Target positioning method, device, system, computer device and storage medium

Abstract

The application relates to a target positioning method, device, system, computer equipment and a storage medium. The target positioning method comprises the following steps: acquiring first position detection information of a target to be positioned in a target space collected by a first device, determining a first detection result of the target to be positioned based on the first position detection information; acquiring a calibration area of the target space; the calibration area is determined based on second position detection information collected by a second device in the target space; and the first detection result of the target to be positioned is subjected to calibration processing based on the calibration area, so as to obtain a target position of the target to be positioned in the target space. The method can improve positioning accuracy.

Description

Technical Field

[0001] This application relates to the field of positioning technology, and in particular to a target positioning method, apparatus, system, computer equipment, and storage medium. Background Technology

[0002] With the development of IoT and smart home technologies, the demand for indoor positioning is increasing. Indoor positioning refers to location tracking within an indoor environment. It primarily utilizes a combination of technologies, including wireless communication, base station positioning, inertial navigation, and motion capture, to form an integrated indoor positioning system. This system enables the monitoring of the location of people and objects within an indoor space. For example, it can be used for navigation in robotic vacuum cleaners and for finding lost items for forgetful elderly individuals. To address these needs, technologies such as Bluetooth positioning, RFID (Radio Frequency Identification) positioning, UWB (Ultra-Wide Band) positioning, and millimeter-wave radar positioning have emerged.

[0003] However, as the requirements for positioning accuracy become increasingly stringent in different scenarios, current positioning technology can no longer meet the actual requirements to a certain extent, so it is necessary to improve positioning accuracy. Summary of the Invention

[0004] Therefore, it is necessary to provide a target positioning method, device, system, computer equipment, and storage medium that can improve positioning accuracy in response to the above-mentioned technical problems.

[0005] A target localization method, the target localization method comprising:

[0006] Acquire the first position detection information of the target to be located in the target space collected by the first device, and determine the first detection result of the target to be located based on the first position detection information;

[0007] The calibration area of ​​the target space is obtained; the calibration area is determined based on the second position detection information collected by the second device in the target space.

[0008] The first detection result of the target to be located is calibrated based on the calibration area to obtain the target position of the target in the target space.

[0009] A target positioning device, the target positioning device comprising:

[0010] The first acquisition module is used to acquire the first position detection information of the target to be located in the target space collected by the first device, and to determine the first detection result of the target to be located based on the first position detection information.

[0011] The second acquisition module is used to acquire the calibration area of ​​the target space; the calibration area is determined based on the second position detection information collected by the second device in the target space;

[0012] The calibration module is used to perform calibration processing on the first detection result of the target to be located based on the calibration area, so as to obtain the target position of the target to be located in the target space.

[0013] In one embodiment, the calibration area includes a verification area; when the second acquisition module acquires the calibration area of ​​the target space, it is specifically used for:

[0014] If the target to be located carries a positioning tag, then the second location detection information collected by the second device in the target space is obtained, and the second detection result of the target to be located is determined based on the second location detection information; the second device collects the second location detection information by detecting the positioning tag;

[0015] Based on the second detection result, the current verification area in the target space is determined;

[0016] When the calibration module performs calibration processing on the first detection result of the target to be located based on the calibration area to obtain the target position of the target to be located in the target space, it is specifically used to: perform calibration processing on the first detection result of the target to be located based on the verification area to obtain the target position of the target to be located in the target space.

[0017] In one embodiment, when the second acquisition module determines the current verification area in the target space based on the second detection result, it is specifically used for:

[0018] Based on the second detection result and the target calibration coefficient, the current verification area in the target space is obtained; the target calibration coefficient is negatively correlated with the positioning accuracy of the first device and the second device.

[0019] In one embodiment, when the calibration module performs calibration processing on the first detection result of the target to be located based on the verification area to obtain the target position of the target to be located in the target space, it is specifically used for:

[0020] If the first device detects at least one non-stationary target to be located, it determines the area where the target to be located is located based on the first detection result of the non-stationary target to be located.

[0021] If a non-stationary target to be located is located within the verification area, the first detection result and the second detection result of the target to be located within the verification area are fused to obtain the target position of the target in the target space.

[0022] In one embodiment, the calibration area includes an interference area; the interference area is determined based on historical second location detection information collected by the second device in the target space;

[0023] When the calibration module calibrates the first detection result of the target to be located based on the calibration area to obtain the target position of the target to be located in the target space, it is specifically used for:

[0024] If the target to be located does not carry a positioning tag, then the target to be located located within the interference area among at least one non-stationary target to be located detected by the first device will be eliminated.

[0025] The first detection result corresponding to the removed target is determined as the target position of the target in the target space.

[0026] In one embodiment, the target positioning device further includes a navigation module, the navigation module being used for:

[0027] In response to a navigation operation targeting a target object in the target space, the target object's position is obtained;

[0028] Based on the obstacle positions detected by the first device in the target space, path planning is performed on the target to be located and the target object to obtain a navigation path for the target object.

[0029] The target to be located is navigated according to the navigation path.

[0030] In one embodiment, the target positioning device further includes a warning module, the warning module being used for:

[0031] The electronic fence corresponding to the target object of the risk category in the target space is obtained; the electronic fence is determined based on the target object location of the risk category detected by the second device.

[0032] If the distance between the target location of the object to be located and the electronic fence reaches a distance threshold, an alert will be issued.

[0033] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to at least implement the steps of the target localization method of the embodiments of this application.

[0034] A target localization system, comprising:

[0035] A first device set in the target space is used to collect first position detection information of the target to be located in the target space;

[0036] A computer device communicatively connected to the first device, the computer device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program performing at least the following steps:

[0037] Acquire the first position detection information of the target to be located in the target space collected by the first device, and determine the first detection result of the target to be located based on the first position detection information;

[0038] The calibration area of ​​the target space is obtained; the calibration area is determined based on the second position detection information collected by the second device in the target space.

[0039] The first detection result of the target to be located is calibrated based on the calibration area to obtain the target position of the target in the target space.

[0040] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements at least the steps of the target localization method of the embodiments of this application.

[0041] A computer program product or computer program includes computer instructions stored in a computer-readable storage medium; a processor of a computer device reads the computer instructions from the computer-readable storage medium, and when the processor executes the computer instructions, it implements the steps of the target localization method of the embodiments of this application.

