Optical phased array lidar system based on a light splitting system and scanning method thereof

Abstract

The present application relates to the technical field of laser radar scanning, and particularly relates to an optical phased array laser radar system based on a light splitting system and a scanning method thereof, the system comprising: a light splitting system and an optical phased array laser radar.The laser radar comprises: a laser, an optical phased array, a visible light area array detector, a filter, a laser radar detector, an image processing module, a data processing module and a control module; the laser emits a laser beam; the optical phased array changes the direction and shape of the laser beam; the visible light area array detector obtains a two-dimensional gray scale image; the laser radar detector receives the light beam after filtering by the filter; the image processing module obtains a point cloud coordinate set; the data processing module generates a control parameter set; and the control module is used to control the optical phased array laser radar to scan a region to be scanned to obtain point cloud data.The present application has the advantages that, through target recognition or edge contour recognition, redundant data is reduced, and the complexity of subsequent data processing is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of laser radar scanning technology, and in particular to an optical phased array laser radar system based on a light splitting system and a scanning method thereof. BACKGROUND

[0002] Optical phased array (OPA) is a beam pointing technology that realizes dynamic control of beam direction, shape and intensity by regulating phase. OPA laser radar with OPA chip as the core integrates laser ranging and imaging technology. Its phase control mainly relies on two modulation methods of electro-optic and thermo-optic: electro-optic modulation changes carrier concentration and refractive index by applying voltage to the PN junction of the waveguide; thermo-optic modulation realizes phase control by driving voltage to regulate temperature.

[0003] In two-dimensional scanning, OPA laser radar controls the transverse scanning phase angle by driving voltage and synchronously changes the laser wavelength to realize longitudinal scanning, thereby covering the entire two-dimensional scene.

[0004] However, the performance of the existing OPA laser radar is limited by its low scanning speed. The bottleneck mainly comes from the limitation of control word writing and configuration speed and voltage establishment speed. When multiple OPA laser radars perform global two-dimensional scene scanning, due to the slow scanning speed, the generated three-dimensional image frame frequency is low, which is difficult to meet the demand of high-speed three-dimensional point cloud data acquisition. In addition, in vehicle-mounted road detection and other applications, the system still needs to perform global scanning on the sky, road surface and other non-key areas, causing waste of hardware resources and redundant data, further slowing down the frame frequency.

[0005] On the other hand, the photodetector of the OPA laser radar needs to filter the incident light with a filter to ensure that only the echo of the same spectral band as the emitted laser is detected and to improve the signal-to-noise ratio. However, narrow-band filtering weakens the echo intensity, and the waveguide array introduces light intensity attenuation in the outgoing and return paths, resulting in a decrease in system light efficiency and affecting the detection performance. SUMMARY

[0006] Therefore, the present application proposes an optical phased array laser radar system based on a light splitting system and a scanning method thereof. The incident light beam is separated into a reflected light beam and a transmitted light beam by the light splitting system, and the two separated light beams enter the visible light area array detector and the laser radar detector respectively. The light beam path entering the visible light area array detector has no filter, so the environment light with strong light power can be used for detection.

[0007] To achieve the above object, the technical scheme of the application is realized as follows: an optical phased array laser radar system based on a light splitting system, comprising: a light splitting system configured to separate an incident light beam from a scene into a reflected light beam and a transmitted light beam; an optical phased array laser radar, the optical phased array laser radar comprising: a laser, an optical phased array, a visible light area array detector, a filter, a laser radar detector, an image processing module, a data processing module, and a control module; the laser is used to emit a laser beam to scan objects in the scene; the optical phased array is used to control the laser beam by phase control to change the direction and shape of the laser beam; the visible light area array detector is used to receive the reflected light beam to obtain a two-dimensional gray scale image of the scene; the filter is arranged in the light path of the transmitted light beam; the laser radar detector is used to receive the light beam filtered by the filter; the image processing module is used to identify targets or identify edge contours of the two-dimensional gray scale image to obtain effective targets or edge contours of the targets, and obtain a point cloud coordinate set of the effective targets or the edge contours; the data processing module is used to map each point coordinate in the point cloud coordinate set to a driving voltage value of the optical phased array and an emission wavelength value of the laser according to a pre-set scanning lookup table to generate a control parameter set composed of the driving voltage value and the emission wavelength value; and the control module is used to control the optical phased array laser radar to scan a to-be-scanned region according to the control parameter set to obtain point cloud data.

