Intelligent control method and system for infrared LED and VCSEL laser fusion light source

Abstract

The invention relates to an intelligent control method and system for an infrared LED and VCSEL laser fusion light source, and the method comprises the following steps: carrying out the multiband light intensity collection of a target scene through a multiband photoelectric detector, and obtaining a scene light intensity feature matrix; performing regional light intensity quantification processing on the scene light intensity feature matrix based on a scene grade divider to obtain scene illumination grade parameters; performing power ratio calculation on infrared LED and VCSEL laser based on the scene illumination level parameters to obtain a dual-light-source driving waveform sequence; and carrying out current modulation output on the dual-light-source driving waveform sequence based on a dual-path driving circuit to obtain a fused light source illumination effect, thereby solving the technical problem of how to accurately obtain and utilize scene light intensity characteristics to guide intelligent regulation and control of the light source.

Description

Technical Field

[0001] The present invention relates to the field of LED and VCSEL laser technology, and in particular to an intelligent control method and system for a fusion light source of infrared LED and VCSEL laser. Background Art

[0002] In the current field of lighting and sensing technology, it is particularly important to develop an intelligent control method that can integrate the characteristics of infrared LEDs and VCSEL lasers. This method not only requires the efficient collaboration of the two light sources, but also the ability to adapt to complex environmental lighting conditions. However, there is still relatively little research in this area. In particular, there are still many technical obstacles in how to accurately obtain and utilize scene light intensity characteristics to guide the intelligent control of light sources. This includes how to design efficient photodetectors to collect multi-band light intensity information, and how to build reasonable algorithm models to process this data and generate effective light source driving solutions. The existence of these problems limits the development of existing technologies in a more efficient and intelligent direction. Summary of the Invention

[0003] The main purpose of the present invention is to provide an intelligent control method and system for an infrared LED and VCSEL laser fusion light source, which solves the technical problem of how to accurately obtain and utilize scene light intensity characteristics to guide the intelligent regulation of the light source.

[0004] To achieve the above objectives, the present invention provides an intelligent control method for an infrared LED and VCSEL laser fusion light source, comprising the following steps: The multi-band light intensity of the target scene is collected by a multi-band photoelectric detector to obtain the scene light intensity feature matrix; Based on the scene level divider, the scene light intensity feature matrix is ​​quantitatively processed into regional light intensity to obtain scene light level parameters; Calculating the power ratio of the infrared LED and the VCSEL laser based on the scene light level parameter to obtain a dual-light source driving waveform sequence; The dual-light source driving waveform sequence is current-modulated and output based on a dual-path driving circuit to obtain a fusion light source lighting effect.

[0005] Furthermore, the multi-band light intensity of the target scene is collected by a multi-band photoelectric detector to obtain a scene light intensity feature matrix, including: Performing spectral segment sampling of a target scene through a multi-band photoelectric detector to obtain an original spectral data stream, and performing wavelength calibration processing on the original spectral data stream to obtain a spectral response curve; Performing signal gain compensation on the spectral response curve to obtain a gain compensation data group, and performing dark current elimination processing on the gain compensation data group to obtain a photoelectric conversion characteristic curve; Performing light intensity analysis on the target scene based on the photoelectric conversion characteristic curve to obtain a spatial light intensity distribution diagram, and performing light intensity uniformity correction on the spatial light intensity distribution diagram to obtain a corrected light intensity matrix; Multi-band feature extraction is performed on the corrected light intensity matrix to obtain a band feature vector group, and light intensity feature synthesis is performed on the band feature vector group to obtain a scene light intensity feature matrix.

[0006] Furthermore, the scene level divider performs regional light intensity quantification processing on the scene light intensity feature matrix to obtain scene light level parameters, including: Performing regional segmentation and calibration on the scene light intensity feature matrix to obtain a scene region division map, and performing light intensity threshold layering on the scene region division map to obtain a regional light intensity hierarchy table; Performing spatial gradient calculation on the regional light intensity hierarchy table using a preset light intensity gradient method to obtain a light intensity change rate matrix, and performing boundary feature extraction on the light intensity change rate matrix to obtain a regional light intensity distribution feature map; Performing regional illumination equalization processing on the regional light intensity distribution characteristic map to obtain an illumination compensation parameter group, and performing dynamic range mapping on the illumination compensation parameter group to obtain a regional illumination distribution map; The regional illumination distribution map is subjected to illumination level quantification to obtain a regional light intensity quantitative parameter group, and the regional light intensity quantitative parameter group is subjected to parameter integration processing to obtain a scene illumination level parameter.

[0007] Furthermore, the power ratio calculation of the infrared LED and the VCSEL laser is performed based on the scene light level parameter to obtain a dual-light source driving waveform sequence, including: Performing light source ratio mapping on the infrared LED and the VCSEL laser based on the scene light level parameter to obtain a light source power distribution ratio table, and performing operating point calculation on the light source power distribution ratio table to obtain a dual-light source reference parameter group; Dividing the dual-light source reference parameter group into PWM cycles to obtain a reference PWM timing table, and performing pulse stretching calculation on the reference PWM timing table to obtain a pulse modulation sequence; Performing a dual-light source synchronous trigger design based on the pulse modulation sequence to obtain a trigger timing spectrum, and performing phase compensation calculation on the trigger timing spectrum to obtain phase compensation data; Performing waveform shaping processing on the phase compensation data to obtain a driving waveform data group, and performing harmonic distortion analysis on the driving waveform data group to obtain a harmonic characteristic table; Waveform optimization and reconstruction are performed based on the harmonic characteristic table to obtain a dual-light source driving waveform sequence.

[0008] Furthermore, performing pulse stretching calculation on the reference PWM timing table to obtain a pulse modulation sequence includes: Performing dual-light source timing decomposition on the reference PWM timing table to obtain a timing reference data group, and performing pulse edge positioning on the timing reference data group to obtain a pulse edge parameter set; Performing pulse width expansion based on the pulse edge parameter set to obtain a stretched pulse sequence, and performing duty cycle compensation on the stretched pulse sequence to obtain a compensated pulse table; Performing pulse superposition calculation on the compensated pulse table to obtain a superposition waveform sequence, and performing edge jitter analysis on the superposition waveform sequence to obtain a jitter characteristic diagram; Pulse shaping optimization is performed based on the jitter characteristic graph to obtain a pulse modulation sequence.

[0009] Furthermore, the dual-path driving circuit performs current modulation output on the dual-light source driving waveform sequence to obtain a fusion light source lighting effect, including: Performing drive current conversion on the dual-light source drive waveform sequence through a dual-path drive circuit to obtain a current amplitude sequence, and performing temperature compensation calculation on the current amplitude sequence to obtain a compensation current parameter group; Performing dual-channel current synchronous output based on the compensation current parameter group to obtain a real-time current waveform, and performing overshoot suppression processing on the real-time current waveform to obtain a steady-state current curve; Performing optical power conversion calculation on the steady-state current curve to obtain an output optical power curve, and performing light spot synthesis analysis on the output optical power curve to obtain a light spot superposition characteristic diagram; The lighting effect is evaluated based on the light spot superposition feature map to obtain the lighting effect of the fused light source.

