Methods, computing devices, and storage media for calibrating infrared distance sensors

Abstract

The present disclosure relates to a method, a computing device and a storage medium for calibrating an infrared distance sensor. The method comprises: obtaining an initial unobstructed floor noise value and a reference obstructed floor noise value of the infrared distance sensor, and determining a near threshold and a far threshold of the infrared distance sensor according to the initial unobstructed floor noise value and / or the reference obstructed floor noise value; and determining that the unobstructed floor noise value of the infrared distance sensor changes and the change exceeds a threshold, and adjusting the near threshold and the far threshold according to the changed unobstructed floor noise value. The accuracy of the infrared distance sensor can be improved by using the method of the present disclosure.

Description

Technical Field

[0001] This disclosure relates to methods, computing devices, and storage media for calibrating infrared distance sensors. Background Technology

[0002] Compared to ultrasonic solutions, infrared distance sensors offer advantages such as high accuracy, fast response, and lower cost. As a result, infrared distance sensors have become the mainstream solution for distance sensors in various electronic devices (such as mobile phones). Summary of the Invention

[0003] This disclosure provides methods for calibrating infrared distance sensors, as well as corresponding computing devices and non-transitory machine-readable storage media for performing these methods.

[0004] According to a first aspect of the present disclosure, a method for calibrating an infrared distance sensor is provided, comprising: acquiring an initial unobstructed noise floor value and a reference occlusion noise floor value of the infrared distance sensor, and determining a proximity threshold and a distance threshold of the infrared distance sensor based on the initial unobstructed noise floor value and / or the reference occlusion noise floor value; and determining that the unobstructed noise floor value of the infrared distance sensor changes and the change exceeds a threshold value, and adjusting the proximity threshold and the distance threshold based on the changed unobstructed noise floor value.

[0005] Optionally, determining that the unobstructed noise floor value of the infrared distance sensor has changed includes: initiating a detection procedure for the unobstructed noise floor value based on time and / or temperature conditions related to the infrared distance sensor.

[0006] Optionally, the detection program may be initiated based on time and / or temperature conditions related to the infrared distance sensor, including: initiating the detection program at preset time intervals; and / or initiating the detection program when the temperature is within a preset range, wherein the temperature includes the temperature of the infrared distance sensor itself, and / or the ambient temperature of the infrared distance sensor, and / or the temperature of the electronic device on which the infrared distance sensor is installed, the ambient temperature, and / or the temperature of its components.

[0007] Optionally, the method further includes: acquiring data on the change of the unobstructed noise floor value of the infrared distance sensor with the temperature; and determining the time period, the range, and / or the threshold in advance based on the data.

[0008] Optionally, determining that the unobstructed noise floor value of the infrared distance sensor has changed includes: determining that the infrared distance sensor is in a distant state; and acquiring the current noise floor value of the infrared distance sensor as the unobstructed noise floor value.

[0009] Optionally, adjusting the proximity threshold and the distance threshold based on the changing unobstructed noise floor value includes: superimposing the difference between the changing unobstructed noise floor value and the initial unobstructed noise floor value onto the values ​​of the proximity threshold and the distance threshold, respectively, to obtain the adjusted proximity threshold and distance threshold; or obtaining the difference between the proximity threshold and the distance threshold and the initial unobstructed noise floor value, respectively, as the proximity threshold difference value and the distance threshold difference value, and adding the changing unobstructed noise floor value to the proximity threshold difference value and the distance threshold difference value, respectively, to obtain the adjusted proximity threshold and distance threshold.

[0010] Optionally, the reference occlusion noise floor value includes the noise floor value measured when there is occlusion at a preset near distance and / or when there is occlusion at a preset far distance.

[0011] Optionally, the initial unobstructed noise floor value, the reference occlusion noise floor value, and / or the changing unobstructed noise floor value are obtained through a single detection, or through multiple detections and averaging.

[0012] According to a second aspect of the present disclosure, a computing device is provided, including: a processor; and a memory having executable code stored thereon, which, when executed by the processor, causes the processor to perform the method as described in any of the schemes in the first aspect above.

[0013] According to a third aspect of the present disclosure, a non-transitory machine-readable storage medium is provided, on which executable code is stored, which, when executed by a processor of an electronic device, causes the processor to perform the method described in any of the schemes in the first aspect above. Attached Figure Description

[0014] The above and other objects, features and advantages of this disclosure will become more apparent from the more detailed description of exemplary embodiments thereof taken in conjunction with the accompanying drawings, wherein like reference numerals generally denote like parts.

