Visible light positioning device and method resistant to ambient light interference

Abstract

The application provides an anti-environmental light interference visible light positioning device and method, comprising a calibration stage and a positioning stage. In the calibration stage, the position of an LED lamp is measured in advance, and the ratio parameter of the LED is calibrated at the known position. In the positioning stage, the ratio parameter calibrated in advance is used to calculate the distance ratio between different LED lamps, and the position of the PD is determined according to the distance ratio. The application controls the variable analysis in different states, and obtains the relationship curve between the normalized RSS value and the environmental light intensity, which does not change with the inclination angle of the PD, the LED lamp, the frequency of the LDE lamp, the height of the PD, and the distance between the PD and the LED. Then, a method based on the distance ratio between the PD and different LED lamps is proposed to effectively suppress the influence of the uneven distribution of environmental light in the time domain on the visible light positioning. In addition, the relationship between the distance ratio and the RSS ratio is directly modeled using the ratio parameter to eliminate the influence of the uneven spatial distribution of environmental light on the calibration of the visible light positioning system.

Description

Technical Field

[0001] This invention relates to the field of image generation technology, specifically to a visible light positioning technology solution that resists ambient light interference. Background Technology

[0002] In recent years, with the development of IoT technology, positioning and navigation technologies have played an increasingly important role in people's lives. With the completion of the BeiDou Navigation Satellite System, it can achieve decimeter-level positioning accuracy in open outdoor environments. However, in challenging environments such as urban canyons and underground spaces, satellite signals are easily blocked by obstacles such as buildings and ceilings, severely degrading positioning accuracy and even making it impossible to obtain a positioning solution. Therefore, various indoor positioning methods have emerged, including Wi-Fi, Bluetooth, UWB, sound, and vision. Among these, visible light positioning has become a popular solution for indoor positioning due to its high accuracy, low energy consumption, and environmental friendliness. However, it is easily affected by ambient light. Current visible light positioning systems mainly rely on curtains or projecting the RSS (Radio Sensitive Level) onto the calibration scene to eliminate the influence of ambient light. Curtains cannot be applied to actual shopping malls and train stations; while projection requires significant manpower to collect RSS values ​​under different ambient light conditions and cannot effectively suppress the impact of uneven spatial distribution of ambient light on the Lambertian parameter calibration.

[0003] Visible light positioning has enormous application potential due to its advantages such as strong resistance to electromagnetic interference, low cost, low power consumption, and environmental friendliness. Existing visible light positioning systems mainly distinguish different LEDs and their positions by frequency modulation of LEDs, and can be divided into two schemes: PD-based and camera-based. Camera-based schemes utilize the roller shutter effect to distinguish different LEDs and then estimate the camera pose through camera extrinsic parameter calibration. RSS-based indoor visible light positioning schemes, on the other hand, involve the PD receiving raw observations, extracting the light intensity values ​​of different LEDs using FFT, then converting the light intensity values ​​into the distance from the PD to each LED using a Lambertian model, and finally estimating the PD's position using trilateration. PD-based positioning schemes are more popular due to their lower cost and ease of implementation. However, PD-based visible light positioning systems are susceptible to interference from ambient light sources, including both artificial and natural light sources. Existing solutions sometimes eliminate ambient light interference by blocking it with cloth, but this approach is difficult to apply in real-world scenarios. Another method involves a two-step adjustment approach that maps the RSS (Rapid Subtraction Standard) to the calibration scene before repositioning. This method requires collecting RSS values ​​for all ambient light intensities, making it time-consuming and inaccurate. Furthermore, it fails to eliminate the damage to Lambertian parameter calibration caused by uneven spatial distribution of ambient light. Therefore, a robust visible light positioning solution that effectively resists ambient light interference has significant application value.

[0004] Related terms:

[0005] VLP (Visible Light Positioning)

[0006] LM (Levenberg-Marquarat) algorithm

[0007] PD (Photo Diode)

[0008] LED (Light-emitting Diode)

[0009] PWM (Pulse Width Modulation)

[0010] RSS (Received Signal Strength)

[0011] FOV (Field of View), Time of Flight

[0012] FFT (Fast Fourier Transform) Summary of the Invention

[0013] To address the shortcomings of the existing technology, this invention proposes a visible light positioning scheme that resists ambient light interference.