[0042] The aforementioned target positioning method, apparatus, system, computer equipment, and storage medium, when locating a target within a target space, acquire first position detection information of the target collected by a first device and determine a first detection result of the target based on the first position detection information; acquire a calibration area of ​​the target space and perform calibration processing on the first detection result of the target based on the calibration area to obtain the target position of the target in the target space, wherein the calibration area is determined based on second position detection information collected by a second device in the target space. This configuration enables joint positioning by two different positioning devices, thereby overcoming the problem of low positioning accuracy that may occur due to interference or other reasons when positioning is performed using only one positioning device, and thus meeting the high positioning accuracy requirements of different scenarios. Attached Figure Description

[0043] Figure 1 This is a diagram illustrating the implementation environment of a target localization method in one embodiment.

[0044] Figure 2 This is a hardware structure block diagram of a gateway in one embodiment;

[0045] Figure 3 This is a flowchart illustrating a target localization method in one embodiment;

[0046] Figure 4 This is a flowchart illustrating the target localization method in another embodiment;

[0047] Figure 5 This is a flowchart illustrating the target localization method in another embodiment;

[0048] Figure 6 This is a schematic diagram illustrating an application scenario of the target localization method in one embodiment;

[0049] Figure 7 This is a structural block diagram of a target positioning device in one embodiment;

[0050] Figure 8 This is a structural block diagram of the target positioning device in another embodiment;

[0051] Figure 9 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0052] 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.

[0053] Application Overview

[0054] As described in the background section, many current positioning technologies suffer from errors due to interference in practical applications, resulting in positioning accuracy that fails to meet actual requirements to some extent. For example, millimeter-wave radar positioning technology is significantly affected by multipath effects in enclosed spaces, easily leading to positioning errors, especially when detecting moving targets. Similarly, lidar positioning technology is susceptible to positioning errors due to interference such as specular reflection. Furthermore, as the demands for positioning accuracy increase, the aforementioned technologies are no longer adequate to meet practical needs.

[0055] In response to the above problems, the inventors discovered through research that other positioning technologies, such as UWB positioning technology, have high positioning accuracy and can better adapt to positioning scenarios with high precision requirements. However, the practical application of UWB positioning technology is also limited by the following: the target to be located must carry a positioning tag; if it does not carry a positioning tag, real-time positioning cannot be completed.

[0056] Based on this, this application proposes a target positioning method, apparatus, system, computer equipment, and storage medium that combines two different positioning technologies, aiming to combine the advantages of the two different positioning technologies to achieve better and more accurate positioning. The specific implementation scheme is described in detail below through embodiments.

[0057] Exemplary Implementation Environment

[0058] The target localization method provided in this application can be applied to, for example... Figure 1 In the illustrated implementation environment, the first device 100 and the second device 110 are communicatively connected to the gateway 120 via a network. The gateway 120 is communicatively connected to the router 130 via a network, and the router 130 is communicatively connected to the cloud server 140 via a network. Furthermore, in some embodiments, the implementation environment may also include a user terminal 150, which is communicatively connected to both the router 130 and the cloud server 140 via networks. In some implementations, the devices can establish network connections and communicate with each other via 2G / 3G / 4G / 5G, WIFI, or other methods.

[0059] The first device 100 and the second device 110 are different types of positioning devices. The first device 100 is capable of locating a large number of objects in the target space but is easily affected by environmental interference, such as, but not limited to, millimeter-wave radar or lidar. The second device 110 has a higher positioning accuracy than the first device 100, but requires the object being detected to carry a positioning tag, thus limiting its application scenarios. The second device 110 may include, but is not limited to, UWB devices. Furthermore, depending on the specific type of application, the first device 100 and the second device 110 can be pre-set at appropriate locations in the target space to be located. When setting the specific locations of the first device 100 and the second device 110, the goal is to maximize signal coverage while minimizing environmental obstruction and interference.

[0060] User terminal 150 may be, but is not limited to, smartphones, tablets, laptops, and desktop computers, and is used to obtain location results and other information in certain scenarios.

[0061] Figure 2 This is a hardware structure block diagram of a gateway according to an exemplary embodiment. This gateway 120 is suitable for... Figure 1 The implementation environment is shown.

[0062] It should be noted that this gateway is merely an example adapted to this invention and should not be construed as providing any limitation on the scope of use of this invention. Furthermore, this gateway should not be interpreted as requiring or depending on any specific feature. Figure 2 One or more components of the exemplary gateway 120 shown.

[0063] The hardware structure of the gateway 120 can vary significantly due to differences in configuration or performance, such as Figure 2 As shown, the gateway 120 includes: a power supply 1210, an interface 1230, at least one memory 1250, and at least one central processing unit (CPU) 1270.

[0064] The power supply 1210 is used to provide operating voltage for the various hardware devices on the gateway 120.

[0065] Interface 1230 includes at least one wired or wireless network interface 1231, at least one serial-to-parallel conversion interface 1233, at least one input / output interface 1235, and at least one USB interface 1237, etc., for communicating with external devices.

[0066] The memory 1250 serves as a resource storage medium and can be a read-only memory, random access memory, disk, or optical disk, etc. The resources stored on it include an operating system 1251, application programs 1253, or data 1255, and the storage method can be temporary or permanent storage. The operating system 1251 manages and controls the various hardware devices on the gateway 120 and the application programs 1253 to enable the central processing unit 1270 to perform calculations and processing on massive amounts of data 1255. It can be Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, FreeRTOS, etc. The application programs 1253 are computer programs that perform at least one specific task based on the operating system 1251, and may include at least one module (…). Figure 2 (Not shown in the image), each module can contain a series of computer-readable instructions for gateway 120. Data 1255 can be photos, images, etc., stored on a disk.

[0067] The central processing unit 1270 may include one or more processors and is configured to communicate with the memory 1250 via a bus for computing and processing massive amounts of data 1255 in the memory 1250.

[0068] As described in detail above, the gateway 120 to which this invention is applied will perform the corresponding processing method by reading a series of computer-readable instructions stored in the memory 1250 by the central processing unit 1270.