[0015] Figure 1 A schematic flowchart illustrating a method for calibrating an infrared distance sensor according to at least one embodiment of the present disclosure is shown as an example.

[0016] Figure 2 A schematic flowchart illustrating some steps of a method for calibrating an infrared distance sensor according to at least one embodiment of the present disclosure is shown as an example.

[0017] Figure 3 A schematic diagram of the structure of a computing device according to at least one embodiment of the present disclosure is shown as an example.

[0018] Figure 4 An illustrative application scenario of an infrared distance sensor is shown as an example.

[0019] Figure 5A An illustrative scenario is shown as an example of an anomaly caused by a decrease in the noise floor of an infrared distance sensor;

[0020] Figure 5B This example illustrates another illustrative scenario where reduced noise floor of an infrared distance sensor leads to anomalies;

[0021] Figure 6A An illustrative scenario is shown as an example of an anomaly caused by an increased noise floor in an infrared distance sensor;

[0022] Figure 6B Another illustrative scenario is shown, exemplarily illustrating how an increased noise floor in an infrared distance sensor can lead to anomalies. Detailed Implementation

[0023] Preferred embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0024] As mentioned earlier, infrared distance sensors offer numerous advantages. When operating, an infrared distance sensor emits infrared light and receives the reflected infrared light, obtaining a noise floor value. This noise floor value can be used to determine the presence or distance of obstructions. For example, infrared distance sensors are frequently installed in mobile phones to determine the distance to objects obstructing the phone screen. Figure 4 As shown, an infrared distance sensor can be installed on the front of the phone and preset proximity and distance settings can be implemented as described below in this disclosure. In one example, when a user is answering a call, if the infrared distance sensor detects that the distance A between the user (e.g., a face) and the screen is less than the proximity distance, the phone can automatically turn off the screen to avoid accidental touches caused by the face. Similarly, during a call or when the call ends, if the infrared distance sensor detects that the distance B between the user and the screen changes from less than the proximity distance (when the screen is off) to greater than the distance to the distance to the screen, the phone can automatically turn on the screen to provide a controllable display interface. The infrared distance sensor can be configured with proximity and distance thresholds accordingly, and the current proximity / distance state can be determined by comparing the currently measured noise floor value with the proximity / distance threshold.

[0025] However, this disclosure reveals that infrared distance sensors may malfunction or fail during use. For example, in current conventional solutions, the proximity and distance thresholds of infrared distance sensors are obtained only through a single calibration at the factory stage, which may lead to malfunctions or failures due to individual differences among infrared distance sensors. For instance, in traditional factory calibration schemes, a uniform proximity / distance threshold difference can be set based on the normal distribution of data from large batches of machines. The noise floor value of each infrared distance sensor under unobstructed conditions is calibrated, and then the proximity / distance threshold of each infrared distance sensor is set by superimposing the uniform proximity / distance threshold difference on its calibrated unobstructed noise floor value. However, this disclosure reveals that in some cases, machine consistency is poor, and the actual proximity / distance threshold difference of some infrared distance sensors may deviate from this uniform value. Therefore, the conventional solution may not achieve the desired effect for every machine, and may even lead to infrared function malfunctions or failures.