[0014] To achieve the above objectives, this invention proposes a visible light positioning method that resists ambient light interference, comprising a calibration stage and a positioning stage. In the calibration stage, the position of the LED is measured in advance, and the ratio parameter of the LED is calibrated at the known position. In the positioning stage, the ratio of the distance between the PD and different LEDs is calculated using the pre-calibrated ratio parameter, and the position of the PD is determined based on the distance ratio.

[0015] Furthermore, during the calibration phase, the light intensity RSS value and the current position coordinates are recorded at different locations, and the distance information between the PD and different LDE lamps is calculated. The calibration ratio parameter A is then calibrated using the following formula. Li and B Li ,

[0016]

[0017] Where n is the number of calibration points, j is used to identify the j-th calibration point, and i is used to identify the i-th LED. This represents the value of the i-th LED at the j-th calibration point. It is the distance from the PD to the i-th LED at the j-th calibration point.

[0018] Furthermore, the positioning phase is implemented by including the following sub-steps:

[0019] Step 2.1, extract and measure the coordinate position of the LED light.

[0020] Step 2.2: Collect RSS values ​​during the positioning process;

[0021] Step 2.3: Calculate the distance between the PD and different LED lights according to the following formula, thus eliminating the influence of ambient light in this process;

[0022]

[0023] Where, d Li b represents the distance between the PD and the i-th LED. Li and a Li Then, it represents the Lambertian parameter of the i-th LED and the ratio parameter of the i-th LED. B i =b L1 ;

[0024] Step 2.4: Using the ratios between the distances from the PD to different LEDs obtained above, estimate the position of the PD according to the following formula.

[0025]

[0026] Where N represents the number of LEDs sensed by the PD, and d i α represents the distance from the PD to the i-th LED. i (x,y) represents the ratio between the distance from the i-th lamp to the PD and the distance from the first lamp to the PD, and (x,y) represents the position of the PD. i ,y i ) represents the position of the i-th lamp.

[0027] Furthermore, the location of PD is finally obtained through optimization calculation using the LM algorithm.

[0028] On the other hand, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the visible light positioning method against ambient light interference as described above.

[0029] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the visible light positioning method against ambient light interference as described above.

[0030] On the other hand, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the visible light positioning method against ambient light interference as described above.

[0031] The present invention proposes the following improvements:

[0032] 1) By modeling the ratio between the distances from the PD to different LED lights, the influence of uneven temporal distribution of ambient light on positioning in the visible light system can be effectively suppressed;

[0033] 2) The relationship between the distance ratio and the corresponding different RSS ratios is directly modeled through the ratio parameter to suppress the influence of uneven spatial distribution of ambient light on parameter calibration in visible light systems;

[0034] The advantages and effects of this invention are as follows:

[0035] 1) Compared with traditional ambient light suppression schemes, this algorithm does not require additional equipment or prior data collection to establish an RSS variation model with ambient light intensity. It can provide real-time visible light positioning results and effectively suppress the impact of unevenly distributed ambient light in the time domain on positioning.

[0036] 2) In addition, this invention directly models the ratio relationship between the distance ratio between the PD and different LEDs and its corresponding RSS ratio by using ratio parameters, which can effectively suppress the influence of unevenly distributed ambient light on parameter calibration.

[0037] The present invention is simple and convenient to implement, highly practical, and solves the problems of low practicality and inconvenience in actual application of related technologies. It can improve user experience and has significant market value. Attached Figure Description

[0038] Figure 1 This is a system overall structure diagram according to an embodiment of the present invention.

[0039] Figure 2 This is a schematic diagram of RSS calibration results under different ambient light conditions according to an embodiment of the present invention. Part (a) shows the calibration of Lambertian parameters under pure positioning light, part (b) shows the calibration of Lambertian parameters under artificial light interference, and part (c) shows the calibration of Lambertian parameters under natural light interference.

[0040] Figure 3 This is a schematic diagram of the positioning effect of parameter calibration in different scenarios without ambient light according to an embodiment of the present invention, wherein (a) is the positioning scenario without ambient light and (b) is the positioning scenario with ambient light.