[0008] A scanning method of an optical phased array laser radar system based on a light splitting system, which is realized by using the optical phased array laser radar system based on the light splitting system, is used to identify targets of a two-dimensional gray scale image to obtain a to-be-scanned region, and comprises the following steps:

[0009] A1: The light splitting system separates an incident light beam from a scene into a reflected light beam and a transmitted light beam.

[0010] A2: The visible light area array detector receives the reflected light beam to obtain a two-dimensional gray scale image of the scene; target identification and target analysis are performed on the two-dimensional gray scale image to screen out effective targets.

[0011] A3: A target detection algorithm based on deep learning is used to process the two-dimensional gray scale image, extract a region of interest corresponding to each effective target, and assign a corresponding point cloud density to each region of interest to generate a point cloud coordinate set, and record a scanning phase angle of the optical phased array corresponding to each to-be-measured point in the point cloud.

[0012] A4: Based on the scanning phase angle, each to-be-measured point coordinate is mapped to a driving voltage value of the optical phased array and an emission wavelength value of the laser through a pre-set scanning lookup table to generate a control parameter set.

[0013] A5: According to the control parameter set, the optical phased array lidar sequentially scans the effective target to generate point cloud data.

[0014] Further, in step A2, target recognition and target analysis are performed on the two-dimensional gray image to obtain the category and size information of the target; based on the category and size information of the target, the value coefficient of the target is determined; and the target whose value coefficient satisfies the preset condition is screened as an effective target.

[0015] Further, in step A3, according to the value coefficient of the effective target, a point cloud density is assigned to the corresponding region of interest to realize dense scanning or sparse scanning; the point cloud density is determined by the number of to-be-measured points in a unit area;

[0016] The number M of to-be-measured points in the point cloud in each region of interest i The number M of to-be-measured points in the point cloud in each region of interest

[0017] ;

[0018] Wherein, is the value coefficient of the region of interest, S i is the area of the region of interest, and k is a proportional coefficient.

[0019] Further, according to the region of interest and the number of to-be-measured points, the to-be-measured points are uniformly distributed in the region of interest in the form of a dot matrix, and the coordinates of each to-be-measured point are determined to form a point cloud coordinate set; according to the point cloud coordinate set, the scanning phase angle of the optical phased array corresponding to each to-be-measured point is calculated.

[0020] A scanning method of an optical phased array lidar system based on a light splitting system, realized by using the above-mentioned optical phased array lidar system based on a light splitting system, for edge contour recognition of a two-dimensional gray image to obtain a to-be-scanned region, comprising the following steps:

[0021] B1: The light splitting system separates the incident light beam from the scene into a reflected light beam and a transmitted light beam.

[0022] B2: The visible light area array detector receives the reflected light beam to obtain a two-dimensional gray image of the scene; based on the image gray difference, an edge contour recognition algorithm is used to extract the edge contour of the target from the two-dimensional gray image to obtain a point cloud coordinate set around the edge contour, and simultaneously record the scanning phase angle of the optical phased array corresponding to the to-be-measured point in the point cloud.

[0023] B3: Based on the scanning phase angle, through a pre-set scanning lookup table, the coordinates of each point in the point cloud are mapped to the driving voltage value of the optical phased array and the emission wavelength value of the laser, and then a control parameter set is generated.

[0024] B4: Based on the set of control parameters, control the optical phased array lidar to scan each edge contour sequentially to generate point cloud data.

[0025] Furthermore, step B2 includes: performing digital image processing on the two-dimensional grayscale image, extracting the edge contour of the target based on the grayscale difference between pixels using an edge contour detection algorithm, and obtaining a set of point cloud coordinates around the edge contour.

[0026] Furthermore, the edge contour detection algorithm is implemented by comparing the grayscale differences between pixels with a preset threshold and extracting points with grayscale differences greater than the threshold to form contours.