[0069] Furthermore, the present invention can also be implemented through hardware circuits or hardware circuits combined with software instructions. Therefore, the implementation of the present invention is not limited to any specific hardware circuit, software, or combination thereof.

[0070] Exemplary methods

[0071] Please see Figure 3 In this exemplary embodiment, a target localization method is provided, applicable to Figure 1 The illustrated implementation environment includes electronic devices such as gateways or cloud servers, used to locate the target within the target space. The method is illustrated using an electronic device as an example; the electronic device could be... Figure 1 The target localization method, which can be executed by the gateway or cloud server, may include the following steps:

[0072] Step S301: The electronic device acquires the first position detection information of the target to be located in the target space collected by the first device, and determines the first detection result of the target to be located based on the first position detection information.

[0073] The first device can be a device capable of collecting location detection information, such as a millimeter-wave radar device; the first device can be pre-set at a specific location within the target space.

[0074] Specifically, after the first device collects the first position detection information of the target to be located, it sends the collected first position detection information to the electronic device for processing, thereby obtaining the first detection result of the target to be located.

[0075] It is understandable that the specific content and type of the first position detection information collected will differ depending on the type of the first device, and correspondingly, the processing procedures of the electronic equipment will also differ. For example, when the first device is a millimeter-wave radar, according to the positioning principle of millimeter-wave radar, the first position detection information includes: the radial distance and azimuth angle of the target to be located relative to the transmitting component (antenna), and the velocity of the target to be located. Accordingly, the electronic equipment processes the aforementioned first position detection information using a corresponding positioning algorithm to obtain the first detection result of the target to be located.

[0076] The positioning principle of millimeter-wave radar includes: the millimeter-wave radar emits a linear frequency modulated continuous wave, which is reflected by the target. The receiver then performs a series of steps, such as mixing, coherent accumulation, FFT (Fast Fourier Transform), noncoherent accumulation, CFAR (Constant False-Alarm Rate), peak extraction, and angle mapping, to obtain the position and velocity of the target in space. Specifically, the echoes from all receiving antennas of the millimeter-wave radar are converted into intermediate frequency (IF) signals through mixing. A two-dimensional FFT transformation is performed on each IF signal to obtain a two-dimensional range-velocity map (complex number), and the modulus is calculated to obtain a range-velocity map (real number). The points corresponding to the modulus values ​​of multiple two-dimensional range-velocity maps are added together to obtain the overall range-velocity map. In the range-velocity map, a two-dimensional CFAR method is used to find points greater than the CFAR threshold. The velocity of these points is the velocity of the target, and the distance is the radial distance of the target. Based on the range and velocity positions of these points in the map, the corresponding complex values ​​are selected. The FFT modulus of the corresponding values ​​of the horizontal antenna is taken, and the maximum value is the corresponding horizontal angle. The FFT modulus of the corresponding values ​​of the vertical antenna is taken, and the maximum value is the elevation angle. If necessary, the radial distance, horizontal angle, and elevation angle of the target can be converted into coordinate values ​​in a Cartesian coordinate system.

[0077] In some embodiments, if the electronic device is a gateway, the gateway determines the first detection result of the target to be located based on the positioning algorithm corresponding to the first device. In other embodiments, if the electronic device is a cloud server, the first device sends the collected first location detection information to the gateway, which forwards it to the cloud server, and then the cloud server determines the first detection result of the target to be located based on the positioning algorithm corresponding to the first device.

[0078] In some implementations, the first detection result of the target to be located may be represented in coordinate form, but is not limited to that shown. Accordingly, before applying the scheme of this embodiment, a Cartesian coordinate system, such as a spatial rectangular coordinate system, can be established for the target space. The origin and the direction of the coordinate axes can be adjusted according to the actual situation and are not limited here.

[0079] Step S302: The electronic device acquires the calibration area of ​​the target space; the calibration area is determined based on the second position detection information collected by the second device in the target space.

[0080] The calibration area refers to a designated area used to calibrate location information. For example, if the first location detection information is not accurate enough, the calibration area can be used to calibrate the first location detection information to obtain a more accurate location detection result.

[0081] Step S303: The electronic device performs calibration processing on the first detection result of the target to be located based on the calibration area to obtain the target position of the target to be located in the target space.

[0082] Specifically, because the first device may experience errors due to interference when collecting the measurement and positioning information of the target, the collected first position detection information usually contains some erroneous information, which will lead to deviations in the first detection result obtained by the electronic device after processing. Therefore, a calibration area is first determined based on the second position detection information collected by the second device, which has relatively higher positioning accuracy. Then, the first detection result of the target obtained by the first device is calibrated based on the calibration area, thereby making the final target position more accurate.

[0083] Similar to the first device, the second device can be pre-set at a specific location within the target space. After collecting the second location detection information, it sends the collected information to an electronic device for processing, thereby determining the calibration area. The electronic device can be a gateway or a cloud server; that is, the calibration area can be determined by the gateway or cloud server.

[0084] Furthermore, it should be noted that the deviation in the first detection result due to interference typically manifests as follows: for a real target, at least two targets are detected during detection. Among these at least two detected targets, one is a real target (i.e., the target to be located) and at least one is a false target. A false target is a target that is detected due to interference or other reasons and does not actually exist. Based on this, calibration processing using the second position detection information collected by the second device can include two approaches: identifying the real target, or (given the existence of false targets) eliminating false targets. The specific approach used for calibration processing depends on the actual application scenario, which will be explained in detail below.

[0085] In some embodiments, one approach to achieving calibration processing by determining the true target is as follows:

[0086] Since the second device (such as a UWB device) needs to detect the positioning tag to collect the second location detection information, the solution in this embodiment is applicable to scenarios where the target to be located carries a positioning tag. Furthermore, because the target to be located carries a positioning tag, the second location detection information collected by the second device through detecting the positioning tag has high accuracy, very small error, and will not detect more than one target for the same target due to interference or other reasons. Based on this, the second location detection information collected by the second device can be used to determine the second detection result of the target to be located, and then the second detection result can be used to verify the position of the real target in the first detection result.