[0026] Furthermore, this disclosure reveals that the functionality of infrared distance sensors may be affected by temperature. For example, the characteristics of the integrated circuit (IC) in an infrared distance sensor may spontaneously compensate for rapid temperature changes, leading to jumps in the noise floor value; for instance, in some cases, a 3-degree Celsius change in a short period may cause a 1% jump in the noise floor. This phenomenon is even more pronounced in the increasingly popular under-display infrared solutions for mobile phones. Moreover, mobile phone circuit boards contain numerous and complex components, including some prone to heat generation (such as the CPU). Hardware layout often makes it difficult to keep the infrared distance sensor away from these heat-generating components, further exacerbating this phenomenon. It is also common for the mobile phone CPU temperature to reach 60 degrees Celsius when playing videos or mobile games. For example, as... Figure 5A , Figure 5B As shown, compared to the previous Figure 4 As shown in the diagram, a sudden increase in the temperature of the infrared distance sensor's IC or nearby components can lead to a decrease in the infrared distance sensor's noise floor. This reduced noise floor shortens the required approach / remote distance, potentially causing... Figure 5A The example describes an infrared distance sensor that detects the distance A between the user (e.g., a face) and the screen is less than a preset proximity distance, but the phone keeps the screen on because the actual required proximity distance is shorter; or it causes... Figure 5B In the example, the infrared distance sensor detects that the distance B between the user (e.g., a face) and the screen is not greater than the preset distance to move away. Similarly, because the actual required distance to move away is shorter, the phone screen lights up. All of these situations can cause the infrared function to malfunction or even fail. Figure 6A , Figure 6BAnother example illustrates a situation where a sudden temperature drop in the infrared distance sensor's IC or nearby devices causes an increase in the infrared distance sensor's noise floor, leading to sensor malfunction. Because the increased noise floor of the infrared distance sensor results in a longer actual approach / remote distance, see [reference needed]. Figure 6A The image shows a scenario where the infrared distance sensor detects that the distance A between the user (e.g., a face) and the screen has not yet reached the preset proximity distance, but because the actual required proximity distance is longer, the phone turns off the screen at this point; or refer to... Figure 6B As shown, the infrared distance sensor detects that the distance B between the user (e.g., a face) and the screen is greater than the preset distance to move away. Similarly, because the actual required distance to move away is longer, the phone remains screen-off, indicating an abnormal infrared function. In some cases, the increase in background noise is so large that it catches up with the proximity threshold set during calibration. For example, if the proximity threshold is 1500, the background noise increases from 1000 to 1500, causing the infrared distance sensor to continuously send proximity messages / notifications to the processor even when no user is nearby / obstructing the view, resulting in the phone remaining in a screen-off state, and the infrared function failing.

[0027] In view of this, this disclosure proposes an improved scheme that performs at least two initial calibrations on the infrared distance sensor, which can improve the consistency of the machine and enhance the accuracy of the infrared distance sensor. Furthermore, the scheme of this disclosure can also monitor changes in the unobstructed noise floor value of the infrared distance sensor and adjust the proximity / distance threshold in a timely manner, thereby compensating for the effects of temperature, etc., and further improving the accuracy of the infrared distance sensor.

[0028] The following describes exemplary schemes for calibrating infrared distance sensors, thereby clearly demonstrating the concept of this disclosure. It should be understood that this disclosure is not limited to these exemplary schemes, but is applicable to similar calibration processes for any infrared distance sensor, including those used independently or installed in various electronic devices.

[0029] Although some examples below describe infrared distance sensors installed in mobile phones or similar terminal devices, those skilled in the art will understand that the infrared distance sensors involved in the embodiments of this disclosure can be used alone or can be installed on any electronic device as needed.

[0030] Therefore, the method for calibrating an infrared distance sensor provided in this disclosure can be applied to terminal devices such as mobile phones, tablets, wearable devices, in-vehicle devices, augmented reality (AR) / virtual reality (VR) devices, laptops, ultra-mobile personal computers (UMPCs), netbooks, and personal digital assistants (PDAs). It can also be applied to other electronic devices that require ranging functions, such as security equipment or monitoring equipment, or other electronic devices equipped with touch screens. This disclosure does not limit the specific type of electronic device.

[0031] For example, the electronic device may be a cellular phone, cordless phone, Session Initiation Protocol (SIP) phone, Wireless Local Loop (WLL) station, Personal Digital Assistant (PDA) device, handheld device with wireless communication capabilities, computing device or other processing device connected to a wireless modem, computer, laptop computer, handheld communication device, handheld computing device, and / or other devices for communication over a wireless system, as well as next-generation communication systems, such as mobile terminals in 5G networks, mobile terminals in future evolved Public Land Mobile Networks (PLMNs), or mobile terminals in future evolved Non-terrestrial Networks (NTNs).

[0032] As an example and not a limitation, when the electronic device is a wearable device, it can also be a general term for devices that utilize wearable technology to intelligently design and develop everyday wearables, such as gloves and watches equipped with near-field communication modules. Wearable devices are portable devices worn directly on the body or integrated into a user's clothing or accessories. By attaching to the user and using a pre-bound electronic card, they perform operations such as payment and authentication. Wearable devices are not merely hardware devices; they achieve powerful functions through software support, data interaction, and cloud interaction. Broadly defined, wearable smart devices include those with comprehensive functions, large size, and the ability to perform complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those focused on a specific application function and requiring the use of other devices such as smartphones, such as various smartwatches and smart bracelets with displays.