[0041] Figure 4 This is a schematic diagram illustrating the positioning effect of parameter calibration in different scenes with ambient light according to an embodiment of the present invention, wherein (a) is the positioning scene without ambient light, and (b) is the positioning scene with ambient light.

[0042] Figure 5 This diagram illustrates the effect of uneven spatial distribution of ambient light on the Lambertian parameters in an embodiment of the present invention.

[0043] Figure 6 This is a diagram showing the effect of ambient light changes on RSS, representing a fixed distance between a PD and an LED light in an embodiment of the present invention.

[0044] Figure 7 This is a graph showing the relationship between normalized RSS and ambient light intensity under different conditions, using controlled variables, as an embodiment of the present invention. Detailed Implementation

[0045] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0046] This invention analyzes the relationship between normalized RSS values ​​and ambient light intensity under different conditions by controlling variables. It finds that this relationship remains unchanged regardless of the tilt angle of the PD, the frequency of the LEDs and LEDs, the height of the PD, or the distance between the PD and the LEDs. Then, it proposes a method based on the distance ratio between the PD and different LEDs to effectively suppress the impact of uneven ambient light distribution in the time domain on visible light positioning. Furthermore, it proposes using a ratio parameter to directly model the relationship between the distance ratio and the RSS ratio to eliminate the influence of uneven spatial distribution of ambient light on the calibration of the visible light positioning system. Based on these two methods, the influence of ambient light on the visible light positioning system can be effectively and comprehensively suppressed.

[0047] This invention proposes a ratio-based visible light positioning framework to suppress the influence of ambient light. Its advantages over the traditional trilateration framework in terms of data processing are shown in the appendix. Figure 1 As shown, traditional VLP systems use frequency division multiplexing (FDM) to modulate LEDs in different frequency domains. When the PD receives the time-series light intensity signal, it projects it into the frequency domain using FFT, and then extracts the RSS values ​​of different LEDs based on their frequencies. Next, the Lambertian model calculates the distance from different LEDs to the PD, and the PD's position is estimated using trilateration. However, traditional methods are easily affected by ambient light interference. The ratio-based VLP system proposed in this invention also extracts the LED's RSS value using FFT, but it then calculates the distance ratio from the PD to different LEDs using a proposed new ratio parameter. Finally, it solves for the PD's location using an optimized scheme. The proposed ratio-based VLP system can effectively suppress the influence of spatiotemporally changing ambient light on the VLP system.

[0048] Part A: Ambient Light Characteristics

[0049] Step 1: The mechanism by which ambient light affects the positioning of visible light systems. This is illustrated by the Lambertian model of light intensity decay over time.

[0050]

[0051] Where: P i P represents the power received by the PD from the i-th LED. Ti d represents the emission power of the i-th LED. i Let A be the 3D distance between the i-th LED and the PD receiver, whose square is inversely proportional to the channel gain; R θ is the effective photoelectric sensing area of ​​the PD receiver; θ is the radiation angle of the visible light signal emitted from the LED base station, representing the angle between the LED normal direction and the visible light signal emission direction; ψ is the incident angle of the visible light signal received by the PD receiver, representing the angle between the PD normal direction and the visible light signal incident direction; T s (Ψ) is the optical filter gain; g(Ψ) is the optical concentrator gain; m i Let be the order of the Lambertian radiation model for the i-th LED. M represents the Lambertian order of the PD, which is determined solely by the PD's hardware. It can be observed that the Lambertian formula does not describe the light intensity P. i The relationship between ambient light and RSS is discussed, but in real-world testing, ambient light intensity has a significant impact on RSS. (See attached image.) Figure 2 As shown, the calibration data collected under different ambient light conditions, after calibration, all exhibited very small residuals, indicating that they conformed to the Lambert model. Figure 3 As shown, when the Lambertian parameters are calibrated in the absence of ambient light, a high positioning accuracy can be achieved if the positioning scene is also in the absence of ambient light; however, if the positioning scene has ambient light, the positioning accuracy drops rapidly. Similarly, see the attached diagram. Figure 4 As shown, when calibrating the Lambertian parameters under ambient light interference, high positioning accuracy can be achieved in positioning scenarios with the same ambient light interference; however, in scenarios where ambient light is blocked, positioning accuracy drops rapidly. Therefore, this invention concludes that when the ambient light intensity of the positioning scenario is the same as that of the calibration scenario, the influence of ambient light is minimal; however, when the ambient light intensities of the two scenarios differ, positioning accuracy drops significantly. In most real-world scenarios, the intensity of ambient light frequently changes over time due to weather, environment, and other factors, which can cause significant errors in visible light positioning, i.e., errors caused by the uneven distribution of ambient light in the time domain. Therefore, suppressing the influence of ambient light is crucial for visible light positioning systems.