[0010] Furthermore, performing optical power conversion calculation on the steady-state current curve to obtain an output optical power curve includes: Performing electro-optical conversion characteristic analysis on the steady-state current curve to obtain a dual-light source response characteristic table, and performing nonlinear compensation on the dual-light source response characteristic table to obtain a photoelectric conversion function; Dynamically tracking the operating point based on the photoelectric conversion function to obtain an electro-optical conversion parameter group, and performing temperature drift correction on the electro-optical conversion parameter group to obtain a corrected power curve; performing optical power fluctuation analysis on the corrected power curve to obtain a power fluctuation feature set, and performing noise suppression processing on the power fluctuation feature set to obtain a steady-state optical power sequence; The dual light source powers are synthesized based on the steady-state optical power sequence to obtain an output optical power curve.

[0011] The present invention also provides an intelligent control system for an infrared LED and VCSEL laser fusion light source, comprising: The acquisition module is used to collect multi-band light intensity of the target scene through a multi-band photoelectric detector to obtain a scene light intensity feature matrix; A partitioning module, configured to perform a regional light intensity quantitative processing on the scene light intensity feature matrix based on a scene level divider to obtain a scene light level parameter; A calculation module, configured to calculate the power ratio of the infrared LED and the VCSEL laser based on the scene light level parameter to obtain a dual-light source driving waveform sequence; The output module is used to perform current modulation output on the dual-light source driving waveform sequence based on a dual-path driving circuit to obtain a fusion light source lighting effect.

[0012] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0013] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0014] The present invention provides an intelligent control method for a fusion light source of an infrared LED and a VCSEL laser, comprising the following steps: collecting multi-band light intensity of a target scene using a multi-band photodetector to obtain a scene light intensity characteristic matrix; performing regional light intensity quantitative processing on the scene light intensity characteristic matrix based on a scene level divider to obtain scene light level parameters; calculating the power ratio of the infrared LED and the VCSEL laser based on the scene light level parameters to obtain a dual-light source driving waveform sequence; and performing current modulation output on the dual-light source driving waveform sequence based on a dual-path driving circuit to obtain the fusion light source lighting effect. This method solves the technical problem of how to accurately obtain and utilize scene light intensity characteristics to guide the intelligent control of the light source, realizes the power ratio calculation of the infrared LED and the VCSEL laser based on the scene light level parameters, and can achieve the optimal combination of the dual light sources. This method can not only give full play to the advantages of the two light sources, but also effectively reduce energy consumption and extend the service life of the light sources. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a schematic diagram of the steps of an intelligent control method for an infrared LED and VCSEL laser fusion light source in one embodiment of the present invention; Figure 2This is a block diagram of the structure of an intelligent control system for an infrared LED and VCSEL laser fusion light source in one embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0016] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0018] like Figure 1 As shown, Figure 1 This is a schematic diagram of the steps of an intelligent control method for an infrared LED and VCSEL laser fusion light source in one embodiment of the present invention; In one embodiment of the present invention, a method for intelligently controlling an infrared LED and VCSEL laser fusion light source is provided, comprising the following steps: Step S1 : collecting multi-band light intensity of a target scene through a multi-band photoelectric detector to obtain a scene light intensity feature matrix.

[0019] Specifically, in implementing an intelligent control method for a fusion of infrared LEDs and VCSEL lasers, the system first collects multi-band light intensity data from the target scene using multi-band photodetectors to obtain a scene light intensity characteristic matrix. Specifically, this step involves using photodetectors capable of sensing multiple wavelengths to capture illumination information within the target scene. These photodetectors are designed to respond to light in specific wavelengths, enabling simultaneous measurement of the intensity of various light sources within the target scene (including ambient light and possible artificial light sources). For example, in a smart home environment, photodetectors can be installed in various locations within a room to monitor real-time changes in natural light and the intensity of light emitted by indoor lighting. This data generates a matrix representing the overall scene illumination characteristics, known as the scene light intensity characteristic matrix. This matrix not only contains the intensity values ​​for each wavelength but also implicitly captures the relationships between them, providing a foundation for subsequent processing. For example, as sunlight gradually intensifies in the morning, multi-band photodetectors can capture changes in light intensity from near-infrared to visible light. This helps the system accurately determine current lighting conditions and adjust the output power of infrared LEDs and VCSEL lasers accordingly, ensuring stable and appropriate lighting regardless of external light fluctuations. This precise light intensity acquisition mechanism is a key step in achieving efficient and intelligent light source control.

[0020] Step S2: performing regional light intensity quantification processing on the scene light intensity feature matrix based on a scene level divider to obtain scene light level parameters.

[0021] Specifically, in implementing an intelligent control method for a fusion infrared LED and VCSEL laser light source, a key step is to quantify the scene light intensity characteristic matrix by region using a scene level divider to obtain scene light level parameters. Specifically, the scene level divider analyzes the scene light intensity characteristic matrix collected by a multi-band photodetector and divides the target scene into multiple sub-regions based on different light intensity ranges and spatial distribution characteristics. The light intensity characteristics of each sub-region are further quantified into specific numerical indicators, thereby forming scene light level parameters. For example, in smart home applications, when lighting conditions vary significantly across different areas of a room (e.g., areas near windows are significantly affected by natural light, while areas far from windows rely primarily on artificial light), the scene level divider can identify these differences and divide the room into high, medium, and low light areas. To achieve this, the scene level divider typically combines a preset light intensity threshold with a dynamic adjustment algorithm to automatically optimize the region division results based on time periods or environmental changes. For example, during bright daylight hours, the system might assign high light levels to areas near windows. However, at night, when the lights are on, the light levels throughout the room might become more uniform. This regionalized light intensity quantification allows the system to accurately determine the actual lighting requirements of each area and generate appropriate scene light level parameters, providing a basis for subsequent calculations of the infrared LED and VCSEL laser power ratio. This mechanism not only improves the accuracy of light source control but also ensures that the lighting effects can better adapt to complex and changing real-world application scenarios.

[0022] Step S3: Calculate the power ratio of the infrared LED and the VCSEL laser based on the scene light level parameter to obtain a dual-light source driving waveform sequence.

[0023] Specifically, in implementing an intelligent control method for a fusion of infrared LEDs and VCSELs, calculating the power ratio of the infrared LEDs and VCSELs based on the scene light level parameters to generate a dual-light source driving waveform sequence is a key step in ensuring efficient and precise lighting effects. Specifically, this process takes the scene light level parameters generated in the previous step as input and, in combination with the characteristics of the infrared LEDs and VCSELs, designs a power allocation scheme tailored to the current lighting conditions. For example, in a smart home scenario, if a room is divided into high-light, medium-light, and low-light areas, the system dynamically adjusts the output power ratio of the two light sources based on the light level parameters for each area. In high-light areas, infrared LEDs may be preferred to provide soft supplemental lighting, while low-light areas may rely more on VCSELs to enhance brightness and provide precise beam control. To achieve this power ratio calculation, the system must comprehensively consider multiple factors, including the light intensity distribution characteristics of the two light sources, energy efficiency, and thermal management requirements. For example, infrared LEDs typically have a large coverage area but low light intensity, while VCSEL lasers can provide a highly focused beam but have a limited coverage area. Therefore, the system may calculate an optimal power distribution plan through an algorithmic model, allowing the two light sources to work together in different areas. In addition, to ensure the stability of the light source output, the system also needs to convert the calculation results into specific dual-light source driving waveform sequences. These waveform sequences define the current variation pattern of each light source in different time periods, thereby achieving precise control of the light source output. In this way, the system can not only meet the lighting needs of different areas, but also maximize energy efficiency and provide users with a comfortable and intelligent lighting experience.