[0033] Figure 1 A schematic flowchart illustrating a method for calibrating an infrared distance sensor according to at least one embodiment of the present disclosure is shown as an example.

[0034] like Figure 1 As shown, in step S110, the initial unobstructed noise floor value and the reference occlusion noise floor value of the infrared distance sensor are obtained, and the proximity threshold and distance threshold of the infrared distance sensor are determined based on the initial unobstructed noise floor value and / or the reference occlusion noise floor value.

[0035] In this document, "unobstructed noise floor value" refers to the noise floor value measured under unobstructed conditions. For example, it can be considered as the unobstructed noise floor value when there are no obstructions within 10 cm of the infrared distance sensor. In some cases, the noise floor value measured under unobstructed conditions within 30 cm of the infrared distance sensor can be used as the unobstructed noise floor value; however, this disclosure does not limit the distance of the unobstructed object. The "initial" unobstructed noise floor value in this step refers to the unobstructed noise floor value obtained before the calibration operation of approaching / moving away from the threshold in the subsequent step S120, which can be measured at various stages, such as the factory stage, before user use, or during use. Similarly, the reference obstructed noise floor value is also a noise floor value obtained before the subsequent calibration operation, which can be measured at the same or different stages as the initial unobstructed noise floor value. In some examples, the initial unobstructed noise floor value and the reference obstructed noise floor value can be detected for each infrared distance sensor at the factory stage.

[0036] In this paper, "reference occlusion noise floor value" refers to the noise floor value measured at a reference location where an obstruction exists. This reference location can be set as needed. The noise floor value can be measured separately by setting obstructions at one or more reference locations, and one or more reference occlusion noise floor values ​​can be obtained accordingly.

[0037] For example, in some implementations, the reference occlusion noise floor value may include the noise floor value measured when there is occlusion at a preset proximity distance and / or when there is occlusion at a preset distance away. The proximity distance and / or distance away can be preset according to the needs of the product to which the infrared distance sensor is applied. The noise floor value at the proximity / distance away distance can correspond to the proximity / distance away threshold, respectively. An obstruction is placed at the proximity distance and / or the distance away distance to obtain the reference occlusion noise floor value at that location, thereby determining the proximity threshold and distance threshold accordingly. For example, an obstruction can be placed at a preset proximity distance to measure the noise floor value. The measured reference obstruction noise floor value is determined as the proximity threshold, and the difference between the reference obstruction noise floor value and the initial unobstructed noise floor value is determined as the proximity threshold difference. The distance threshold difference is calculated based on, for example, a preset ratio between the distance and the proximity distance, and the distance threshold difference is added to the initial unobstructed noise floor value to obtain the distance threshold. The reference obstruction noise floor value in the aforementioned example can also be changed to be measured when there is an obstruction at a preset distance, and the proximity threshold and distance threshold can be determined similarly. For example, the approach distance can be preset to 3 cm, and the ratio of the difference between the distance threshold and the approach threshold can be 0.65. Assuming the initial unobstructed noise floor value is 1000, and the noise floor value is 1200 when there is a gray card (or other obstruction, which is not a limitation of this disclosure) at 3 cm, then 1200 can usually be used as the approach threshold, and the difference between the approach threshold and the distance threshold is 1200-1000=200. The difference between the distance threshold and the distance threshold is 200*0.65=130, and the distance threshold is 1000+130=1130. When the infrared distance sensor is working, when the currently measured noise floor value is lower than the distance threshold of 1130, it is defined as the distance state, and when it is higher than the approach threshold of 1200, it is defined as the approach state. The range of 1130 to 1200 is used as a buffer zone, and the previous state will be maintained within this range. In other examples, obstructions can be set at preset proximity and distances to measure the noise floor value separately. The two reference obstruction noise floor values ​​can then be determined as the proximity threshold and distance threshold, respectively.

[0038] In some implementations, the location of the obstruction, i.e., the reference location, is set when measuring the reference occlusion noise floor value. This location may not be either a preset approach distance or a distance from the obstruction. In this case, the approach threshold and distance threshold can be calculated from the reference occlusion noise floor value based on, for example, a preset conversion relationship.