[0027] Furthermore, a point cloud coordinate set is generated by employing a geometric offset method based on normal vectors or a dilation method based on image morphology.

[0028] This invention achieves the following beneficial effects: It utilizes a visible light area array detector to acquire a two-dimensional grayscale image of a scene, identifies effective targets and their edge contours, and then guides an optical phased array lidar to perform targeted scanning to obtain point cloud data. This method leverages the inherent components of the OPA lidar system, eliminating the need for additional photoelectric detection equipment such as cameras. By preprocessing the scene under test and combining the flexibility of the OPA system in steering control, it achieves the scanning of potentially important targets.

[0029] The system quickly identifies "valid targets" and "edge contours" using 2D grayscale images, scanning only the contour areas of valid targets. This significantly reduces the number of points that need to be measured, allowing for more frequent updates to key target information or the completion of a panoramic scan in a shorter timeframe.

[0030] This method optimizes resource allocation, concentrating limited detection capabilities on key target contour regions, thereby significantly improving the detection speed of local scanning and the system's response speed to targets. Ultimately, it generates more distinctive and higher-quality 3D point clouds. Furthermore, this method reduces redundant data and lowers the complexity of subsequent data processing, providing technical support for achieving higher performance and energy efficiency in optical phased array lidar scanning imaging. Attached Figure Description

[0031] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments and descriptions of the invention are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0032] Figure 1 This is a schematic diagram of the structure of an optical phased array lidar system based on a beam splitting system provided in an embodiment of the present invention;

[0033] Figure 2 This is a flowchart of a scanning method based on effective targets provided according to an embodiment of the present invention;

[0034] Figure 3 This is a flowchart of an edge contour-based scanning method provided according to an embodiment of the present invention. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not constitute a limitation thereof.

[0036] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0037] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0038] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0039] The invention will now be described in detail with reference to specific embodiments.

[0040] like Figure 1As shown in the figure, an optical phased array lidar system based on a beam splitting system is provided in this embodiment of the invention. The system includes a beam splitting system and an optical phased array lidar. The beam splitting system is configured to separate an incident beam from a scene into a reflected beam and a transmitted beam. An optical phased array lidar includes: a laser, an optical phased array, a visible light array detector, a filter, a lidar detector, an image processing module, a data processing module, and a control module. The laser emits a laser beam to scan objects in the scene. The optical phased array controls the laser beam through phase control to change its direction and shape. The visible light array detector receives the reflected beam and acquires a two-dimensional grayscale image of the scene. The filter is placed in the optical path of the transmitted beam. The lidar detector receives the beam filtered by the filter. The image processing module performs target recognition or edge contour recognition on the two-dimensional grayscale image to obtain valid targets or their edge contours, and acquires a set of point cloud coordinates for the valid targets or edge contours. The data processing module maps the coordinates of each point in the point cloud coordinate set to the driving voltage value of the optical phased array and the emission wavelength value of the laser, generating a set of control parameters consisting of the driving voltage value and the emission wavelength value, based on a pre-set scan lookup table. The control module controls the optical phased array lidar to scan the area to be scanned according to the control parameter set, obtaining point cloud data.

[0041] A scanning method for an optical phased array lidar system based on a beam splitting system, implemented using the aforementioned optical phased array lidar system based on a beam splitting system, is used to identify targets in a two-dimensional grayscale image to obtain the area to be scanned, and includes the following steps:

[0042] A1: The beam splitting system separates the incident light beam from the scene into a reflected beam and a transmitted beam. The reflected beam is received by a visible light array detector, while the transmitted beam is received by a lidar detector after passing through a filter.

[0043] A2: The visible light array detector receives the reflected light beam and acquires a two-dimensional grayscale image of the scene; it then performs target recognition and analysis on the two-dimensional grayscale image to filter out valid targets.

[0044] Specifically, a visible light array detector acquires a two-dimensional grayscale image of the scene. The image processing module performs target recognition and analysis on the grayscale image to obtain target category and size information, resulting in multiple targets T1, T2, ..., Tn (n is a positive integer). Based on the target category and size information, the target's value coefficients Value1, Value2, ..., Value are determined. n Targets whose value coefficients meet preset conditions are selected as valid targets. The value coefficients of the targets are compared with preset value coefficient thresholds, and targets with value coefficients higher than the thresholds are selected as valid targets TE1, TE2, ..., TE3. m(m is a positive integer).