[0024] Step S4: performing current modulation output on the dual-light source driving waveform sequence based on a dual-path driving circuit to obtain a fused light source lighting effect.

[0025] Specifically, in implementing an intelligent control method for a fused infrared LED and VCSEL light source, current modulation of the dual-light source drive waveform sequence based on a dual-path driver circuit to achieve a fused light source lighting effect is a key step in ensuring the entire system can accurately respond to and execute the preset light source control strategy. Specifically, in this process, the dual-path driver circuit precisely controls both light sources by adjusting the current intensity flowing through the infrared LED and VCSEL based on the previously calculated dual-light source drive waveform sequence. For example, in a smart home environment, when the system identifies that different areas of a room require different levels of supplemental lighting, the dual-path driver circuit adjusts the corresponding current values ​​based on the specific scene light level parameters of each area, enabling the infrared LED and VCSEL to work together in a pre-set ratio, providing energy-efficient and efficient lighting effects. To achieve this goal, the dual-path driver circuit must possess high flexibility and responsiveness to adjust the current output in real time. This means that the circuit design must not only consider the electrical characteristics of different light sources but also ensure stable performance across the entire operating range. For example, in the morning or evening, when natural light conditions fluctuate rapidly, the dual-path driver circuit can quickly respond to these changes, dynamically adjusting the current intensity of the infrared LED and VCSEL laser based on scene light level parameters, thereby maintaining a constant and appropriate light level in the room. In this way, the system not only adapts to varying ambient light conditions but also ensures optimal lighting quality in all situations. This current-modulated output method greatly improves the efficiency of light source use and provides users with a more intelligent and comfortable living space. Furthermore, it demonstrates how advanced electronics and intelligent algorithms can be used to transform complex theories into practical technical solutions, further promoting the development of the smart home sector.

[0026] In a specific embodiment, the multi-band light intensity acquisition of the target scene by the multi-band photoelectric detector to obtain the scene light intensity feature matrix includes: Performing spectral segment sampling of a target scene through a multi-band photoelectric detector to obtain an original spectral data stream, and performing wavelength calibration processing on the original spectral data stream to obtain a spectral response curve; Performing signal gain compensation on the spectral response curve to obtain a gain compensation data group, and performing dark current elimination processing on the gain compensation data group to obtain a photoelectric conversion characteristic curve; Performing light intensity analysis on the target scene based on the photoelectric conversion characteristic curve to obtain a spatial light intensity distribution diagram, and performing light intensity uniformity correction on the spatial light intensity distribution diagram to obtain a corrected light intensity matrix; Based on the spectrum fusion processor, multi-band feature extraction is performed on the corrected light intensity matrix to obtain a band feature vector group, and light intensity feature synthesis is performed on the band feature vector group to obtain a scene light intensity feature matrix.

[0027] Specifically, in implementing an intelligent control method for a fusion light source of infrared LEDs and VCSELs, the process of acquiring the multi-band light intensity of a target scene using a multi-band photodetector to obtain a scene light intensity feature matrix is ​​a complex and sophisticated process. First, the multi-band photodetector samples the target scene's spectrum in segmented segments. This process aims to obtain a raw spectral data stream covering the visible to near-infrared band. For example, in a smart home application, when morning sunlight enters a room through a window, the photodetector can capture variations in light intensity across different wavelength ranges, including visible light and near-infrared. Next, these raw spectral data streams are wavelength-calibrated to ensure data accuracy for each band, generating a set of spectral response curves. This set includes not only the visible spectrum bandwidth but also the near-infrared peak wavelength and the spectral resolution factor, which measures the system's resolution capability. To improve data quality and reliability, the spectral response curves are then subjected to signal gain compensation. This step helps balance response differences between different bands, resulting in a gain-compensated data set. Next, dark current cancellation is performed on the gain compensation data set to effectively remove errors caused by internal electronic noise in the device, ultimately yielding a photoelectric conversion characteristic curve that reflects the photoelectric conversion efficiency. This curve includes key parameters such as photoelectric response sensitivity, signal-to-noise ratio, and linear dynamic range, which are crucial for subsequent analysis. For example, in a smart home environment, if lighting conditions in a particular area change significantly—for example, if curtains are suddenly drawn, reducing natural light input—an accurate photoelectric conversion characteristic curve can help the system quickly adjust light source output to maintain a stable indoor light level. Next, based on this photoelectric conversion characteristic curve, light intensity analysis is performed on the target scene to generate a spatial light intensity distribution map. This step involves mapping the light intensity values ​​at each detection point to their corresponding locations, providing a visual representation of the lighting conditions within the entire scene. To further improve data consistency and reliability, the spatial light intensity distribution map is then subjected to light uniformity correction, resulting in a corrected light intensity matrix. This matrix not only records the actual light intensity values ​​at each location but also includes key indicators for assessing light quality, such as the light uniformity index, spatial distribution gradient, and light intensity fluctuation coefficient. For example, in a conference room, using this corrected light intensity matrix, the system can accurately identify seating areas requiring additional supplemental lighting, thereby optimizing the overall lighting effect. Finally, a spectral fusion processor performs multi-band feature extraction on the corrected light intensity matrix, extracting band feature vectors. These vectors not only reflect important light intensity information within each band but also provide a foundation for subsequent comprehensive analysis. Next, by synthesizing the light intensity features of the band feature vectors, a scene light intensity feature matrix can be constructed that comprehensively describes the target scene's lighting conditions.This matrix integrates important information such as the visible light intensity spectrum, near-infrared intensity spectrum, and ambient scattered light distribution map, allowing the system to make more accurate light source control decisions based on this matrix. For example, in a smart home environment, when night falls, outdoor street lights bring a certain amount of near-infrared light through the windows, while indoor lights provide the main visible light illumination. At this time, the system can automatically adjust the power ratio of infrared LEDs and VCSEL lasers based on the scene light intensity characteristic matrix to ensure that the best lighting experience is provided regardless of how the external environment changes. Through this series of meticulous operating steps, an in-depth understanding and precise control of the target scene's lighting conditions are achieved, greatly improving the intelligence level of the lighting system and the user experience.