[0039] In some implementations, the initial unobstructed noise floor value and / or the reference obstructed noise floor value can be obtained through a single detection or through multiple detections and averaging. For example, the infrared distance sensor can be measured multiple times at preset time intervals to obtain multiple noise floor values, which can then be averaged to obtain the final result, thus improving the accuracy of the measurement.

[0040] Compared to the traditional approach that only corrects the unobstructed noise floor value of each infrared distance sensor at the factory stage, the exemplary method disclosed herein can also perform additional corrections on the proximity threshold and / or distance threshold of each infrared distance sensor, that is, perform additional corrections on the proximity and / or distance variations of each machine, thereby improving the infrared experience caused by machine differences and reducing false alarm problems caused by consistency deviations between different machines.

[0041] Then, as Figure 1 As shown, in step S120, it is determined that the unobstructed noise floor value of the infrared distance sensor has changed and the change exceeds a threshold. The proximity threshold and the distance threshold are adjusted according to the changed unobstructed noise floor value.

[0042] As previously mentioned, this disclosure reveals that the functionality of infrared distance sensors can be affected by temperature. During use, changes in the temperature of the infrared distance sensor or the ambient temperature can lead to significant variations in the noise floor, causing abnormal or malfunctioning infrared functionality. While it's possible to improve the IC hardware design of the infrared distance sensor to reduce the impact of temperature changes, and / or optimize the hardware layout in products where the infrared distance sensor is used (e.g., mobile phones) to keep the sensor away from heat sources, this may increase hardware costs and / or restrict the hardware layout of products like mobile phones, which often have limited space and complex hardware layouts, making complete heat isolation difficult and potentially leading to uncontrollable risks. In contrast, the exemplary method of this disclosure primarily uses software to enhance the infrared distance sensor's resistance to temperature interference, saving costs and controlling risks. Furthermore, it offers greater freedom in hardware design, such as a higher tolerance for the placement of nearby heat-generating devices.

[0043] In some embodiments of this disclosure, a detection procedure for the unobstructed noise floor value can be initiated based on time and / or temperature conditions related to the infrared distance sensor, thereby tracking changes in the noise floor value and calibrating the near and far thresholds when it is determined that the noise floor value changes too much, to avoid infrared function malfunction or failure.

[0044] In some implementations, the detection program can be started periodically at a preset time interval. For example, an interrupt can be registered, and a corresponding polling time can be set, such as starting the detection program every 12 to 30 seconds. This time interval can be set according to power consumption and / or functional stability requirements. For example, a time interval can be preset based on usage experience, which can avoid excessive power consumption and functional abnormalities or failures caused by temperature. In some examples, data on the unobstructed noise floor value of the infrared distance sensor changing with one or more relevant temperatures can be collected, and the relationship between this temperature change and time can be established, thereby predicting the change in noise floor over time, and the time interval can be preset accordingly. In some examples, data on the unobstructed noise floor value of the infrared distance sensor changing over time can be collected, and a data model of the unobstructed noise floor value changing over time can be established, thereby the time interval can be preset according to this model.

[0045] In some embodiments, the detection procedure can be initiated when one or more temperatures associated with the infrared distance sensor are within a preset range. This temperature may include the infrared distance sensor's own temperature and / or the ambient temperature where the infrared distance sensor is located, and / or the temperature may include the temperature of the electronic device on which the infrared distance sensor is installed, the ambient temperature, and / or the temperature of its components. For example, the temperature may include the battery temperature, CPU temperature, and / or the ambient temperature measured by the electronic device (such as a mobile phone). In some embodiments, data on the unobstructed noise floor value of the infrared distance sensor as a function of temperature can be collected, and the preset range can be predetermined based on this data. For example, a model of the unobstructed noise floor value as a function of temperature can be established using the collected data. Based on this model, it can be determined that the change in the unobstructed noise floor value may exceed a threshold when the temperature enters one or more ranges, thereby enabling the detection procedure to be initiated for calibration when the temperature enters this or these ranges. For example, if a 10-degree Celsius change in the ambient temperature of the infrared distance sensor would result in a 3% change in the unobstructed noise floor value, and a 3% change could lead to abnormal or malfunctioning infrared functionality, then the detection program could be preset to start when the ambient temperature of the infrared distance sensor changes by more than 10 degrees Celsius relative to the initial measurement temperature (e.g., room temperature).