[0087] The positioning principle based on UWB devices involves at least three UWB base stations pre-positioned at different locations within space continuously broadcasting electromagnetic wave signals to the surrounding environment. Upon receiving these signals, the positioning tag sends a response signal to the surrounding UWB base stations. Since different UWB base stations receive the response signal at different times, the tag's location can be calculated using either the TOA (Time of Arrival) algorithm or the TDOA (Time Difference of Arrival) algorithm. Calculating the positioning location using either the TOA or TDOA algorithm is existing technology, and therefore its specific process will not be detailed here.

[0088] Based on the above ideas, as a feasible specific implementation, in some embodiments, the calibration area includes a verification area; step S302 may specifically include: if the target to be located carries a positioning tag, then acquire the second position detection information collected by the second device in the target space, and determine the second detection result of the target to be located based on the second position detection information; determine the current verification area in the target space based on the second detection result; wherein, the second device collects the second position detection information by detecting the positioning tag; correspondingly, step S303 may specifically include: calibrating the first detection result of the target to be located based on the verification area to obtain the target position of the target to be located in the target space.

[0089] Specifically, since the same target is being detected and located, even with different positioning accuracies, the actual target detected by the first device is usually not too far from the second detection result of the second device. Therefore, in this embodiment, a verification area can be obtained based on the second detection result. If one of the at least two targets included in the first detection result is located within the verification area, then the target located within the verification area is the actual target detected by the first device. Since the position of the target to be located may change, the verification area is determined based on the current position of the target; that is, the verification area obtained each time is the current verification area. In some embodiments, for ease of subsequent processing, the representation of the second detection result of the target to be located is consistent with the representation of the first detection result. For example, both are represented in spatial rectangular coordinates.

[0090] In some embodiments, determining the current verification region in the target space based on the second detection result may specifically include: obtaining the current verification region in the target space based on the second detection result and the target calibration coefficient.

[0091] Specifically, in some embodiments, the verification area can be an annular area centered on the second detection result and with the target calibration coefficient as the radius. Of course, the verification area can also be other shapes, as long as the above purpose can be achieved, and there is no limitation on this.

[0092] Specifically, in practical applications, the target calibration coefficient can be determined based on the positioning accuracy of the first and second devices. Since the higher the positioning accuracy of the first and second devices, the closer their detection results are, the target calibration coefficient is negatively correlated with the positioning accuracy of the first and second devices; that is, the higher the positioning accuracy of the first and second devices, the smaller the target calibration coefficient. More specifically, in some embodiments, the target calibration coefficient can be the sum of the positioning accuracy tx1 of the first device and the positioning accuracy tx2 of the second device (tx1+tx2).

[0093] Alternatively, the product of the sum of the positioning accuracy tx1 of the first device and the positioning accuracy tx2 of the second device and a preset multiplier k (tx1+tx2)*k can be used as the target calibration coefficient. In this way, by adjusting the specific value of k, it can be better ensured that the verification area contains only the real targets detected by the first device, and not false targets.

[0094] Furthermore, when implementing steps S303 and S304, the true target can also be determined in other ways. For example, as another feasible implementation, it can be determined that among the at least two targets included in the first detection result, the one closest to the second detection result is the true target.

[0095] Furthermore, in some embodiments, the calibration process of the first detection result of the target to be located based on the verification area to obtain the target position of the target to be located in the target space may specifically include: if the first device detects at least one non-stationary target to be located, determining the area where the target to be located is located based on the first detection result of the non-stationary target to be located; if a non-stationary target to be located is located within the verification area, then fusing the first detection result and the second detection result of the target to be located within the verification area to obtain the target position of the target to be located in the target space.

[0096] Specifically, in practical applications, non-stationary targets are more susceptible to interference. Therefore, the solution in this embodiment is more effective when locating non-stationary targets. Based on this, when detecting non-stationary targets through the first device, if at least one non-stationary target is detected, the first detection result of the target located in the verification area among the at least one non-stationary target is determined to be a real target.

[0097] Furthermore, in this embodiment, after determining the actual target, its corresponding first detection result is fused with the second detection result based on the second device, and the fused result is used as the target position of the target to be located in the target space. Through fusion processing, the positioning result can comprehensively consider the detection information from both the first and second devices, thereby improving positioning accuracy.

[0098] More specifically, in some embodiments, the fusion process may include: performing specific calculations on the first detection result and the second detection result corresponding to the real target, such as directly calculating the average value, or calculating the average value after weighting, etc. Wherein, if both the first and second detection results are represented by coordinates, performing specific calculations on the first and second detection results means calculating the coordinates corresponding to each of the first and second detection results. Furthermore, if a weighted average value is used, the corresponding weights can be determined based on the ranging resolution of the first and second devices; for example, in some embodiments, the ranging resolution of the first device is set to τ. R The ranging resolution of the second device is τ. U The weight of the first detection result is then... The weight of the second test result is

[0099] It should be noted that in other embodiments, after determining the true target in the first detection result detected by the first device, it may not be necessary to fuse it with the second detection result. Instead, its position may be directly used as the target position of the target to be located in the target space. This reduces the processing steps, speeds up the processing, and allows for faster location results.

[0100] The above method can determine the real target when the first device detects at least two targets for the same target due to interference, thereby improving positioning accuracy.

[0101] Furthermore, in some embodiments, the calibration process is achieved by eliminating spurious targets as follows:

[0102] Since the second device (such as a UWB device) needs to detect the positioning tag to collect the second location detection information, the above-mentioned calibration processing scheme based on the verification area cannot be applied to scenarios where the target to be located does not carry a positioning tag. To address this issue, in this embodiment, considering that for the same target space, the areas prone to interference are usually relatively fixed, the historical positioning results of the second device can be used, that is, the second location detection information collected by the second device in the target space in the past (hereinafter referred to as historical second location detection information), to determine the second detection results for other positioning targets. By using the second detection results for other positioning targets, the areas in the target space prone to false targets can be determined through statistical methods, thereby eliminating possible false targets during subsequent positioning.

[0103] Based on the above ideas, as a feasible specific implementation, in some embodiments, the calibration area includes an interference area, wherein the interference area is determined based on historical second position detection information collected by the second device in the target space; step S302 may specifically include: acquiring a predetermined interference area in the target space; correspondingly, step S303 may specifically include: if the target to be located does not carry a positioning tag, then among at least one non-stationary target to be located detected by the first device, the target to be located located within the interference area is removed; the first detection result corresponding to the removed target to be located is determined as the target position of the target to be located in the target space.

