampling point, determine the unit region that matches the location coordinates from each unit region, and use it as the associated unit region of the sampling point.

[0240] Step 2: Based on at least two signal strength feature data of each sampling point and the associated unit region, determine at least two signal strength feature data of each associated unit region.

[0241] Step 3: Determine whether the current meteorological environment data of the digital key matches the reference meteorological environment data of the location fingerprint database of the parking location of the digital key in the sampling area. If they do not match, proceed to step 4; if they match, proceed to step 6.

[0242] Step 4: Based on the model of the impact of meteorological environment on signal strength, at least two signal strength feature data of each sampling point under the current meteorological environment data are converted to at least two signal strength feature data of each sampling point under the reference meteorological environment data.

[0243] Step 5: Bind each associated unit area with at least two corresponding converted signal strength feature data to create a location fingerprint database for the digital key at the parking location.

[0244] Step 6: Bind each associated unit area with at least two corresponding signal strength feature data to create a location fingerprint database for the digital key at the parking location.

[0245] Step 7: If a positioning command for the digital key is detected, acquire at least two signal strength characteristic data of the digital key at its current location under real-time meteorological environmental data.

[0246] Step 8: Convert at least two signal strength feature data of the current location point under real-time meteorological environmental data to at least two signal strength feature data of the current location point under reference meteorological environmental data.

[0247] Step 9: Determine the current location information of the digital key based on the location fingerprint database of the parking location and at least two signal strength characteristic data of the current location under reference meteorological environmental data.

[0248] The specific processes of S1501 to S1504 described above can be found in the description of the above method embodiments. Their implementation principles and technical effects are similar, and will not be repeated here.

[0249] Furthermore, the execution order of the above steps is merely illustrative and is not intended to limit the execution steps. The execution order of other steps is within the protection scope of the embodiments of this application.

[0250] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0251] Based on the same inventive concept, this application also provides a location fingerprint database management device for implementing the location fingerprint database management method described above. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in one or more location fingerprint database management device embodiments provided below can be found in the limitations of the location fingerprint database management method described above, and will not be repeated here.

[0252] In one embodiment, such as Figure 16 As shown, a location fingerprint database management device is provided, comprising:

[0253] The determining module 10 is configured to, when determining that the reference device associated with the vehicle and the digital key are carried by the same object, acquire at least two signal strength characteristic data of the digital key at each sampling point within the sampling area; and, based on the signal interaction information between the reference device at each sampling point and the first signal receiver on the vehicle, determine the location information of each sampling point; wherein the at least two signal strength characteristic data of each sampling point include the signal strength of at least two wireless signals of different power emitted by the digital key at the sampling point and received by the second signal receiver on the vehicle.

[0254] The management module 20 is used to manage the location fingerprint database of the digital key based on at least two signal strength feature data and location information of each sampling point.

[0255] The aforementioned location fingerprint database management device acquires at least two signal strength feature data of the digital key at each sampling point within the sampling area when it is determined that the reference device associated with the vehicle and the digital key are carried by the same object; and determines the location information of each sampling point based on the signal interaction information between the reference device and the first signal receiver on the vehicle at each sampling point; and then manages the location fingerprint database of the digital key based on the at least two signal strength feature data and the location information of each sampling point. The above scheme, on the one hand, leverages the mobile association and binding characteristics of the reference device and the digital key. It utilizes the signal interaction between the vehicle and the reference device to determine the distance between the digital key and the vehicle, replacing the distance estimation based on the signal strength of the interaction between the digital key and the vehicle. This bypasses the low positioning accuracy of the digital key. By associating the signal strength feature data determined by the interaction between the vehicle and the digital key with the positioning determined by the interaction between the vehicle and the reference device, during the location fingerprint database application phase, the digital key vehicle control function is based on the signal strength feature data between the digital key and the vehicle, unaffected by the accuracy of the signal strength-to-distance conversion. In other words, the accuracy of vehicle control based on the digital key no longer depends on the positioning accuracy of the digital key itself, thus improving the precision of vehicle control. On the other hand, by introducing the function of the digital key to emit signals of different power, multiple signal strength feature data can be acquired for each sampling point, increasing the signal acquisition dimension and enriching the feature data in the location fingerprint database, thereby improving the precision of vehicle control.

[0256] In one embodiment, at least two wireless signals of different power are transmitted by the same signal transmitter in the digital key.

[0257] In one embodiment, the sampling area includes multiple unit areas of the same size, and the location information of each sampling point includes the position coordinates of the sampling point relative to the vehicle; the management module 20 specifically includes:

[0258] The determination unit is used to determine, for each sampling point, a unit region matching the location coordinates from each unit region, as the associated unit region of the sampling point;

[0259] The management unit is used to manage the location fingerprint database of the digital key based on at least two signal strength feature data of each sampling point and the associated unit area.