[0045] It should be noted that the value coefficient is usually set based on experience: pedestrians, vehicles, and close-range targets are assigned larger values, while road surfaces and distant targets are assigned smaller values. It should also be noted that the preset threshold is an empirical parameter and needs to be flexibly adjusted according to the on-site scenario and detection accuracy requirements; no specific limitations are set here.

[0046] A3: A deep learning-based target detection algorithm is used to process the two-dimensional grayscale image, extract the region of interest (the area to be scanned) corresponding to each effective target, and assign a corresponding point cloud density to each region of interest to generate a set of point cloud coordinates. At the same time, the scanning phase angle of the optical phased array corresponding to each point to be tested in the point cloud is recorded.

[0047] Specifically, a deep learning-based object detection algorithm is used to process the two-dimensional grayscale image to generate object masks Mask1, Mask2, ..., Mask. m The target mask is multiplied by the 2D grayscale image to extract the region of interest R1, R2, ..., R for each valid target. m (m is a positive integer). The image processing module assigns different 3D point cloud densities to each region of interest based on the value coefficient of the effective target, performing dense scanning in regions with high value coefficients and sparse scanning in regions with low value coefficients.

[0048] The number of points to be measured in the 3D point cloud within each region of interest is M. i Calculated using the following formula:

[0049] ;

[0050] in, S represents the value coefficient of the region of interest. i Let be the area of ​​the region of interest, and k be the scaling factor. It should be noted that k is usually set based on experience, and its value ranges from 0 to 1.

[0051] Based on the region of interest and the number of test points, the test points are distributed in a grid within the region of interest, and the coordinates of each test point are determined as (x1, y1), (x2, y2), ..., (x...). Mi y Mi This forms a three-dimensional point cloud coordinate set; simultaneously, it records the scanning phase angle of the optical phased array corresponding to each point under test. Here, x is the horizontal coordinate, and y is the vertical coordinate (longitudinal direction) orthogonal to x.

[0052] In this embodiment, the test points in the dot matrix are arranged in a rectangular pattern. The size of the test points is ri×ci, where ri is the number of rows of test points, ci is the number of columns of test points, and ri×ci=Mi. The OPA scanning phase angle sequence corresponding to all test points is calculated.

[0053] Point cloud density is dynamically allocated based on the target's value coefficient. For high-value targets (such as pedestrians and vehicles), a higher point cloud density is allocated to obtain finer contours and surface details; for low-value targets, a lower density is used for scanning, saving resources and significantly improving the quality of useful data.

[0054] A4: Based on the scanning phase angle, the coordinates of each test point are mapped to the driving voltage value of the optical phased array and the emission wavelength value of the laser through a pre-set scanning lookup table, thereby generating a set of control parameters.

[0055] The pre-set scan lookup table includes the following steps: The optical phased array lidar is driven to scan within the global field of view, recording the lateral angle of the scan phase and the corresponding driving voltage value, thus establishing a lateral scan lookup table to find the corresponding driving voltage value (x-axis) based on the scan phase angle. The longitudinal angle of the scan phase and the corresponding laser emission wavelength value are recorded, establishing a longitudinal scan lookup table to find the corresponding laser wavelength based on the required longitudinal position. The lateral and longitudinal scan lookup tables are used during the scanning process to obtain the corresponding driving voltage and laser wavelength values ​​based on the coordinate mapping of the target point.

[0056] The coordinates of the points to be measured for each valid target are (x1, y1), (x2, y2), ..., (x Mi y Mi The control parameter set (V1, λ1), (V2, λ2), ..., (V2, λ2) corresponding to the driving voltage value and the emission wavelength value for each point is mapped through horizontal and vertical scan lookup tables. Mi , λ ri ), ri is the number of rows of the points to be measured in the scanning area Ri, corresponding to ri scanning wavelengths.

[0057] A5: Based on the set of control parameters, control the optical phased array lidar to scan the effective target or edge contour area in sequence to obtain the corresponding point cloud data.