[0028] In a specific embodiment, the scene level divider performs regional light intensity quantification processing on the scene light intensity feature matrix to obtain scene light level parameters, including: Performing regional segmentation and calibration on the scene light intensity feature matrix to obtain a scene region division map, and performing light intensity threshold layering on the scene region division map to obtain a regional light intensity hierarchy table; Performing spatial gradient calculation on the regional light intensity hierarchy table using a preset light intensity gradient method to obtain a light intensity change rate matrix, and performing boundary feature extraction on the light intensity change rate matrix to obtain a regional light intensity distribution feature map; Performing regional illumination equalization processing on the regional light intensity distribution characteristic map based on a preset illumination compensation processor to obtain an illumination compensation parameter group, and performing dynamic range mapping on the illumination compensation parameter group to obtain a regional illumination distribution map; The regional illumination distribution map is quantified by a scene level divider to obtain a regional light intensity quantitative parameter group, and the regional light intensity quantitative parameter group is subjected to parameter integration processing to obtain a scene illumination level parameter.

[0029] Specifically, in implementing an intelligent control method for a fusion infrared LED and VCSEL laser light source, the process of quantifying the light intensity of each region of the scene light intensity feature matrix using a scene level divider to obtain scene light level parameters is a highly sophisticated and technically demanding process. First, the scene light intensity feature matrix undergoes regional segmentation and calibration. This process aims to divide the entire scene into multiple sub-regions based on the light intensity characteristics of its different internal components, generating a scene region partition map. For example, in a smart home application, the system can identify bright areas near windows, darker areas away from windows, and the transition areas between the two within a room. This scene region partition map is then subjected to a light intensity threshold stratification method. By setting different light intensity thresholds, the light intensity levels within each region are distinguished, thereby forming a regional light intensity hierarchy table. This table not only identifies the primary target area, the transition region boundaries, and the background region, but also provides basic data support for subsequent analysis. Next, to more accurately understand the light intensity variations within each region, a preset light intensity gradient method is used to perform spatial gradient operations on the regional light intensity hierarchy table to calculate a light intensity change rate matrix. This step is particularly important for capturing the transition of light from one area to another. For example, in a smart home living room, when sunlight filters through the curtains, the light intensity change rate matrix accurately reflects the gradual weakening of light from the window edge to the depths of the room. Next, by performing boundary feature extraction on the light intensity change rate matrix, a regional light intensity distribution feature map is obtained, including a set of light intensity transition points, a gradient curve, and boundary sharpness values. This information helps the system better understand and simulate the complex changing patterns under actual lighting conditions, ensuring a more precise lighting system response. Subsequently, a pre-defined illumination compensation processor performs regional illumination equalization on the regional light intensity distribution feature map. This process balances illumination differences between different areas and improves the consistency and comfort of the overall lighting effect. Specifically, the system calculates an illumination compensation parameter set based on the regional light intensity distribution feature map and further applies dynamic range mapping to these parameters to generate a regional illuminance distribution map. This map not only contains key indicators such as the mean illuminance, illuminance dynamic range, and illuminance compensation coefficient for each area, but also helps the system formulate targeted light source control strategies. For example, in a smart home environment, if the illumination in a corner is detected to be significantly lower than in other areas, the system can adjust the output power of the infrared LED and VCSEL laser based on the regional illumination distribution map to ensure uniform lighting throughout the room. Finally, the regional illumination distribution map is quantified using a scene level divider. This process aims to convert specific illumination values ​​into easy-to-understand and easy-to-use light level parameters. The system then performs parameter integration on the regional light intensity quantitative parameter group to ultimately obtain the scene light level parameters.These parameters include the main area illumination value, background area brightness ratio, and dynamic range coefficient, which together form the basis for guiding light source regulation. For example, in a smart home environment, when night falls and indoor lights become the primary light source, the system can automatically adjust the operating status of infrared LEDs and VCSEL lasers according to the scene light level parameters, so that whether watching TV on the sofa or reading at the desk, everyone can enjoy a suitable and comfortable lighting experience. Through this series of meticulous operating steps, not only can in-depth analysis and optimization adjustments of the target scene lighting conditions be achieved, but it also provides users with more intelligent and personalized lighting solutions, greatly improving the comfort and sense of technology in the living environment. In addition, this precise lighting management method also helps to save energy and reduce consumption, reflecting the development trend and direction of modern lighting technology.

[0030] In a specific embodiment, the power ratio calculation of the infrared LED and the VCSEL laser based on the scene light level parameter to obtain the dual-light source driving waveform sequence includes: Performing light source ratio mapping on the infrared LED and the VCSEL laser based on the scene light level parameter to obtain a light source power distribution ratio table, and performing operating point calculation on the light source power distribution ratio table to obtain a dual-light source reference parameter group; Dividing the dual-light source reference parameter group into PWM cycles to obtain a reference PWM timing table, and performing pulse stretching calculation on the reference PWM timing table to obtain a pulse modulation sequence; Performing a dual-light source synchronous trigger design based on the pulse modulation sequence to obtain a trigger timing spectrum, and performing phase compensation calculation on the trigger timing spectrum to obtain phase compensation data; Performing waveform shaping processing on the phase compensation data to obtain a driving waveform data group, and performing harmonic distortion analysis on the driving waveform data group to obtain a harmonic characteristic table; Waveform optimization and reconstruction are performed based on the harmonic characteristic table to obtain a dual-light source driving waveform sequence.

[0031] Specifically, when calculating the power ratio of the infrared LED and VCSEL laser based on scene light level parameters to generate the dual-light source driving waveform sequence, the infrared LED and VCSEL laser light source ratio mapping is first performed based on the scene light level parameters. This process aims to determine the optimal output ratio of different light sources to meet specific lighting requirements, thereby generating a light source power allocation ratio table. For example, in a smart home environment, when a user wants to create a living room atmosphere that is both warm and energy-efficient, the system will determine the optimal power allocation ratio of the infrared LED and VCSEL laser based on the current scene light level parameters to ensure soft and even light distribution throughout the space. Next, by performing an operating point calculation on this light source power allocation ratio table, a dual-light source reference parameter set containing the LED reference power, the VCSEL reference power, and the mixing ratio coefficient is obtained. These parameters form the basis for subsequent PWM cycle division and pulse modulation. Next, the dual-light source reference parameter set is divided into PWM cycles, which produces a reference PWM timing table, a crucial step for achieving precise light intensity control. For example, in smart home applications, flexible adjustment of the light source's brightness and color temperature is required to accommodate different activity scenarios (such as reading and watching movies). A reference PWM timing table provides detailed guidance for this adjustment. Subsequently, pulse stretching calculations are performed on the reference PWM timing table to optimize the pulse width within each PWM cycle to achieve the optimal lighting effect. This results in a pulse modulation sequence that includes LED duty cycle parameters, VCSEL pulse width parameters, and modulation frequency parameters. These parameters collectively determine the light source's operating state. For example, in home theater mode, these parameters can be fine-tuned to reduce ambient light intensity and enhance the viewing experience. A dual-light source synchronous triggering design is then implemented based on this pulse modulation sequence. The goal is to ensure that the infrared LED and VCSEL laser operate in a pre-set time sequence, forming a trigger timing pattern. For example, in a smart home's automatic lighting control system, seamless switching between daytime and nighttime lighting modes requires precise control of the on and off times of the two light sources, which relies on an accurate trigger timing pattern. Based on this, phase compensation calculations are further performed on the trigger timing pattern to eliminate potential signal delays or distortion, thereby generating phase compensation data. This step is crucial for ensuring synchronization between light sources, especially in high-precision lighting applications such as art exhibitions or professional photography studios. Next, the phase compensation data undergoes waveform shaping to optimize the final electrical signal output to the light source, making it smoother and more stable, and preventing unnecessary fluctuations that affect lighting quality. The resulting drive waveform data set undergoes harmonic distortion analysis to assess and improve signal quality and mitigate the negative effects of nonlinear distortion.The harmonic signature table formed during this process provides important information about signal purity, facilitating subsequent waveform optimization and reconstruction. Finally, waveform optimization and reconstruction are performed based on the harmonic signature table, ultimately resulting in a dual-light source driving waveform sequence. This sequence includes key elements such as the LED duty cycle, VCSEL pulse width, and trigger timing, which together determine the specific operating modes of the infrared LED and VCSEL laser. For example, in a smart home environment, a carefully designed dual-light source driving waveform sequence can not only achieve all-day natural light simulation from early morning to late night, but also customize various special lighting effects based on the user's personalized preferences, greatly enhancing the comfort and intelligence level of the living environment. At the same time, this approach also helps extend the life of the light source and improve energy efficiency, reflecting the development direction of modern intelligent lighting technology.