[0260] In one embodiment, when the parking location to which the sampling area belongs is a location without a location fingerprint database, the management unit is specifically used to:

[0261] Based on at least two signal strength feature data and associated unit areas at each sampling point, at least two signal strength feature data for each associated unit area are determined; each associated unit area is bound to the corresponding at least two signal strength feature data to create a location fingerprint database of the digital key at the parking location.

[0262] In one embodiment, the reference device is a physical key to a vehicle.

[0263] In one embodiment, the physical key supports ultra-wideband (UWB) wireless communication.

[0264] In one embodiment, the management module 20 is specifically used for:

[0265] When the current meteorological environment data of the digital key does not match the reference meteorological environment data used to construct the location fingerprint database of the parking location in the sampling area, the location fingerprint database of the digital key is constructed based on the influence model of meteorological environment on signal strength. At least two signal strength feature data points of each sampling point under the current meteorological environment data are converted to at least two signal strength feature data points of each sampling point under the reference meteorological environment data. The location fingerprint database of the digital key is managed based on the location information of each sampling point and the at least two signal strength feature data points of the reference meteorological environment data. After managing the location fingerprint database of the digital key based on the at least two signal strength feature data points of each sampling point and the location information, when a positioning command for the digital key is detected, at least two signal strength feature data points of the digital key at its current location under the real-time meteorological environment data are obtained. These at least two signal strength feature data points of the current location under the real-time meteorological environment data are converted to at least two signal strength feature data points of the current location under the reference meteorological environment data. The current location information of the digital key is determined based on the location fingerprint database of the parking location and the at least two signal strength feature data points of the current location under the reference meteorological environment data.

[0266] In one embodiment, the management module 20 is specifically used for:

[0267] When the current meteorological environment data of the digital key matches the reference meteorological environment data used to construct the location fingerprint database of the parking location of the digital key in the sampling area, the location fingerprint database of the digital key is managed based on the location information of each sampling point and at least two signal strength feature data under the current meteorological environment data. After managing the location fingerprint database of the digital key based on the at least two signal strength feature data and location information of each sampling point, when a positioning command for the digital key is detected, at least two signal strength feature data of the digital key at its current location under the real-time meteorological environment data are obtained. The at least two signal strength feature data of the current location under the real-time meteorological environment data are converted to at least two signal strength feature data of the current location under the reference meteorological environment data. Based on the location fingerprint database of the parking location and the at least two signal strength feature data of the current location under the reference meteorological environment data, the current location information of the digital key is determined.

[0268] In one embodiment, the meteorological environmental data includes at least two types of environmental factor data, and the determination module 10 is further configured to:

[0269] If the difference between the key environmental factor data in the current meteorological environmental data and the key environmental factor data in the reference meteorological environmental data is greater than the factor error corresponding to the key environmental factor, then it is determined that the current meteorological environmental data of the digital key does not match the reference meteorological environmental data when constructing the location fingerprint database of the digital key at the parking location; among them, the influence of key environmental factors on signal strength is greater than the influence of other environmental factors on signal strength.

[0270] In one embodiment, the determining module 10 is specifically used for:

[0271] Obtain the field strength signal between the reference device and the digital key; if the field strength signal is greater than a preset strength threshold, it is determined that the reference device and digital key associated with the vehicle are carried by the same object.

[0272] The various modules in the aforementioned fingerprint database management device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0273] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the location fingerprint database management method described in any of the above embodiments.

[0274] In one exemplary embodiment, see Figure 17 , Figure 17 An internal structure diagram of a computer device is provided. This computer device can be a server or a controller in a vehicle. The computer device includes a memory 1701 and a processor 1702, which are connected via a system bus 1703. The memory 1701 stores a computer program, and when the processor 1702 executes the computer program, it implements the location fingerprint database management method described in any of the above embodiments.

[0275] Optional, see Figure 18 , Figure 18 Another diagram of the internal structure of a computer device is provided. Figure 17 Based on this, the computer device may further include an input / output (I / O) interface 1704, a communication interface 1705, and a non-volatile storage medium 1706. The processor 1702, memory 1701, and I / O interface 1704 are connected via a system bus 1703, and the communication interface 1705 is connected to the system bus 1703 via the I / O interface 1704. The processor of this computer device provides computing and control capabilities. The memory of this computer device includes a non-volatile storage medium 1706 and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of this computer device stores input data. The I / O interface 1704 of this computer device is used for exchanging information between the processor 1702 and external devices. The communication interface 1705 of this computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the location fingerprint database management method described in any of the above embodiments.

[0276] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the location fingerprint database management method described in any of the above embodiments.

[0277] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the location fingerprint database management method described in any of the above embodiments.