[0052] Step 2: The mechanism by which ambient light affects the calibration of visible light system parameters. (See attached document) Figure 5 As shown, the uneven distribution of ambient light in space affects the Lambert curve, disrupts the Lambert parameter calibration, and consequently affects the subsequent positioning accuracy.

[0053] Step 3: Collect visible light RSS data under different conditions by controlling variables. Specifically, collect the RSS values ​​as a function of ambient light under different PD tilt angles, different LED lights, different LED frequencies, different PD heights, and different distances between the PD and the LEDs. The ambient light intensity is defined as the average of the raw values ​​received by the PD.

[0054] Step 4: Define the normalized RSS value. (See attached image) Figure 6 As shown, while keeping the distance between the PD and LED constant, the RSS varies with ambient light, divided into saturated and unsaturated stages. In the unsaturated stage (i.e., RSS < threshold t), the RSS value increases with increasing ambient light; in the saturated stage (i.e., RSS > threshold t), the RSS does not increase with increasing ambient light but remains relatively stable. Here, t is obtained from the measured normalized RSS and ambient light relationship curve, representing the ambient intensity value when the normalized RSS does not change with ambient light. Figure 6 As shown. Therefore, the normalized RSS is defined as follows:

[0055]

[0056] Where RSS0 is the signal strength value when the PD is saturated, and RSS represents the optical signal strength under arbitrary light intensity conditions. Then K is the normalized RSS value.

[0057] Step 5: Analyze the relationship between normalized RSS values ​​and ambient light intensity under different PD tilt angles, different LED lights, different LED frequencies, different PD heights, and different distances between PDs and LEDs. See attached diagram for details. Figure 7 As shown in the figure, the relationship curves between the normalized RSS value and the ambient light intensity are extremely similar under different PD tilt angles, different LED lights, different LED frequencies, different PD heights, and different distances between the PD and the LEDs. Therefore, this invention concludes that the RSS received by all LED lights from the same PD is similarly affected by the ambient light intensity.

[0058] Part B: Ambient Light Noise Elimination

[0059] Step 1: Simplify the Lambertian model. At the user end, the intensity of the visible light signal received by the PD is related to the user's position in the positioning space, and the received intensity of the visible light signal is related to the optical channel gain from the LED base station to the location of the receiving PD. To more clearly analyze the relationship between the optical channel gain and the location information of the receiving PD, this invention simplifies the optical channel gain model. Specifically, it is assumed that when both the LED and the PD are placed horizontally, the incident angle and the radiation angle are equal. The cosine function of the incident angle satisfies the following formula:

[0060]

[0061] Furthermore, without a lens, both functions Ts(ψ) and g(ψ) are 1. Therefore, the Lambert formula can be simplified to...

[0062]

[0063] In this embodiment of the invention, the Lambertian coefficient of each lamp and A R P Ti Both are denoted as constants, where A R P represents the photosensitive area of ​​the PD. Ti This represents the emission power of the i-th LED. Then we can remember...

[0064]

[0065] b = -(m i +M+2) (6)

[0066] Where h represents the vertical distance between the LED and the PD, the final model can be simplified to:

[0067] RSS = a·d b (7)

[0068] Only two parameters, a and b, need to be calibrated.