[0032] In a specific embodiment, the light source ratio mapping of the infrared LED and the VCSEL laser is performed based on the scene light level parameter to obtain a light source power distribution ratio table, including: Performing a dual-light source characteristic analysis on the scene illumination level parameters to obtain a light source luminous characteristic table, and performing wavelength matching processing on the light source luminous characteristic table to obtain a dual-light source spectral parameter group; Calculating the illumination range of the infrared LED and the VCSEL laser based on the dual-light source spectral parameter group to obtain a light source coverage area map, and performing energy density analysis on the light source coverage area map to obtain a spatial energy distribution table; Optimizing the power ratio of the infrared LED and the VCSEL laser on the spatial energy distribution table to obtain a light source energy ratio sequence, and performing light intensity balance calibration on the light source energy ratio sequence to obtain a power distribution curve set; Performing temperature drift compensation on the power distribution curve set using a light source characteristic analyzer to obtain a temperature compensation parameter group, and performing power stability processing on the temperature compensation parameter group to obtain a steady-state power data table; Based on the steady-state power data table, the ratio mapping conversion of the infrared LED and the VCSEL laser is performed to obtain a light source power distribution ratio table.

[0033] Specifically, in implementing an intelligent control method for a fused infrared LED and VCSEL light source, mapping the infrared LED and VCSEL light source ratios based on scene light level parameters to generate a light source power allocation ratio table is a sophisticated and complex technical process. First, a dual-light source characteristic analysis is performed based on the scene light level parameters. This process evaluates the luminous properties of the infrared LED and VCSEL laser under different lighting conditions and generates a light source luminous property table. For example, in a smart home application, if a user wishes to automatically adjust the room's lighting brightness based on the time of day, the system will analyze the optimal output of the two light sources based on the current scene light level parameters. Next, wavelength matching is performed on the light source luminous property table to optimize the spectral overlap between the two, resulting in a dual-light source spectral parameter set. This step is crucial for ensuring consistent and uniform lighting results. Subsequently, the illumination range of the infrared LED and VCSEL laser is calculated based on the dual-light source spectral parameter set to generate a light source coverage map. This process not only considers the physical properties of the light sources themselves but also incorporates the needs of the actual application scenario, such as the required light intensity for different activity areas in a living room. Next, an energy density analysis is performed on the light source coverage area map to determine the specific energy distribution within each area, generating a spatial energy distribution table. For example, in a home theater setup, accurate energy density analysis can ensure the optimal visual experience for the audience area in front of the screen while avoiding the discomfort caused by excessive lighting. The spatial energy distribution table is then used to optimize the power ratio of infrared LEDs and VCSEL lasers to find the optimal power combination that meets specific lighting requirements, generating a light source energy distribution sequence. To further improve lighting quality, the light source energy distribution sequence is calibrated for intensity balance to eliminate any unevenness, resulting in a power distribution curve set. For example, in a smart home environment, if the light in a corner appears too dim or too bright, the system can adjust the power distribution curve to balance the light level across the entire room. Next, the power distribution curve set is compensated for temperature drift using a light source characteristic analyzer to address fluctuations in light source performance caused by ambient temperature changes, generating a temperature compensation parameter set. Given the impact of temperature on light source output stability, this step is critical for maintaining long-term stable lighting. Subsequently, the temperature compensation parameter set is processed for power stability to further optimize the light source's operating state and reduce power fluctuations caused by external factors, generating a steady-state power data table. Finally, based on this steady-state power data table, the infrared LED and VCSEL laser power distribution ratios are mapped and converted to produce a light source power distribution ratio table. This table clearly defines the respective proportions of infrared LED and VCSEL laser power under different lighting conditions, providing accurate data support for subsequent current modulation and driving.For example, in smart home applications, whether in sunny daytime or low-light environments at night, the system can dynamically adjust light output based on the light source power allocation ratio table to ensure the most suitable lighting experience. This series of meticulous operation steps not only achieves a deep understanding and precise control of the target scene's lighting conditions, but also provides users with more intelligent and personalized lighting solutions. This approach not only improves the efficiency and responsiveness of the lighting system, but also significantly enhances the comfort and sense of technology of the living environment.

[0034] In a specific embodiment, performing pulse stretching calculation on the reference PWM timing table to obtain a pulse modulation sequence includes: Performing dual-light source timing decomposition on the reference PWM timing table to obtain a timing reference data group, and performing pulse edge positioning on the timing reference data group to obtain a pulse edge parameter set; Performing pulse width expansion based on the pulse edge parameter set to obtain a stretched pulse sequence, and performing duty cycle compensation on the stretched pulse sequence to obtain a compensated pulse table; Performing pulse superposition calculation on the compensated pulse table to obtain a superposition waveform sequence, and performing edge jitter analysis on the superposition waveform sequence to obtain a jitter characteristic diagram; Pulse shaping optimization is performed based on the jitter characteristic graph to obtain a pulse modulation sequence.