[0278] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0279] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0280] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0281] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for managing a location fingerprint database, characterized in that, The method includes: If it is determined that the reference device associated with the vehicle and the digital key are carried by the same object, at least two signal strength characteristic data of the digital key are acquired at each sampling point within the sampling area; and, Based on the signal interaction information between the reference device at each sampling point and the first signal receiver on the vehicle, the location information of each sampling point is determined; wherein, the at least two signal strength feature data of each sampling point include the signal strength of at least two wireless signals of different power emitted by the digital key at the sampling point and received by the second signal receiver on the vehicle. The location fingerprint database of the digital key is managed based on the at least two signal strength feature data of each sampling point and the location information; The sampling area includes multiple unit areas of the same size, and the location information of each sampling point includes the position coordinates of the sampling point relative to the vehicle. Based on the at least two signal strength feature data of each sampling point and the location information, the location fingerprint database of the digital key is managed, including: For each sampling point, based on the location coordinates of the sampling point, a unit region matching the location coordinates is determined from each unit region and used as the associated unit region of the sampling point; The location fingerprint database of the digital key is managed based on the at least two signal strength feature data of each sampling point and the associated unit region.

2. The method according to claim 1, characterized in that, The at least two wireless signals of different power are transmitted by the same signal transmitter in the digital key.

3. The method according to claim 1, characterized in that, When the parking location to which the sampling area belongs is a location without a location fingerprint database, the location fingerprint database of the digital key is managed based on the at least two signal strength feature data of each sampling point and the associated unit area, including: Based on the at least two signal strength feature data of each sampling point and the associated unit region, at least two signal strength feature data of each associated unit region are determined; Each of the associated unit regions is bound to the corresponding at least two signal strength feature data to create a location fingerprint database of the digital key at the parking location.

4. The method according to claim 1, characterized in that, The reference device is the physical key of the vehicle.

5. The method according to claim 4, characterized in that, The physical key supports ultra-wideband (UWB) wireless communication.

6. The method according to any one of claims 1-5, characterized in that, Based on the at least two signal strength feature data of each sampling point and the location information, the location fingerprint database of the digital key is managed, including: If the current meteorological environment data of the digital key does not match the reference meteorological environment data for constructing the location fingerprint database of the parking location of the digital key in the sampling area, the at least two signal strength feature data of each sampling point under the current meteorological environment data are converted to the at least two signal strength feature data of each sampling point under the reference meteorological environment data based on the meteorological environment influence model. The location fingerprint database of the digital key is managed based on the location information of each sampling point and the at least two signal strength feature data under the reference meteorological environment data; After managing the location fingerprint database of the digital key based on the at least two signal strength feature data of each sampling point and the location information, the method further includes: Upon detecting a positioning command for the digital key, acquire at least two signal strength characteristic data of the digital key at its current location under real-time meteorological environmental data; Convert the at least two signal strength feature data of the current location point under the real-time meteorological environment data to the at least two signal strength feature data of the current location point under the reference meteorological environment data; The current location information of the digital key is determined based on the location fingerprint database of the parking location and the at least two signal strength feature data of the current location under the reference meteorological environment data.

7. The method according to any one of claims 1-5, characterized in that, Based on the at least two signal strength feature data of each sampling point and the location information, the location fingerprint database of the digital key is managed, including: When the current meteorological environment data of the digital key matches the reference meteorological environment data for constructing the location fingerprint database of the digital key at the parking location in the sampling area, the location fingerprint database of the digital key is managed according to the location information of each sampling point and the at least two signal strength feature data under the current meteorological environment data. After managing the location fingerprint database of the digital key based on the at least two signal strength feature data of each sampling point and the location information, the method further includes: Upon detecting a positioning command for the digital key, acquire at least two signal strength characteristic data of the digital key at its current location under real-time meteorological environmental data; Convert the at least two signal strength feature data of the current location point under the real-time meteorological environment data to the at least two signal strength feature data of the current location point under the reference meteorological environment data; The current location information of the digital key is determined based on the location fingerprint database of the parking location and the at least two signal strength feature data of the current location under the reference meteorological environment data.

8. The method according to claim 6, characterized in that, Meteorological and environmental data include data on at least two environmental factors, and the method further includes: If the difference between the key environmental factor data in the current meteorological environment data and the key environmental factor data in the reference meteorological environment data is greater than the factor error corresponding to the key environmental factor, then it is determined that the current meteorological environment data of the digital key does not match the reference meteorological environment data when constructing the location fingerprint database of the digital key at the parking location. Among them, the key environmental factors have a greater impact on signal strength than other environmental factors.

9. The method according to any one of claims 1-5, characterized in that, The reference device and digital key associated with the vehicle are determined to be carried by the same object, including: Obtain the field strength signal strength between the reference device and the digital key; If the field strength signal strength is greater than a preset strength threshold, it is determined that the reference device and digital key associated with the vehicle are carried by the same object.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 9.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 9.

12. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 9.

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