[0046] Furthermore, in some implementations, it can be determined first that the infrared distance sensor is in a distant state, and then the current noise floor value of the infrared distance sensor can be collected as the unobstructed noise floor value to determine whether the change in the unobstructed noise floor value exceeds a threshold. This avoids measuring the noise floor value when the sensor is close. This is because, as discovered in this disclosure, the change in noise floor value when close in real-world scenarios is usually much greater than the change caused by factors such as temperature. If the threshold is updated when close, it may cause the threshold to be extremely high for a short period, leading to misjudgment of the state. Additionally, the noise floor value collected here as the current unobstructed noise floor value can be obtained through a single detection or by averaging multiple detections.

[0047] In some embodiments, the change in the aforementioned unobstructed noise floor value can refer to the absolute value of the difference between the currently obtained unobstructed noise floor value and the initial unobstructed noise floor value obtained in the preceding step S110, or the proportion of the absolute value to the initial unobstructed noise floor value. The threshold for this change can be a preset value or a preset proportion. In some embodiments, the threshold can be preset based on usage experience, or data on the change of the unobstructed noise floor value of the infrared distance sensor with one or more temperatures can be collected, and the threshold can be predetermined based on this data.

[0048] After determining that the change exceeds the threshold, the proximity threshold and the distance threshold are adjusted based on the changed unobstructed noise floor value. The changed unobstructed noise floor value can be used instead of the initial unobstructed noise floor value to redetermine the proximity threshold and the distance threshold. For example, in some embodiments, the difference between the changed unobstructed noise floor value and the previously obtained initial unobstructed noise floor value can be added to the previous proximity threshold and distance threshold values ​​to obtain the adjusted proximity threshold and distance threshold. In some embodiments, the proximity threshold difference and distance threshold difference can be obtained, that is, the difference between the proximity threshold and distance threshold determined in step S110 and the initial unobstructed noise floor value, respectively, and the changed unobstructed noise floor value can be added to the proximity threshold difference and distance threshold difference respectively to obtain the adjusted proximity threshold and distance threshold.

[0049] Figure 2 A schematic flowchart illustrating at least one exemplary embodiment of step S120 described above is shown.

[0050] like Figure 2As shown, in step S210, the detection procedure for the unobstructed noise floor value can be initiated based on time and / or temperature conditions related to the infrared distance sensor, as described above. Then, in step S220, it is determined whether the infrared distance sensor is currently in a distant state. If yes, subsequent operations are performed; otherwise, the process can be terminated or a period of time can be waited before re-determining. Then, if the infrared distance sensor is determined to be in a distant state, step S230 is performed, where the current noise floor value of the infrared distance sensor is collected as the unobstructed noise floor value, and it is determined whether the change in the current unobstructed noise floor value relative to the initial unobstructed noise floor value exceeds a threshold. If yes, i.e., the change exceeds the threshold, step S240 is performed, where the proximity threshold and distance threshold are adjusted based on the current unobstructed noise floor value. Although not shown in the figure, it should be understood that the process can be terminated if the change does not exceed the threshold. The operations in each of the above steps can be combined with the aforementioned... Figure 1 The various implementation methods or examples described herein will not be elaborated upon here.

[0051] Figure 3 A schematic diagram of a computing device according to at least one embodiment of the present disclosure is shown, which can be used to implement the above-described method for calibrating an infrared distance sensor.

[0052] See Figure 3 The computing device 300 includes a memory 310 and a processor 320.

[0053] Processor 320 may be a multi-core processor or may contain multiple processors. In some embodiments, processor 320 may include a general-purpose main processor and one or more special-purpose coprocessors, such as a graphics processing unit (GPU), a digital signal processor (DSP), etc. In some embodiments, processor 320 may be implemented using custom circuitry, such as an application-specific integrated circuit (ASIC) or a field-programmable gate array (FPGA).