[0104] Specifically, in this embodiment, taking the localization of a non-stationary target as an example, since the first device may detect two or more target results for the same target due to interference, the target located within the interference area is eliminated based on the acquired interference area. The first detection result corresponding to the eliminated target is then the desired location of the true target. The eliminated target is considered a false target; that is, the target located within the interference area is treated as a false target and eliminated. This eliminates interference, making the final localization result more accurate.

[0105] In some embodiments, the process of determining the interference region may include:

[0106] Historical location records are acquired, and areas where false targets have appeared in these records are identified. Areas where the frequency of false targets appears is greater than a preset frequency are marked as interference areas. The historical location records include at least historical first detection information collected by a first device, historical second detection information collected by a second device, historical first detection results obtained based on the historical first detection information, and historical second detection results obtained based on the historical second detection information. False targets can be obtained when determining real targets using the method described in the foregoing embodiments. That is, when determining real targets in the first detection results according to the scheme described in the foregoing embodiments to achieve calibration processing, targets other than real targets in the first detection results can be recorded as false targets, thus enabling application in this embodiment.

[0107] It should be noted that in other embodiments, the interference area can also be predetermined through other means. For example, the location of the interference source can be predetermined based on factors such as the location and type of the first device and the cause of the interference, and then the area where false targets may appear can be determined as the interference area based on the location of the interference source. For example, when the first device is a millimeter-wave radar, the cause of the interference is multipath effect. Therefore, the area / environment that is prone to multipath effect can be determined in advance based on the setting location of the millimeter-wave radar in the target space, and then the interference area can be determined by combining the area / environment that is prone to multipath effect.

[0108] The above method can eliminate false targets when the first device detects at least two targets for the same target due to interference, thereby improving positioning accuracy.

[0109] In summary, the target localization method described above, when locating a target within a target space, involves acquiring the first position detection information of the target collected by a first device and determining the first detection result of the target based on this information. A calibration region within the target space is then acquired, and the first detection result of the target is calibrated based on this calibration region to obtain the target position of the target within the target space. The calibration region is determined based on the second position detection information collected by a second device within the target space. This configuration enables joint localization using two different positioning devices, overcoming the potential for low positioning accuracy due to interference when using only one device. This allows for meeting the high accuracy requirements of various scenarios.

[0110] Furthermore, in some embodiments, such as Figure 4 As shown, the above target localization method may further include:

[0111] Step S401: The electronic device responds to the navigation operation for the target object in the target space and obtains the target object's position.

[0112] Depending on the specific application scenario, the specific method for obtaining the target object's location can vary. For example, when the target object is a large item that the first device can detect, the first device can collect the target object's location information and determine its location. However, when the target object is a small item that the first device cannot detect (such as a pen placed on a table) or is placed in a location that the first device cannot detect (such as a medicine box placed in a drawer), it is necessary to pre-set a positioning tag on the target object and use a second device to collect the target object's location information based on the positioning tag and determine its location.

[0113] Step S402: Based on the obstacle positions detected by the first device in the target space, the electronic device performs path planning for the target to be located and the target object to obtain a navigation path for the target object.

[0114] Specifically, an obstacle is an object that affects the movement path of the target when it moves toward the target object, and it is usually a large object, so its position can be detected by the first device.

[0115] In some embodiments, the optimal path can be calculated using the A* (A-Star) algorithm, Dijkstra's algorithm, or other algorithms. This embodiment does not improve the specific path planning method, so it will not be described in detail here.

[0116] Step S403: The electronic device performs navigation processing on the target to be located according to the navigation path.

[0117] In some embodiments, when the electronic device navigates the target to be located according to the navigation path, it can send the navigation path to a preset device associated with the target. Depending on the specific type of the target, the preset device associated with the target can be a component of the target or a separate device carried or worn by the target. For example, when the target is a robot, the preset device can be a component of the robot; when the target is a human body, the preset device can be a smartphone carried by the human body.

[0118] Using the method of this embodiment, navigation can be performed on the target to be located, helping the target to quickly reach the location of the object.

[0119] For example, this can be applied to scenarios where forgetful elderly people at home need to find medicine: location tags are set on the medicines in advance, and then the forgetful elderly person can use their smartphone to type or voice input the medicine they want to find. Once the gateway or cloud server determines the location of the elderly person and the medicine, as well as the location of obstacles between them, it can perform route planning and use the planning results to navigate the elderly person. The navigation information can be output by voice to help the elderly person reach the location of the medicine.

[0120] In some embodiments, during the navigation process of the target to be located, the above method may further include:

[0121] Furthermore, in some embodiments, such as Figure 5 As shown, the above target positioning method may further include: if the target position of the target to be located is less than the target object position, sending a prompting instruction to the preset device so that the preset device can provide a prompt.

[0122] In this embodiment, a prompting function can be implemented when the target to be located is less than a preset distance from the target object. For example, based on the above scenario, when an elderly person is close to the medicine, a voice prompt can be given through the elderly person's smartphone to inform them that they are approaching the target (medicine).

[0123] Furthermore, in some embodiments, such as Figure 5 As shown, the above target localization method may further include:

[0124] Step S501: The electronic device acquires the electronic fence corresponding to the target object of the risk category in the target space; the electronic fence is determined based on the target object location of the target object of the risk category detected by the second device.

[0125] Step S502: If the distance between the target location of the target to be located and the electronic fence reaches a distance threshold, the electronic device will issue a warning.

[0126] Specifically, in this embodiment, the electronic fence function can be realized based on the above-mentioned target positioning method. That is, when the distance between the target to be located and the electronic fence reaches the distance threshold, the warning function can be realized.

[0127] For example, an electronic fence can be built around a child in the home as the target to be located, and a target of a risk category bound with a location tag as the center. When the child gets close to the electronic fence to a distance threshold, that is, when the child is close to a target of a risk category, the electronic device can issue an alert, such as sending an alert command to the parent's terminal (such as a smartphone) so that the parent can notice it in time.