[0058] Specifically, the control module sets the emission wavelength of the laser and the driving voltage of the optical phased array based on the set of control parameters, and controls the optical phased array lidar to scan all the test points in the region of interest line by line.

[0059] Adjust the emission wavelength of the laser to λ1, where λ1 is the scanning wavelength corresponding to the first row of test points in the scanning area R1; according to the driving voltage value obtained in step A3, control the OPA to complete the scanning of the first row of test points in the scanning area R1.

[0060] Adjust the laser emission wavelength to λ2, ..., λ r1 , where r1 is the number of rows of test points in the scanning area R1, corresponding to r1 scanning wavelengths. Repeat the above process until all test points in the scanning area R1 are measured.

[0061] Iteratively execute steps A1 to A5 to continuously generate 3D point cloud data of the region of interest.

[0062] A scanning method for an optical phased array lidar system based on a beam splitting system, utilizing the aforementioned optical phased array lidar system based on a beam splitting system, is used to perform edge contour recognition on a two-dimensional grayscale image to obtain the area to be scanned, and includes the following steps:

[0063] B1: The beam splitting system separates the incident light beam from the scene into a reflected beam and a transmitted beam. The reflected beam is received by a visible light array detector, while the transmitted beam is received by a lidar detector after passing through a filter.

[0064] B2: The visible light array detector receives the reflected light beam and acquires a two-dimensional grayscale image of the scene; based on the grayscale difference of the image, the edge contour recognition algorithm is used to extract the edge contour of the target from the two-dimensional grayscale image, and obtain the set of point cloud coordinates around the edge contour (the area to be scanned), while recording the scanning phase angle of the optical phased array corresponding to the point to be measured in the point cloud.

[0065] Specifically, the image processing module performs digital image processing on the 2D grayscale image. It preprocesses the original 2D grayscale image (e.g., noise reduction and contrast enhancement) to improve the signal-to-noise ratio. Based on the grayscale differences (grayscale gradients) between pixels, an edge detection algorithm is used to extract the edge contours of the target. The grayscale differences between pixels are compared with a preset threshold, and points with grayscale differences greater than the threshold are extracted to form edge contours, obtaining a set of point cloud coordinates surrounding each edge contour. After these steps, the coordinates of all pixels in the image confirmed as valid edges are extracted, forming a set of point cloud coordinates surrounding the edge contours.

[0066] It should be noted that the preset threshold is an empirical parameter and needs to be flexibly adjusted according to the on-site scenario and detection accuracy requirements. No specific limitation is made here.

[0067] The point cloud coordinate set is evenly distributed in a lattice pattern around the edge contour. This means that the lattice does not just overlap the extracted edge contour, but rather extends outwards and inwards from the contour line of the edge contour as a band-shaped area. The purpose of this is to ensure that even if there are slight deviations in contour recognition, or slight movements in the actual position of the object, the laser beam can completely "cover" the real physical edge.

[0068] The point cloud coordinate set is uniformly distributed in the form of a point matrix around the edge contour, which can be achieved in ways including but not limited to the following:

[0069] The geometric offset method based on normal vectors calculates the unit normal vector of each point in the point cloud of the contour region, and offsets it by a preset distance along the positive and negative directions of the normal vector to generate two extended boundaries, forming a closed strip-shaped polygonal region; then uniform sampling is performed within this polygonal region to generate an extended point cloud coordinate set.

[0070] The image morphology-based dilation method maps the point cloud coordinates of the contour onto a binary image to form a single-pixel-wide contour line; it then performs morphological dilation on the binary image using structuring elements of preset shapes and sizes to generate a band-shaped region; finally, it extracts the coordinates of all pixels within this band-shaped region as an extended point cloud coordinate set, or it can be downsampled and used.

[0071] It should be noted that, regardless of the method used, the purpose is to construct an extended region based on the identified target's edge contour to guide the optical phased array lidar for fine scanning. Those skilled in the art can implement this step by combining known algorithms (such as geometric offset of normal vectors, image morphology dilation, etc.) according to the above description. In other embodiments, other methods can also be used to uniformly distribute the point cloud coordinate set in a matrix form around the edge contour.