[0069] Step 2: Eliminate the influence of ambient light during positioning. Assume there are five LED positioning lights in the system. In this embodiment, a Lambertian model was calibrated under ambient light saturation conditions: Lambertian model (aL1, bL1) for LED1, (aL2, bL2) for LED2, (aL3, bL3) for LED3, (aL4, bL4) for LED4, and (aL5, bL5) for LED5. During real-time positioning, the ambient light intensity can be saturated or unsaturated, and the LED light intensity collected by the PD is the RSS. According to formula (2), the embodiment can project the RSS from the positioning stage onto the RSS value under ambient light saturation conditions in the calibration scene, and then use the Lambertian parameters obtained under ambient light saturation conditions to convert the RSS into a relevant distance. The conversion formula is shown below.

[0070]

[0071] Where d Li This represents the distance between the PD and the i-th LED. (b) Li and a Li Then represents the Lambertian parameter of the i-th LED, RSS. Li K represents the signal strength received by the PD from the i-th LED. LiThis indicates the currently received RSS. Li This is converted to the coefficient corresponding to the saturation state. However, in actual positioning, K... Li Since ambient light is difficult to obtain, this invention eliminates its influence through a ratio method. The specific formula is shown below.

[0072]

[0073] Once the expression for the distance between the PD and different LEDs is obtained through projection, the distances between the PD and different LEDs can be compared. Then, formula (9) can be decomposed into formulas 10 and 11 as follows.

[0074]

[0075]

[0076] Equation 10 is determined by the Lambert parameter; while Equation 11 is determined by the ambient light intensity. Furthermore, as shown in Part A analysis, since all LEDs share the same PD in the same VLP system, the impact of ambient light on all LEDs is the same. Therefore, K can be obtained. L1 ≈K Li Similarly, the Lambertian parameter b is determined by the chip in the PD and LED light; ambient light does not affect this parameter. Furthermore, in the same VLP system, all LED lights are essentially of the same type. Therefore, assuming b... L1 =b Li It does not introduce additional errors. Ultimately, we can obtain Formula 12, which eliminates the influence of ambient light noise by using the ratio between different distances, without needing to know the parameter K. Li Specific numerical values.

[0077]

[0078] Finally, the formula after eliminating the influence of ambient light is as follows: Formula 13

[0079]

[0080] Step 3: Eliminating Environmental Influences During Calibration. As mentioned in Part A, the influence of ambient light on VLP systems includes the impact of uneven temporal distribution on positioning and the impact of uneven spatial distribution on Lambertian parameters. Although the influence of ambient light during positioning can be eliminated by using a ratio method as shown in Equation 13, the uneven spatial distribution of ambient light will still seriously affect the calibration process of Lambertian parameters, thereby affecting subsequent positioning accuracy. Therefore, in order to eliminate the influence of the environment during calibration, Equation 13 is further simplified as follows:

[0081]

[0082] To further simplify,

[0083]

[0084] in: B i =b L1 In this embodiment, the ratio parameter of the i-th LED is referred to as the ratio parameter. Therefore, Formula 15 can effectively eliminate the influence of ambient light on the uneven distribution of ambient light during the Lambertian parameter calibration process.

[0085] Step 4: Calibration of the ratio parameter. Collect the RSS of different LEDs at known locations and calibrate the ratio parameter using the following method.

[0086]

[0087] Where n is the number of calibration points, j is used to identify the j-th calibration point, and i is used to identify the i-th LED. This represents the value of the i-th LED at the j-th calibration point. It is the distance from the PD to the i-th LED at the j-th calibration point. That is, This represents the value of the first LED at the j-th calibration point. It is the distance from the PD to the first LED at the j-th calibration point.

[0088] Step 5: Real-time VLP system resistant to ambient light interference. Since the position and ratio parameters of the calibrated LEDs have been extracted, the distance ratios between the PD and different LEDs are obtained using Formula 15. Then, the pose is calculated using the LM optimization algorithm. Details are shown below.

[0089]

[0090] Where d i Let represent the distance from PD to the i-th LED. Formula (17) can be further simplified to:

[0091]

[0092] Where N represents the number of LEDs sensed by the PD, and assuming the first LED is set as the reference, then α i (x,y) represents the ratio between the distance from the i-th lamp to the PD and the distance from the first lamp to the PD, and (x,y) represents the position of the PD. i ,y i ) represents the position of the i-th lamp. Formula 18 can be calculated using an optimization algorithm (such as the preferred LM algorithm) to finally obtain the position of PD.