[0128] It should be noted that although the first and second devices in the above embodiments are mainly illustrated using millimeter-wave radar and UWB devices as examples, it should be understood that, based on the implementation principle of the above schemes, the corresponding schemes can also be achieved by reasonably replacing the UWB devices and millimeter-wave radar with other positioning devices. For example, the millimeter-wave radar can be replaced with lidar. In principle, the following conditions should be met: the positioning accuracy of the second device is greater than that of the first device, but for the second device to achieve positioning, the target to be positioned must carry a positioning tag; while the first device can achieve positioning of a large number of targets in space, even if the target to be positioned does not carry a positioning tag.

[0129] Exemplary application scenarios

[0130] This application also provides an application scenario in which the above-described positioning method is applied. Specifically, combined with Figure 6 The application process of this positioning method in this application scenario is as follows:

[0131] 1) Deploy UWB base stations indoors and label them:

[0132] Four UWB base stations are deployed indoors (at least three are required in unobstructed conditions), preferably on the ceiling to minimize obstruction from other objects. An indoor Cartesian coordinate system is established with the upper left corner of the room as the origin, and the positions (x, y) of the four deployed UWB base stations within this coordinate system are measured. U1 ,y U1 ,z U1 ), (x U2 ,y U2 ,z U2 ), (x U3 ,y U3 ,z U3 ), (x U4 ,y U4 ,z U4 ).

[0133] 2) Install millimeter-wave radar indoors and calibrate it:

[0134] A millimeter-wave radar is installed on an indoor wall, and its position in the aforementioned coordinate system (x) is measured. R ,y R ,z R ).

[0135] 3) UWB positioning:

[0136] The mobile target Tar1 (e.g., a person walking indoors) and the stationary target Tar2 (e.g., a stationary valuable object) carry UWB positioning tags Tag1 and Tag2 respectively, and normal communication is maintained between the UWB positioning tags and the UWB base station.

[0137] During the positioning process, the UWB base station sends data packets to the positioning tag, and the positioning tag (Tagi) sends a response packet (via electromagnetic waves) after receiving the data packets. The Cartesian coordinates of the positioning tag are (x... T,i ,y T,i ,z T,i When i is 1, it represents the coordinates of the location tag Tag1; when i is 2, it represents the coordinates of the location tag Tag2.

[0138] The four UWB base stations received the response packets at times t1, t2, t3, and t4, respectively. According to the TDOA method, the distances from the location tag Tagi to the four UWB base stations are:

[0139]

[0140] In the formula, d 12,i d 23,i d 34,i and d 14,i These represent the distances from the location tag to the four UWB base stations, respectively, and c represents the speed of light. In actual calculations, c can be approximated as 3*10^8 m / s.

[0141] Then, based on the coordinates of the four UWB base stations, the coordinates of the positioning tag Tagi can be calculated using the following formula:

[0142]

[0143] Based on the above formula (2), the positions of the location tags Tag1 and Tag2 can be calculated, that is, the position of the moving target (x). T,1 ,y T,1 ,z T,1 ) and the position (x) of the stationary target T,1 ,y T,1 ,z T,1 ).

[0144] 4) Millimeter-wave radar positioning:

[0145] Millimeter-wave radar transmits linear frequency modulated continuous waves, which are reflected by indoor targets. The receiver then performs mixing, coherent accumulation, FFT, non-coherent accumulation, CFAR, peak extraction, and angle mapping on the received signal to obtain the position and velocity (x′) of the target in space. T,j ,y′ T,j ,z′ T,j ,v′ T,j), j=1,...,m, where m is the number of targets detected by the millimeter-wave radar. Detected targets may include real moving targets, stationary obstacles, and some false targets caused by interference. If the target velocity is near 0, for example, less than a preset velocity value, then the target is considered a stationary obstacle (x′). T,2 ,y′ T,2 ,z′ T,2 If the target speed is not near 0, for example, if it is greater than or equal to the preset speed value, then the target is considered to be a non-stationary target.

[0146] Specifically, the echoes from all receiving antennas of the millimeter-wave radar are converted into intermediate frequency (IF) signals through mixing. A two-dimensional FFT transformation is performed on each IF signal to obtain a two-dimensional range-velocity map (complex number), and the modulus is calculated to obtain a range-velocity map (real number). The points corresponding to the modulus values ​​of multiple two-dimensional range-velocity maps are added together to obtain the overall range-velocity map. In the range-velocity map, a two-dimensional CFAR method is used to find points greater than the CFAR threshold. The velocity of these points is the target velocity v, and the distance is the target's radial distance. Based on the range and velocity positions of these points in the map, the corresponding complex values ​​are selected. The FFT modulus of the corresponding values ​​of the horizontal antenna is taken, and the maximum value is the corresponding horizontal angle. The FFT modulus of the corresponding values ​​of the vertical antenna is taken, and the maximum value is the elevation angle. The target's radial distance, horizontal angle, and elevation angle can be converted into three-axis coordinates x, y, z in a rectangular coordinate system.

[0147] 5) Joint positioning:

[0148] Scenario 1: A moving target carries a UWB positioning tag and is detected by both a UWB base station and millimeter-wave radar.

[0149] For a moving target carrying a UWB positioning tag, its coordinate position (x, y) can be obtained using the UWB positioning method in step 3). T,1 ,y T,1 ,z T,1 Then select the non-stationary target detected by millimeter-wave radar in step 4), whose position and velocity are (x′). T,j ,y′ T,j ,z′ T,j ,v′ T,j ),j=1,...,m', where m' is the number of non-stationary targets detected by the radar, including real moving targets and false targets obtained due to interference.

[0150] The moving target's location (x) obtained from UWB positioning T,1 ,y T,1 ,z T,1 ), resulting in a circular verification region ([x T,1 -τ x ,x T,1+τ x ],[y T,1 -τ y ,y T,1 +τ y ],[z T,1 -τ z ,z T,1 +τ z ]), where τ x ,τ y ,τ z These are thresholds in three dimensions. The circular verification area, as described in Example 2, is primarily determined by the positioning accuracy of the UWB base station and millimeter-wave radar. If the positioning accuracies of the UWB base station and millimeter-wave radar are tx1 and tx2 respectively, the threshold can be tx1 + tx2. Alternatively, tx1 + tx2 can be reduced or increased by a certain factor based on the actual situation to serve as the aforementioned threshold.