[0035] Specifically, in implementing an intelligent control method for a fused infrared LED and VCSEL laser light source, the process of performing pulse stretching calculations on a reference PWM timing table to obtain a pulse modulation sequence is a crucial and technically complex step. First, the reference PWM timing table must undergo dual-light source timing decomposition. This process aims to break down the raw data containing information about the duty cycles of the two light sources into more detailed sets of timing reference data. For example, in a smart home application, when the system adjusts the living room lighting to accommodate the gradually dimming natural light conditions of the evening, analysis of the reference PWM timing table can accurately determine the start and end points of the respective duty cycles of the infrared LED and VCSEL laser, thereby generating a detailed set of timing reference data. Next, pulse edge positioning is performed based on this set of timing reference data. The goal is to identify key time points in each pulse signal, including the rising edge, falling edge, and pulse center, to form a set of pulse edge parameters. These key time points are crucial for subsequent pulse width stretching, as they directly impact the stability and accuracy of the final light source output. Next, pulse width stretching is performed based on the pulse edge parameter set. This increases the pulse width to enhance the brightness or modify the characteristics of the light source, resulting in a stretched pulse sequence. For example, in a smart home environment, if a user wishes to create a more immersive, dimmed atmosphere while watching a movie, the system can appropriately extend the pulse width of the VCSEL laser to reduce ambient light intensity. To ensure that this adjustment does not cause disharmony between light sources or affect overall lighting quality, the stretched pulse sequence is duty-cycle compensated to generate a compensated pulse table. This table not only includes the stretching coefficients for the infrared LED and VCSEL laser, but also takes into account phase compensation values ​​to ensure seamless interoperability. This step helps maintain synchronization between the different light sources and allows for flexible adjustment of the output ratio of each light source based on actual needs. The compensated pulse table is then subjected to pulse superposition calculations. This process combines the stretched and duty-cycle compensated pulse sequences into a single, combined waveform sequence. For example, in a smart home scenario, when the system attempts to simulate a light transition from day to night, superimposing waveform sequences can achieve a smooth lighting transition. However, to ensure stability and consistency during this conversion process, edge jitter analysis of the superimposed waveform sequence is required to detect and quantify any potential signal instabilities. The resulting jitter profile details key metrics such as jitter amplitude, jitter period, and edge steepness—information crucial for evaluating the quality of the light source output. Finally, pulse shaping optimization, based on the jitter profile, completes the entire process, aiming to eliminate or minimize any potential signal fluctuations and ensure the resulting pulse modulation sequence is highly reliable and stable.For example, in smart home applications, whether adjusting the brightness of a reading light or creating a low-light environment suitable for rest, precise pulse modulation sequences are required to guide the specific operating modes of infrared LEDs and VCSEL lasers. This sequence includes key elements such as LED duty cycle parameters, VCSEL pulse width parameters, and modulation frequency parameters, which together determine the ultimate performance of the light source. This series of carefully designed operating steps not only achieves precise response to the complex lighting requirements of the target scene, but also significantly improves the user experience, demonstrating the sophistication and flexibility of modern smart lighting systems. At the same time, this approach also provides a solid technical foundation for more innovative lighting application scenarios in the future.

[0036] In a specific embodiment, the dual-path driving circuit is used to perform current modulation output on the dual-light source driving waveform sequence to obtain a fusion light source lighting effect, including: Performing drive current conversion on the dual-light source drive waveform sequence through a dual-path drive circuit to obtain a current amplitude sequence, and performing temperature compensation calculation on the current amplitude sequence to obtain a compensation current parameter group; Performing dual-channel current synchronous output based on the compensation current parameter group to obtain a real-time current waveform, and performing overshoot suppression processing on the real-time current waveform to obtain a steady-state current curve; Performing optical power conversion calculation on the steady-state current curve to obtain an output optical power curve, and performing light spot synthesis analysis on the output optical power curve to obtain a light spot superposition characteristic diagram; The lighting effect is evaluated based on the light spot superposition feature map to obtain the lighting effect of the fused light source.

[0037] Specifically, in implementing an intelligent control method for a fused infrared LED and VCSEL laser light source, the process of current-modulating the dual-light source drive waveform sequence using a dual-path drive circuit to achieve the fused light source lighting effect is a key step in ensuring the final lighting quality. First, the dual-path drive circuit converts the dual-light source drive waveform sequence into a drive current sequence, generating a current amplitude sequence. This process transforms the previously calculated pulse modulation sequence into an operational current signal, providing basic data support for subsequent light source control. For example, in a smart home environment, when the system needs to adjust the living room lighting conditions to suit different activities, the dual-path drive circuit can accurately control the operating current of the infrared LED and VCSEL laser according to a preset drive waveform sequence. To ensure that these current signals maintain stable performance under different temperature conditions, temperature compensation calculations are performed on the current amplitude sequence to generate a compensated current parameter set. This parameter set not only includes the LED current threshold and VCSEL bias current, but also takes into account the temperature correction factor, which is crucial for maintaining the stability of the light source in various environments. Next, dual-channel current output is synchronized based on the compensation current parameter set. This ensures that the infrared LED and VCSEL laser operate in tandem according to a predetermined time sequence, generating a real-time current waveform. For example, in smart home applications, to create a smooth natural light transition from morning to night, the on / off timing of the two light sources must be precisely controlled, which relies on accurate real-time current waveforms. However, in actual operation, current overshoots may occur, affecting the light source's lifespan and lighting quality. Therefore, the real-time current waveform needs to be processed to suppress overshoot, optimize its rising and falling edge characteristics, and reduce steady-state ripple, thereby achieving a more stable steady-state current curve. This optimization process is crucial for ensuring the long-term stability of the light source. Subsequently, the steady-state current curve is converted to optical power, converting the current signal into actual light output to generate an output optical power curve. This process directly impacts the final lighting effect, as optical power determines the brightness and coverage of the light source. For example, in a smart home environment, if a user desires uniform and adequate light for reading, the system needs to adjust the output intensity of the infrared LED and VCSEL laser based on the output optical power curve. To further improve lighting quality, spot synthesis analysis is performed on the output optical power curve to evaluate the lighting effects of different light source combinations. The resulting spot superposition feature map details key indicators such as spot overlap, energy distribution uniformity, and edge transition band width. This information is very useful for understanding the actual lighting effect of the light source. Finally, the lighting effect evaluation based on the spot superposition feature map is the final step in the entire process, aiming to comprehensively evaluate the lighting performance of the integrated light source.For example, in smart home applications, whether adjusting the brightness of a reading light or creating a low-light environment suitable for rest, precise lighting effect evaluation is required to guide the specific operating mode of the light source. This evaluation result includes core elements such as lighting uniformity, contrast in the target area, and light intensity stability indicators, which together determine the ultimate lighting experience. Through this series of carefully designed operating steps, not only can the complex lighting requirements of the target scene be accurately responded to, but the user experience can also be significantly improved, reflecting the sophistication and flexibility of modern smart lighting systems. At the same time, this approach also provides a solid technical foundation for more innovative lighting application scenarios in the future, promoting the development of the smart home field. This highly integrated light source control system not only improves energy efficiency, but also brings unprecedented comfort and convenience to users.