[0072] B3: Based on the scanning phase angle, the coordinates of each point in the point cloud are mapped to the driving voltage value of the optical phased array and the emission wavelength value of the laser through a pre-set scanning lookup table, thereby generating a set of control parameters.

[0073] The pre-set scan lookup table includes the following steps: drive the optical phased array lidar to scan within the global field of view, record the lateral angle of each scan phase angle and the corresponding drive voltage value, and establish a lateral scan lookup table; record the longitudinal angle of each scan phase angle and the corresponding laser emission wavelength value, and establish a longitudinal scan lookup table; based on the coordinates of each point, obtain the drive voltage from the lateral scan lookup table and obtain the laser wavelength from the longitudinal scan lookup table.

[0074] The horizontal and vertical scan lookup tables are used to obtain the corresponding driving voltage and laser wavelength based on the coordinate mapping of each point during the scanning process.

[0075] The coordinates of each point in the edge contour are (x1, y1), (x2, y2), ..., (x Mi y Mi The control parameters (V1, λ1), (V2, λ2), ..., (V2, λ2) corresponding to the driving voltage and emission wavelength values ​​for each point are mapped using horizontal and vertical scan lookup tables. Mi , λ Mi ).

[0076] B4: Based on the set of control parameters, control the optical phased array lidar to scan each edge contour sequentially to generate point cloud data.

[0077] Iteratively execute steps B1 to B4 to continuously generate 3D point cloud data of the region of interest.

[0078] In summary, the scanning method of this invention, by setting up a beam-splitting system, enables a visible light area array detector to perform area array imaging of the scene under test using ambient light with relatively high intensity, effectively improving the accuracy of target recognition. It utilizes the visible light area array detector to acquire a two-dimensional grayscale image of the scene and identifies effective targets or their edge contours, thereby guiding the optical phased array lidar for targeted scanning. This method leverages the inherent components of the OPA lidar system, eliminating the need for additional photoelectric detection equipment such as cameras. By preprocessing the scene under test and combining the flexibility of the OPA system in steering control, it achieves the scanning of potentially important targets.

[0079] By preprocessing the 2D grayscale image, effective targets or edge contours are identified. Leveraging the flexible steering advantage of the optical phased array, dense scanning is performed on potentially important targets, while sparse scanning or skipping of less important targets is performed. This reduces redundant data and lowers the complexity of subsequent data processing.

[0080] This method optimizes resource allocation, concentrating limited detection capabilities on the region of interest, thereby significantly improving the detection speed of local scanning and the system's response speed to targets. Ultimately, it generates more salient and higher-quality 3D point clouds. Furthermore, this method reduces redundant data and lowers the complexity of subsequent data processing, providing technical support for achieving higher performance and energy efficiency in optical phased array lidar scanning imaging.