[0093] The embodiment provides a visible light positioning method to resist ambient light interference. Based on the above process, it can be briefly summarized as follows: it includes a calibration stage and a positioning stage. In the calibration stage, the position of the LED is measured in advance, and the ratio parameter of the LED is calibrated at the known position. In the positioning stage, the ratio of the distance between the PD and different LEDs is calculated using the pre-calibrated ratio parameter, and the position of the PD is determined according to the distance ratio.

[0094] During the calibration phase, the light intensity RSS value and the current position coordinates are recorded at different locations, and the distance information between the PD and different LDE lamps is calculated. The calibration ratio parameter A is then determined according to Formula 16. Li and B Li .

[0095] The location phase is implemented by the following sub-steps:

[0096] Step 2.1, extract and measure the coordinate position of the LED light.

[0097] Step 2.2: Collect RSS values ​​during the positioning process;

[0098] Step 2.3: Calculate the distance between the PD and different LED lights according to Formula 15, thus eliminating the influence of ambient light in this process;

[0099] Step 2.4: Using the ratio between the distances of the PD to different LEDs obtained above, estimate the position of the PD according to Formula 18.

[0100] In specific implementation, the method proposed in the technical solution of this invention can be automatically executed by those skilled in the art using computer software technology. System devices for implementing the method, such as computer-readable storage media storing the corresponding computer program of the technical solution of this invention and computer equipment including the computer program running the corresponding computer program, should also be within the protection scope of this invention.

[0101] In some possible embodiments, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the visible light positioning method with resistance to ambient light interference as described above.

[0102] In some possible embodiments, a non-transitory computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the visible light positioning method resistant to ambient light interference as described above.

[0103] In some possible embodiments, a computer program product is provided, including a computer program that, when executed by a processor, implements the visible light positioning method resistant to ambient light interference as described above.

[0104] The specific embodiments described herein are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to substitute them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

Claims

1. A visible light positioning method resistant to ambient light interference, characterized in that: It includes a calibration stage and a positioning stage. In the calibration stage, the position of the LED is measured in advance, and the ratio parameter of the LED is calibrated at the known position. In the positioning stage, the ratio of the distance between the PD and different LEDs is calculated using the pre-calibrated ratio parameter, and the position of the PD is determined based on the distance ratio. During the calibration phase, the light intensity RSS value and the current position coordinates are recorded at different locations, and the distance information between the PD and different LEDs is calculated. The calibration ratio parameter is then determined using the following formula. A Li and B Li , in, n It is the number of calibration points. j Used to identify the first j One calibration point, i Used to identify the first i One LED light Indicates the first i The LED light is in the first j The value at each calibration point It is PD to the number i The first LED light in the... j The distance between each calibration point; The location phase is implemented by the following sub-steps: Step 2.1, extract and measure the coordinate position of the LED light. Step 2.2: Collect RSS values ​​during the positioning process; Step 2.3: Calculate the distance between the PD and different LED lights according to the following formula, thus eliminating the influence of ambient light in this process; in, d Li This represents the distance between the PD and the i-th LED. b Li and a Li Then, it represents the Lambertian parameter of the i-th LED and the ratio parameter of the i-th LED. A i = , B i = ; Step 2.4: Using the ratios between the distances from the PD to different LEDs obtained above, estimate the position of the PD according to the following formula. Where N represents the number of LEDs sensed by the PD. d i This represents the distance from the PD to the i-th LED. Indicates the first i The ratio between the distance from the first lamp to the PD and the distance from the first lamp to the PD, where (x, y) represents the position of the PD. i , y i ) indicates the first i The location of the lamp.

2. The visible light positioning method for resisting ambient light interference according to claim 1, characterized in that: The location of PD is finally obtained by optimizing the calculation through the LM algorithm.

3. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the visible light positioning method against ambient light interference as described in any one of claims 1 to 2.

4. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the visible light positioning method against ambient light interference as described in any one of claims 1 to 2.

5. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the visible light positioning method against ambient light interference as described in any one of claims 1 to 2.

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