[0054] Memory 310 may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage devices. ROM may store static data or instructions required by processor 320 or other modules of the computer. Permanent storage devices may be read-write storage devices. Permanent storage devices may be non-volatile storage devices that retain stored instructions and data even when the computer is powered off. In some embodiments, permanent storage devices use mass storage devices (e.g., magnetic or optical disks, flash memory) as permanent storage devices. In other embodiments, permanent storage devices may be removable storage devices (e.g., floppy disks, optical drives). System memory may be a read-write storage device or a volatile read-write storage device, such as dynamic random access memory. System memory may store some or all of the instructions and data required by the processor during operation. Furthermore, memory 310 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks may also be used. In some embodiments, memory 310 may include a removable storage device that is readable and / or writable, such as a laser disc (CD), a read-only digital multifunction optical disc (e.g., DVD-ROM, dual-layer DVD-ROM), a read-only Blu-ray disc, an ultra-high density optical disc, a flash memory card (e.g., SD card, mini SD card, Micro-SD card, etc.), a magnetic floppy disk, etc. Computer-readable storage media do not contain carrier waves or transient electronic signals transmitted wirelessly or via wired connections.

[0055] The memory 310 stores executable code, which, when processed by the processor 320, enables the processor 320 to execute the method for calibrating the infrared distance sensor described above.

[0056] Furthermore, the method according to this disclosure can also be implemented as a computer program or computer program product, which includes computer program code instructions for performing the steps defined in the above-described method of this disclosure.

[0057] Alternatively, this disclosure may be implemented as a non-transitory machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium) storing executable code (or computer program, or computer instruction code) that, when executed by a processor of an electronic device (or computing device, server, etc.), causes the processor to perform the steps of the method described above according to this disclosure.

[0058] Those skilled in the art will also understand that the various exemplary logic blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein can be implemented as electronic hardware, computer software, or a combination of both.

[0059] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems and methods according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0060] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for calibrating an infrared distance sensor, comprising: Obtain the initial unobstructed noise floor value and the reference obstructed noise floor value of the infrared distance sensor, and determine the proximity threshold and distance threshold of the infrared distance sensor based on the initial unobstructed noise floor value and / or the reference obstructed noise floor value; as well as If the unobstructed noise floor value of the infrared distance sensor changes and the change exceeds a threshold, the proximity threshold and the distance threshold are adjusted based on the changed unobstructed noise floor value. The adjustment of the proximity threshold and the distance threshold based on the changing unobstructed noise floor value includes: The difference between the changed unobstructed noise floor value and the initial unobstructed noise floor value is superimposed on the values ​​of the near threshold and the far threshold, respectively, to obtain the adjusted near threshold and far threshold; or The differences between the proximity threshold and the distance threshold and the initial unobstructed noise floor value are obtained as the proximity threshold difference and the distance threshold difference, respectively. The changed unobstructed noise floor value is added to the proximity threshold difference and the distance threshold difference to obtain the adjusted proximity threshold and distance threshold.

2. The method according to claim 1, wherein, Determining that the unobstructed noise floor value of the infrared distance sensor changes includes: The procedure for detecting the unobstructed noise floor value is initiated based on the time and / or the temperature conditions related to the infrared distance sensor.

3. The method according to claim 2, wherein, The detection procedure is initiated based on time and / or temperature conditions related to the infrared distance sensor, including: The detection program is started at preset time intervals; and / or When the temperature is within a preset range, the detection program is started, wherein the temperature includes the temperature of the infrared distance sensor itself, and / or the ambient temperature of the infrared distance sensor, and / or the temperature of the electronic device on which the infrared distance sensor is installed, the ambient temperature, and / or the temperature of its components.

4. The method according to claim 3, further comprising: Collect data on the change of the unobstructed noise floor value of the infrared distance sensor with the temperature; as well as The time period, the range, and / or the threshold are determined in advance based on the data.

5. The method according to claim 1, wherein, Determining that the unobstructed noise floor value of the infrared distance sensor changes includes: Determine that the infrared distance sensor is in a remote state; and The current noise floor value of the infrared distance sensor is collected as the unobstructed noise floor value.

6. The method according to claim 1, wherein, The reference occlusion noise floor value includes the noise floor value measured when there is occlusion at a preset close distance and / or when there is occlusion at a preset far distance.

7. The method according to claim 1, wherein, The initial unobstructed noise floor value, the reference occlusion noise floor value, and / or the changed unobstructed noise floor value are obtained through a single detection or through multiple detections and averaging.

8. A computing device, comprising: processor; as well as A memory having executable code stored thereon, which, when executed by the processor, causes the processor to perform the method as described in any one of claims 1-7.

9. A non-transitory machine-readable storage medium having executable code stored thereon, which, when executed by a processor of an electronic device, causes the processor to perform the method as described in any one of claims 1-7.

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