[0081] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An optical phased array lidar system based on a light splitting system, characterized in that, The application relates to a kind of optical phased array lidar systems and methods. The application includes: A light splitting system configured to split an incident light beam from a scene into a reflected light beam and a transmitted light beam; An optical phased array lidar including a laser, an optical phased array, a visible light area array detector, a filter, a lidar detector, an image processing module, a data processing module, and a control module; The laser is configured to emit a laser beam to scan an object of the scene; The optical phased array is configured to control the laser beam by phase control to change the direction and shape of the laser beam; The visible light area array detector is configured to receive the reflected light beam to obtain a two-dimensional grayscale image of the scene; The filter is disposed in the optical path of the transmitted light beam; The lidar detector is configured to receive the light beam filtered by the filter; The image processing module is configured to perform target recognition or edge contour recognition on the two-dimensional grayscale image to obtain an effective target or an edge contour of the target, and further obtain a point cloud coordinate set of the effective target or the edge contour; The data processing module is configured to map each point coordinate in the point cloud coordinate set to a driving voltage value of the optical phased array and an emission wavelength value of the laser according to a pre-set scanning lookup table to generate a control parameter set composed of the driving voltage value and the emission wavelength value; 2. A scanning method of an optical phased array lidar system based on a light splitting system, implemented by the optical phased array lidar system based on the light splitting system of claim 1, for target recognition on a two-dimensional gray image to obtain a region to be scanned, characterized in that, The control module is configured to control the optical phased array lidar to scan the to-be-scanned region according to the control parameter set to obtain point cloud data. The application includes the following steps: A1: The light splitting system splits the incident light beam from the scene into the reflected light beam and the transmitted light beam; A2: The visible light area array detector receives the reflected light beam to obtain a two-dimensional grayscale image of the scene; target recognition and target analysis are performed on the two-dimensional grayscale image to screen out effective targets; A3: A deep learning-based target detection algorithm is used to process the two-dimensional grayscale image, extract a region of interest corresponding to each effective target, assign a corresponding point cloud density to each region of interest, generate a point cloud coordinate set, and record a scanning phase angle of the optical phased array corresponding to each point to be measured in the point cloud; A4: Based on the scanning phase angle, each coordinate of the point to be measured is mapped to a driving voltage value of the optical phased array and an emission wavelength value of the laser through a pre-set scanning lookup table to generate a control parameter set; 3. The scanning method of the optical phased array lidar system based on a light splitting system according to claim 2, characterized in that, A5: The optical phased array lidar is controlled to sequentially scan the effective targets according to the control parameter set to generate point cloud data. In step A2, target recognition and target analysis are performed on the two-dimensional grayscale image to obtain category and size information of the target; Based on the category and size information of the target, a value coefficient of the target is determined; 4. The scanning method of the optical phased array lidar system based on a light splitting system according to claim 3, characterized in that, Targets whose value coefficients satisfy a pre-set condition are screened as the effective targets. In step A3, the value coefficient of the effective target is used to assign a point cloud density to the corresponding region of interest to realize dense scanning or sparse scanning; The point cloud density is determined by the number of points to be measured per unit area. M: the number of points to be measured in the point cloud in each region of interest i M: the number of points to be measured in the point cloud in each region of interest i M: the number of points to be ； wherein, S is the value coefficient of the region of interest, k is a proportionality coefficient. i S is the area of the region of interest, k is a proportionality coefficient.

5. The scanning method of the optical phased array lidar system based on a light splitting system according to claim 4, characterized in that, According to the region of interest and the number of test points, the test points are uniformly distributed in the form of a dot matrix in the region of interest, and the coordinates of each test point are determined to form a point cloud coordinate set; According to the point cloud coordinate set, the scanning phase angle of the optical phased array corresponding to each test point is calculated.

6. A scanning method of an optical phased array lidar system based on a light splitting system, implemented by the optical phased array lidar system based on the light splitting system of claim 1, used for edge contour recognition of a two-dimensional gray image to obtain a region to be scanned, characterized in that, The method comprises the following steps: B1: The light splitting system separates the incident light beam from the scene into reflected light beams and transmitted light beams; B2: The visible light area array detector receives the reflected light beams to obtain a two-dimensional gray scale image of the scene; Based on the image gray scale difference, an edge contour recognition algorithm is used to extract the edge contour of the target from the two-dimensional gray scale image to obtain a point cloud coordinate set around the edge contour, and the scanning phase angle of the optical phased array corresponding to the test points in the point cloud is recorded; B3: Based on the scanning phase angle, the coordinates of each point in the point cloud are mapped to the driving voltage value of the optical phased array and the emission wavelength value of the laser through a pre-set scanning lookup table, and then a control parameter set is generated; B4: According to the control parameter set, the optical phased array lidar is controlled to scan each edge contour in turn to generate point cloud data.

7. The scanning method of the optical phased array lidar system based on a light splitting system according to claim 6, characterized in that, Step B2 includes: performing digital image processing on the two-dimensional gray scale image, extracting the edge contour of the target based on the gray scale difference between pixels, and obtaining a point cloud coordinate set around the edge contour.

8. The scanning method of the optical phased array lidar system based on a light splitting system according to claim 7, characterized in that, The edge contour recognition algorithm is realized by comparing the gray scale difference between pixels with a preset threshold value and extracting points with a gray scale difference greater than the threshold value to form a contour.

9. The scanning method of the optical phased array lidar system based on a light splitting system according to claim 6, characterized in that, The point cloud coordinate set is generated by using a geometric offset method based on a normal vector or an inflation method based on image morphology.

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