[0151] Next, it is verified whether the non-stationary targets obtained by the millimeter-wave radar fall within the aforementioned verification area. If there is only one non-stationary target located within the verification area, then this unique non-stationary target is determined to be the real target, and its position coordinates are marked as (x′). T,1 ,y′ T,1 ,z′ T,1 The remaining targets are false targets. Furthermore, the areas where false targets frequently appeared (with a frequency greater than the preset frequency) during multiple positioning attempts were statistically analyzed and identified as interference areas.

[0152] The final confirmed true target location (x′) detected by millimeter-wave radar T,1 ,y′ T,1 ,z′ T,1 ), combined with the moving target position (x) obtained by UWB positioning T,1 ,y T,1 ,z T,1 The weighted sums are then used to obtain the final joint localization result for the moving target T. M Location:

[0153]

[0154] In the formula, τ U and τ R These are the ranging resolutions for UWB base stations and millimeter-wave radars, respectively.

[0155] Furthermore, the indoor stationary obstacle T can be obtained from the millimeter-wave radar positioning in step 4). O Position (x) O ,y O ,z O )=(x′ T,2 ,y′T,2 ,z′ T,2 The stationary target T can be obtained from the UWB positioning in step 3). S Position (x) S ,y S ,z S )=(x T,2 ,y T,2 ,z T,2 ).

[0156] Scenario 2: The moving target does not carry a UWB positioning tag and is only detected by millimeter-wave radar.

[0157] Since the moving target does not carry a UWB positioning tag, the UWB positioning method in step 3) cannot be used to obtain its location. The target's location can only be determined by millimeter-wave radar detection. Furthermore, the moving target detected by millimeter-wave radar includes both real moving targets and some false targets caused by interference. In this case, the interference area obtained in scenario one can be used to eliminate false targets, thereby obtaining the real moving target T. M Position (x) M ,y M ,z M )=(x′ T,1 ,y′ T,1 ,z′ T,1 Alternatively, based on the characteristic that false targets generally appear randomly, targets that persist for less than a preset time can be identified as false targets and eliminated.

[0158] 6) Path planning:

[0159] Based on the moving target T obtained in step 5) M stationary target T S and indoor stationary obstacles T O The positions of T respectively M The position is set to the navigation starting position, with a stationary target T. S For navigation to the destination location, an indoor stationary obstacle T O To navigate to the location of obstacles in the middle, the A* algorithm is used to find a path from the moving target T indoors. M Move to stationary target T S And without passing through an indoor stationary obstacle T O The route with the lowest cost. This step can be applied to the user (moving target T). M Find important items (stationary target T) S In the context of ).

[0160] In addition, when a moving target T is detected M and stationary target T SWhen the current distance is less than a set threshold, a prompt can be issued. For example, in a scenario where someone is searching for an item, the system can announce via voice that the item is nearby and the exact distance. At the same time, based on the current location of the moving target and the location of the item, the direction of the item can be determined. In another scenario, in a hazardous material alarm scenario, the system can act as a virtual fence to issue alarms or prompts, prompting moving targets to stay away from hazardous materials.

[0161] It should be understood that, although Figure 3-5 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 3-5 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0162] Exemplary device

[0163] In one embodiment, such as Figure 7 As shown, a target positioning device 700 is provided, including: a first acquisition module 701, a second acquisition module 702, and a calibration module 703, wherein:

[0164] The first acquisition module 701 is used to: acquire first position detection information of the target to be located in the target space collected by the first device, and determine the first detection result of the target to be located based on the first position detection information;

[0165] The second acquisition module 702 is used to: acquire the calibration area of ​​the target space; the calibration area is determined based on the second position detection information collected by the second device in the target space;

[0166] The calibration module 703 is used to: perform calibration processing on the first detection result of the target to be located based on the calibration area, so as to obtain the target position of the target to be located in the target space.

[0167] In one embodiment, the calibration area includes a verification area; when the second acquisition module 702 acquires the calibration area of ​​the target space, it is specifically used to: if the target to be located carries a positioning tag, acquire the second position detection information collected by the second device in the target space, and determine the second detection result of the target to be located based on the second position detection information; the second device collects the second position detection information by detecting the positioning tag; and determines the current verification area in the target space based on the second detection result; when the calibration module 703 performs calibration processing on the first detection result of the target to be located based on the calibration area to obtain the target position of the target to be located in the target space, it is specifically used to: perform calibration processing on the first detection result of the target to be located based on the verification area to obtain the target position of the target to be located in the target space.

[0168] In one embodiment, when the second acquisition module 702 determines the current verification area in the target space based on the second detection result, it is specifically used to: obtain the current verification area in the target space based on the second detection result and the target calibration coefficient; the target calibration coefficient is negatively correlated with the positioning accuracy of the first device and the second device.

[0169] In one embodiment, when the calibration module 703 performs calibration processing on the first detection result of the target to be located based on the verification area to obtain the target position of the target to be located in the target space, it is specifically used for: if the first device detects at least one non-stationary target to be located, determining the area where the target to be located is located based on the first detection result of the non-stationary target to be located; if a non-stationary target to be located is located within the verification area, then fusing the first detection result and the second detection result of the target to be located within the verification area to obtain the target position of the target to be located in the target space.

[0170] In one embodiment, the calibration area includes an interference area; the interference area is determined based on historical second position detection information collected by the second device in the target space; when the calibration module 703 performs calibration processing on the first detection result of the target to be located based on the calibration area to obtain the target position of the target to be located in the target space, it is specifically used to: if the target to be located does not carry a positioning tag, then remove the target to be located located within the interference area from at least one non-stationary target to be located detected by the first device; and determine the first detection result corresponding to the removed target to be located as the target position of the target to be located in the target space.

[0171] In one embodiment, such as Figure 8As shown, the target positioning device 700 further includes a navigation module 704; the navigation module 704 is used to: obtain the target position of the target object in response to a navigation operation for the target object in the target space; perform path planning for the target to be positioned and the target object based on the obstacle position of the obstacle detected by the first device in the target space to obtain a navigation path for the target object; and perform navigation processing on the target to be positioned according to the navigation path.

[0172] In one embodiment, such as Figure 8 As shown, the target positioning device 700 also includes an alert module 705; the alert module 705 is used to: acquire the electronic fence corresponding to the target object of the risk category in the target space; the electronic fence is determined based on the target object position of the target object of the risk category detected by the second device; if the target position of the target to be located reaches a distance threshold with the electronic fence, an alert is issued.