[0038] Specifically, the specific implementation process of performing spot synthesis analysis on the output light power curve to obtain the spot superposition feature map is as follows: first, the output light power curve of the LED light source is obtained, which exhibits a Gaussian distribution characteristic. The spatial distribution data of the light intensity emitted by the LED is collected using a photodetector array, and its divergence angle and edge attenuation characteristics are recorded. Then, the output light power curve of the VCSEL laser is collected. Due to the good collimation of the VCSEL, its spot exhibits a more concentrated energy distribution. The collected light intensity data is then converted into a two-dimensional matrix, where each element of the matrix represents the light intensity value at the corresponding spatial position. A spatial superposition operation is then performed. By establishing a spatial coordinate system, the center positions of the LED and VCSEL light spots are determined as reference points, and the light intensity contributions of the two light sources at different spatial positions are calculated. Considering the diffuse reflection characteristics of the LED and the coherence of the VCSEL, the direct illumination component and the scattered component need to be calculated separately, while also considering the possible interference effect between the two light sources. Then, a numerical simulation of the superimposed light field is performed, and the composite light intensity at each point in space is calculated using the finite element analysis method, focusing on the energy distribution characteristics of the spot overlap area and analyzing the intensity gradient change in the edge transition area. To ensure calculation accuracy, optical parameters such as the material's reflectivity and refractive index, as well as the impact of environmental factors on light propagation, must be considered. The calculation results are then used to generate a spot superposition feature map. This map includes intensity contours, an energy distribution heat map, and a three-dimensional distribution map. Different colors represent different light intensity levels. Image processing algorithms are used to optimize the display and highlight key feature areas. For example, when the LED spot diameter is 20mm, the VCSEL spot diameter is 15mm, and the distance between the two light sources is 5mm, the intensity enhancement effect in the central overlap area and the gradual transition characteristics at the edge can be clearly observed. Finally, the spot superposition feature map is quantitatively analyzed to calculate the spot uniformity index, contrast parameters, and edge sharpness. These parameters serve as important indicators for evaluating the lighting effect of the fused light source and provide data support for subsequent light source optimization. This detailed analysis process accurately defines the spatial intensity distribution characteristics of the dual-light source fusion, providing technical support for achieving high-quality lighting effects.

[0039] In a specific embodiment, performing optical power conversion calculation on the steady-state current curve to obtain an output optical power curve includes: Performing electro-optical conversion characteristic analysis on the steady-state current curve to obtain a dual-light source response characteristic table, and performing nonlinear compensation on the dual-light source response characteristic table to obtain a photoelectric conversion function; Dynamically tracking the operating point based on the photoelectric conversion function to obtain an electro-optical conversion parameter group, and performing temperature drift correction on the electro-optical conversion parameter group to obtain a corrected power curve; performing optical power fluctuation analysis on the corrected power curve to obtain a power fluctuation feature set, and performing noise suppression processing on the power fluctuation feature set to obtain a steady-state optical power sequence; The dual light source powers are synthesized based on the steady-state optical power sequence to obtain an output optical power curve.

[0040] Specifically, in the process of calculating the optical power conversion from the steady-state current curve to obtain the output optical power curve, the electro-optical conversion characteristics of the steady-state current curve must first be analyzed to obtain a dual-light source response characteristic table. This process involves meticulously evaluating the performance of the infrared LED and VCSEL laser at different driving currents, thereby constructing a database that accurately describes their electro-optical response behavior. For example, in a smart home lighting system, to ensure comfortable and energy-efficient lighting in the living room, the performance parameters of each light source under various operating conditions must be precisely determined. Based on this response characteristic table, nonlinear compensation is then performed to eliminate non-ideal factors caused by internal device mechanisms or external environmental variations, thereby deriving the electro-optical conversion function. This function not only includes the current-power slope and threshold current point, but also key parameters such as the quantum efficiency coefficient, which are crucial for precise control of the light source. Subsequently, dynamic operating point tracking is performed based on this electro-optical conversion function. The purpose is to monitor and adjust the operating state of the light source in real time to ensure that it always remains within the optimal efficiency range, thereby obtaining a set of electro-optical conversion parameters. This stage of operation directly affects the actual performance of the system, as the highest energy conversion efficiency can only be achieved when the light source operates at its optimal operating point. Considering the impact of temperature on light source performance, the electro-optical conversion parameter set needs to be corrected for temperature drift. This step introduces a temperature compensation coefficient and takes into account factors such as power linearity and wavelength drift, ultimately generating a corrected power curve. For example, in high summer temperatures, if the smart home system fails to promptly adjust the operating parameters of the lighting fixture, this can lead to unstable light output and even damage the device. Temperature drift correction can effectively prevent these problems. Furthermore, the corrected power curve is analyzed for optical power fluctuations to identify and quantify various indicators that highlight power fluctuation characteristics, such as power stability, pulse energy distribution, and noise suppression ratio. This analysis provides a deeper understanding of the stability of the light source output and its temporal variations, providing a basis for subsequent optimization. For example, in a home theater environment, to ensure that the viewing experience is not affected by light intensity fluctuations, the output power of the projector lamp must be strictly controlled, which requires a precise understanding of the power fluctuation characteristics. Based on this, noise suppression processing is implemented to reduce the impact of random noise on the light source output quality, ultimately forming a steady-state optical power sequence. This sequence includes critical information such as carefully tuned power stability, pulse energy distribution, and noise suppression ratio, which together determine the reliability and consistency of the light source. Finally, dual-light source power synthesis based on the steady-state optical power sequence aims to combine the respective advantages of infrared LEDs and VCSEL lasers to produce an ideal output optical power curve. This curve not only reflects basic parameters such as peak optical power and average power density, but also includes the optical power dynamic range, demonstrating the system's adaptability throughout the entire operating cycle.For example, in smart home applications, whether creating a warm atmosphere for family gatherings or meeting low-light requirements at night, the total output power of the light source must be flexibly adjusted based on actual conditions. This highly integrated control approach not only significantly improves lighting performance, but also significantly reduces energy consumption and extends device life. Furthermore, this approach provides solid technical support for the development of more innovative smart lighting solutions, driving the entire industry towards greater intelligence and efficiency. In short, through the careful design and implementation of each of the above steps, precise conversion from current signal to optical power output is achieved, providing users with an unprecedented lighting experience.

[0041] The above describes the intelligent control method of the infrared LED and VCSEL laser fusion light source in the embodiment of the present invention. The following describes the intelligent control system of the infrared LED and VCSEL laser fusion light source in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, an intelligent control system for an infrared LED and VCSEL laser fusion light source includes: The acquisition module 21 is used to collect multi-band light intensity of the target scene through a multi-band photoelectric detector to obtain a scene light intensity feature matrix; A partitioning module 22 is configured to perform a regional light intensity quantification process on the scene light intensity feature matrix based on a scene level divider to obtain a scene light level parameter; A calculation module 23 is used to calculate the power ratio of the infrared LED and the VCSEL laser based on the scene light level parameter to obtain a dual-light source driving waveform sequence; The output module 24 is used to perform current modulation output on the dual-light source driving waveform sequence based on a dual-path driving circuit to obtain a fusion light source lighting effect.

[0042] In this embodiment, for the specific implementation of each unit in the above system embodiment, please refer to the above method embodiment, which will not be repeated here.

[0043] Reference Figure 3 The embodiment of the present invention further provides a computer device, the internal structure of which can be as follows Figure 3As shown. The computer device includes a processor, memory, display screen, input device, network interface and database connected via a system bus. The processor of the computer design is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the above method is implemented.

[0044] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0045] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the above-described method when executed by a processor. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0046] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware using a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the above-described method embodiments. Any reference to memory, storage, database, or other media provided herein and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may 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), double-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM.

[0047] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, apparatus, article, or method comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, apparatus, article, or method. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, apparatus, article, or method comprising the element.

[0048] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the description and drawings of the present invention, or directly or indirectly applied in other related technical fields, is also included in the patent protection scope of the present invention.