[0173] Specific limitations regarding the target positioning device can be found in the limitations of the target positioning method described above, and will not be repeated here. Each module in the aforementioned target positioning 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 operations corresponding to each module.

[0174] Exemplary computer device

[0175] In one embodiment, a computer device is provided, which may be a gateway or a cloud server, and its internal structure diagram may be as follows: Figure 9 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data such as positioning or navigation algorithms. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a positioning method.

[0176] Those skilled in the art will understand that Figure 9The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0177] In one embodiment, a computer device is provided, which may be a gateway or a cloud server, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the various steps of the target localization method shown in the above exemplary method section embodiments.

[0178] Exemplary positioning system

[0179] In one embodiment, a target localization system is provided, comprising:

[0180] A first device set in the target space is used to collect first position detection information of the target to be located in the target space;

[0181] A computer device communicatively connected to the first device, the computer device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the various steps of the target localization method shown in the exemplary method embodiments above. This may include the following steps:

[0182] Acquire the first position detection information of the target to be located in the target space collected by the first device, and determine the first detection result of the target to be located based on the first position detection information;

[0183] The calibration area of ​​the target space is obtained; the calibration area is determined based on the second position detection information collected by the second device in the target space.

[0184] The first detection result of the target to be located is calibrated based on the calibration area to obtain the target position of the target in the target space.

[0185] In some embodiments, the target positioning system further includes a second device disposed in the target space and communicatively connected to the computer device, for collecting second position detection information of the target to be located in the target space.

[0186] Exemplary computer program products and computer-readable storage media

[0187] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the computer device to perform the steps of the target localization method in the above-described method embodiments.

[0188] Computer program products can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the device or as a standalone software package.

[0189] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the various steps of the target localization method shown in the embodiments of the exemplary method section above.

[0190] Those skilled in the art will understand that all or part of the processes in the methods of 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, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0191] 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.

[0192] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. 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 patent application should be determined by the appended claims.

Claims

1. A target positioning method characterized by, The target positioning method comprises: obtaining first position detection information of a target to be positioned in a target space collected by a first device, and determining a first detection result of the target to be positioned based on the first position detection information; obtaining a calibration region of the target space; the calibration region is determined based on second position detection information collected by a second device in the target space; the calibration region comprises a verification region and / or an interference region; the verification region is used for determining a position in the first detection result located in the verification region as a real position of the target to be positioned; and the interference region is used for eliminating a false position in the first detection result located in the interference region; performing calibration processing on the first detection result of the target to be positioned based on the calibration region, to obtain a target position of the target to be positioned in the target space.

2. The method of claim 1, wherein, The calibration region comprises a verification region; and the obtaining of the calibration region of the target space comprises: if the target to be positioned carries a positioning tag, obtaining second position detection information collected by the second device in the target space, and determining a second detection result of the target to be positioned according to the second position detection information; the second device collects the second position detection information by detecting the positioning tag; determining a current verification region under the target space according to the second detection result; the calibration processing on the first detection result of the target to be positioned based on the calibration region to obtain the target position of the target to be positioned in the target space comprises: the calibration processing on the first detection result of the target to be positioned based on the verification region to obtain the target position of the target to be positioned in the target space.

3. The method of claim 2, wherein, The determination of the current verification region under the target space according to the second detection result comprises: obtaining the current verification region under the target space according to the second detection result and a target calibration coefficient; the target calibration coefficient is negatively correlated with positioning accuracy of the first device and the second device.

4. The method of claim 2, wherein, The calibration processing on the first detection result of the target to be positioned based on the verification region to obtain the target position of the target to be positioned in the target space comprises: if the first device detects at least one non-stationary target to be positioned, determining a region in which the target to be positioned is located according to the first detection result of the non-stationary target to be positioned; if the non-stationary target to be positioned is located in the verification region, performing fusion processing on the first detection result and the second detection result of the target to be positioned located in the verification region, to obtain the target position of the target to be positioned in the target space.

5. The method of claim 1, wherein, The calibration region comprises an interference region; the interference region is determined based on historical second position detection information collected by the second device in the target space; The calibration processing on the first detection result of the target to be positioned based on the calibration region to obtain the target position of the target to be positioned in the target space comprises: If the target to be positioned does not carry a positioning tag, the target to be positioned in the interference area among the at least one non-stationary target to be positioned detected by the first device is eliminated; The first detection result corresponding to the eliminated target to be positioned is determined as the target position of the target to be positioned in the target space.

6. The method according to any one of claims 1 to 5, characterized in that, The method further comprises: In response to a navigation operation for the target object in the target space, a target object position of the target object is acquired; Based on the obstacle position of the obstacle in the target space detected by the first device, path planning is performed on the target to be positioned and the target object, to obtain a navigation path for the target object; The target to be positioned is navigated according to the navigation path.

7. The method according to any one of claims 1 to 5, characterized in that, The method further comprises: An electronic fence corresponding to the target object of the risk category in the target space is acquired; the electronic fence is determined based on the target object position of the target object of the risk category detected by the second device; If the distance between the target position of the target to be positioned and the electronic fence reaches a distance threshold, a warning process is performed.

8. A target positioning device, characterized by The target positioning device comprises: A first acquisition module is configured to acquire first position detection information of a target to be positioned in a target space collected by a first device, and determine a first detection result of the target to be positioned based on the first position detection information; A second acquisition module is configured to acquire a calibration area of the target space; the calibration area is determined based on second position detection information collected by a second device in the target space; the calibration area comprises a verification area and / or an interference area; the verification area is configured to determine a position in the first detection result that is in the verification area as a real position of the target to be positioned; and the interference area is configured to eliminate a false position in the first detection result that is in the interference area; A calibration module is configured to perform calibration processing on the first detection result of the target to be positioned based on the calibration area, to obtain a target position of the target to be positioned in the target space. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor executes the computer program to implement the steps of the method in any one of claims 1 to 7.

10. A target location system characterized by Comprise: A first device arranged in a target space is configured to collect first position detection information of a target to be positioned in the target space; A computer device in communication connection with the first device, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method in any one of claims 1 to 7.

11. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 7.

Images