Claims

1. An intelligent control method for an infrared LED and VCSEL laser fusion light source, characterized in that: The following steps are involved: The multi-band light intensity of the target scene is collected by a multi-band photoelectric detector to obtain the scene light intensity feature matrix; Based on the scene level divider, the scene light intensity feature matrix is ​​quantitatively processed into regional light intensity to obtain scene light level parameters; Calculating the power ratio of the infrared LED and the VCSEL laser based on the scene light level parameter to obtain a dual-light source driving waveform sequence; The dual-light source driving waveform sequence is current-modulated and output based on a dual-path driving circuit to obtain a fusion light source lighting effect.

2. The intelligent control method of the infrared LED and VCSEL laser fusion light source according to claim 1, characterized in that: The multi-band light intensity of the target scene is collected by the multi-band photoelectric detector to obtain the scene light intensity feature matrix, including: Performing spectral segment sampling of a target scene through a multi-band photoelectric detector to obtain an original spectral data stream, and performing wavelength calibration processing on the original spectral data stream to obtain a spectral response curve; Performing signal gain compensation on the spectral response curve to obtain a gain compensation data group, and performing dark current elimination processing on the gain compensation data group to obtain a photoelectric conversion characteristic curve; Performing light intensity analysis on the target scene based on the photoelectric conversion characteristic curve to obtain a spatial light intensity distribution diagram, and performing light intensity uniformity correction on the spatial light intensity distribution diagram to obtain a corrected light intensity matrix; Multi-band feature extraction is performed on the corrected light intensity matrix to obtain a band feature vector group, and light intensity feature synthesis is performed on the band feature vector group to obtain a scene light intensity feature matrix.

3. The intelligent control method of the infrared LED and VCSEL laser fusion light source according to claim 1, characterized in that: The scene level divider performs regional light intensity quantification processing on the scene light intensity feature matrix to obtain scene light level parameters, including: Performing regional segmentation and calibration on the scene light intensity feature matrix to obtain a scene region division map, and performing light intensity threshold layering on the scene region division map to obtain a regional light intensity hierarchy table; Performing spatial gradient calculation on the regional light intensity hierarchy table using a preset light intensity gradient method to obtain a light intensity change rate matrix, and performing boundary feature extraction on the light intensity change rate matrix to obtain a regional light intensity distribution feature map; Performing regional illumination equalization processing on the regional light intensity distribution characteristic map to obtain an illumination compensation parameter group, and performing dynamic range mapping on the illumination compensation parameter group to obtain a regional illumination distribution map; The regional illumination distribution map is subjected to illumination level quantification to obtain a regional light intensity quantitative parameter group, and the regional light intensity quantitative parameter group is subjected to parameter integration processing to obtain a scene illumination level parameter.

4. The intelligent control method of the infrared LED and VCSEL laser fusion light source according to claim 1, characterized in that: The power ratio calculation of the infrared LED and the VCSEL laser based on the scene light level parameter to obtain a dual-light source driving waveform sequence includes: Performing light source ratio mapping on the infrared LED and the VCSEL laser based on the scene light level parameter to obtain a light source power distribution ratio table, and performing operating point calculation on the light source power distribution ratio table to obtain a dual-light source reference parameter group; Dividing the dual-light source reference parameter group into PWM cycles to obtain a reference PWM timing table, and performing pulse stretching calculation on the reference PWM timing table to obtain a pulse modulation sequence; Performing a dual-light source synchronous trigger design based on the pulse modulation sequence to obtain a trigger timing spectrum, and performing phase compensation calculation on the trigger timing spectrum to obtain phase compensation data; Performing waveform shaping processing on the phase compensation data to obtain a driving waveform data group, and performing harmonic distortion analysis on the driving waveform data group to obtain a harmonic characteristic table; Waveform optimization and reconstruction are performed based on the harmonic characteristic table to obtain a dual-light source driving waveform sequence.

5. The intelligent control method of the infrared LED and VCSEL laser fusion light source according to claim 4, characterized in that: The performing pulse stretching calculation on the reference PWM timing table to obtain a pulse modulation sequence includes: Performing dual-light source timing decomposition on the reference PWM timing table to obtain a timing reference data group, and performing pulse edge positioning on the timing reference data group to obtain a pulse edge parameter set; Performing pulse width expansion based on the pulse edge parameter set to obtain a stretched pulse sequence, and performing duty cycle compensation on the stretched pulse sequence to obtain a compensated pulse table; Performing pulse superposition calculation on the compensated pulse table to obtain a superposition waveform sequence, and performing edge jitter analysis on the superposition waveform sequence to obtain a jitter characteristic diagram; Pulse shaping optimization is performed based on the jitter characteristic graph to obtain a pulse modulation sequence.

6. The intelligent control method of the infrared LED and VCSEL laser fusion light source according to claim 1, characterized in that: The dual-path driving circuit is used to perform current modulation output on the dual-light source driving waveform sequence to obtain a fusion light source lighting effect, including: Performing drive current conversion on the dual-light source drive waveform sequence through a dual-path drive circuit to obtain a current amplitude sequence, and performing temperature compensation calculation on the current amplitude sequence to obtain a compensation current parameter group; Performing dual-channel current synchronous output based on the compensation current parameter group to obtain a real-time current waveform, and performing overshoot suppression processing on the real-time current waveform to obtain a steady-state current curve; Performing optical power conversion calculation on the steady-state current curve to obtain an output optical power curve, and performing light spot synthesis analysis on the output optical power curve to obtain a light spot superposition characteristic diagram; The lighting effect is evaluated based on the light spot superposition feature map to obtain the lighting effect of the fused light source.

7. The intelligent control method of the infrared LED and VCSEL laser fusion light source according to claim 6, characterized in that: The performing optical power conversion calculation on the steady-state current curve to obtain an output optical power curve includes: Performing electro-optical conversion characteristic analysis on the steady-state current curve to obtain a dual-light source response characteristic table, and performing nonlinear compensation on the dual-light source response characteristic table to obtain a photoelectric conversion function; Dynamically tracking the operating point based on the photoelectric conversion function to obtain an electro-optical conversion parameter group, and performing temperature drift correction on the electro-optical conversion parameter group to obtain a corrected power curve; performing optical power fluctuation analysis on the corrected power curve to obtain a power fluctuation feature set, and performing noise suppression processing on the power fluctuation feature set to obtain a steady-state optical power sequence; The dual light source powers are synthesized based on the steady-state optical power sequence to obtain an output optical power curve.

8. An intelligent control system for infrared LED and VCSEL laser fusion light source, characterized in that: include: The acquisition module is used to collect multi-band light intensity of the target scene through a multi-band photoelectric detector to obtain a scene light intensity feature matrix; A partitioning module, configured to perform a regional light intensity quantitative processing on the scene light intensity feature matrix based on a scene level divider to obtain a scene light level parameter; A calculation module, configured to calculate the power ratio of the infrared LED and the VCSEL laser based on the scene light level parameter to obtain a dual-light source driving waveform sequence; The output module is used to perform current modulation output on the dual-light source driving waveform sequence based on a dual-path driving circuit to obtain a fusion light source lighting effect.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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