Optical phased array lidar and effective target based scanning method

Abstract

The present application relates to the technical field of laser radar scanning, and particularly relates to an optical phased array laser radar and a scanning method based on effective targets, the scanning method comprising: S1: acquiring a two-dimensional gray scale map of a scene by using a surface array photoelectric detector, and screening out effective targets; S2: extracting a region of interest corresponding to the effective targets, assigning a point cloud density to the region of interest to generate a point cloud coordinate set, and recording a scanning phase angle of an optical phased array corresponding to each to-be-measured point; S3: generating a control parameter set through a pre-set scanning lookup table; S4: controlling the optical phased array laser radar to sequentially scan each region of interest according to the control parameter set, and acquiring three-dimensional point cloud data of the region of interest; and S5: iteratively executing steps S1 to S4. The present application has the advantages that the method reduces redundant data, reduces the complexity of subsequent data processing, and provides technical support for realizing a higher-performance and energy-efficient optical phased array laser radar scanning imaging.

Description

Technical Field

[0001] This invention relates to the field of lidar scanning technology, and in particular to an optical phased array lidar and a scanning method based on effective targets. Background Technology

[0002] Optical phased array (OPA) is a beam pointing technology that dynamically controls the direction, shape, and intensity of a beam by manipulating its phase. OPA lidar, with an OPA chip at its core, integrates laser ranging and imaging technologies. Its phase control primarily relies on two modulation methods: electro-optic and thermo-optic. Electro-optic modulation changes the carrier concentration and refractive index by applying a voltage to the PN junction of the waveguide; thermo-optic modulation achieves phase control by adjusting the temperature through a driving voltage.

[0003] In two-dimensional scanning, the OPA lidar controls the lateral scanning phase angle by driving voltage and simultaneously changes the laser wavelength to achieve longitudinal scanning, thereby covering the entire two-dimensional scene.

[0004] However, existing OPA LiDAR systems require additional photoelectric detection equipment such as cameras to identify ROIs (Regions of Interest), limiting scanning speed. The writing and configuration speeds of control signals, as well as voltage setup speeds, constitute the main bottlenecks, resulting in excessively low frame rates during global scanning, making it difficult to meet the demands of high-speed 3D point cloud acquisition. Furthermore, in practical applications (such as automotive radar), indiscriminate global scanning of low-value areas like the sky and roads not only generates a large amount of redundant data and wastes hardware resources but also further restricts the improvement of detection efficiency and frame rate. Summary of the Invention

[0005] Based on this, this invention proposes an optical phased array lidar and a scanning method based on effective targets. The OPA lidar scanning method uses an internal area array photodetector to image the scene, identify regions of interest, and autonomously guide the scanning process. This improves the detection speed of the optical phased array lidar while reducing hardware resource consumption, effectively eliminating redundant data, and fundamentally reducing the hardware complexity of subsequent data output and processing modules.

[0006] To achieve the above objectives, the technical solution of this invention is implemented as follows: An optical phased array lidar includes: a laser for emitting a laser beam to scan objects in a scene; an optical phased array for controlling the laser beam through phase control to change the direction and shape of the laser beam; a planar photodetector for acquiring a two-dimensional grayscale image of the scene; an image processing module for target recognition of the two-dimensional grayscale image to filter out effective targets and determine the region of interest and point cloud density corresponding to the effective targets; a data processing module for mapping the point cloud coordinates to the driving voltage value of the optical phased array and the emission wavelength value of the laser according to a pre-set scan lookup table, generating a set of control parameters consisting of the driving voltage value and the emission wavelength value; and a control module for controlling the optical phased array lidar to scan the region of interest according to the set of control parameters to obtain point cloud data.

[0007] A scanning method based on effective targets, implemented using the aforementioned optical phased array lidar, includes the following steps:

[0008] S1: The area array photodetector acquires a two-dimensional grayscale image of the scene, and performs target recognition and analysis on the two-dimensional grayscale image to filter out valid targets.

[0009] S2: The deep learning-based target detection algorithm processes the two-dimensional grayscale image, extracts the region of interest corresponding to each valid target, assigns point cloud density to each region of interest, generates a set of point cloud coordinates, and records the optical phased array scanning phase angle corresponding to each test point in the point cloud.

[0010] S3: 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.

[0011] S4: Based on the set of control parameters, control the optical phased array lidar to scan each region of interest in sequence to generate point cloud data.

[0012] Furthermore, step S1 includes: performing target recognition and target analysis on the two-dimensional grayscale image to obtain target category and size information; determining the target value coefficient based on the target category and size information; and filtering targets whose value coefficients meet preset conditions as valid targets.

[0013] Furthermore, in step S2, assigning point cloud density to each region of interest specifically includes:

[0014] Based on the value coefficient of the effective target, the point cloud density is assigned to the corresponding region of interest to achieve dense or sparse scanning; the point cloud density is determined by the number of points to be measured per unit area.

[0015] The number of points to be measured in the point cloud within each region of interest is M. i Calculated using the following formula:

[0016] ;

[0017] in, S represents the value coefficient of the region of interest. i Let k be the area of ​​the region of interest, and k be the scaling factor.

[0018] Furthermore, based on the region of interest and the number of test points, the test points are evenly distributed within the region of interest in the form of a dot matrix, and the coordinates of each test point are determined to form a point cloud coordinate set; based on the point cloud coordinate set, the scanning phase angle of the optical phased array corresponding to each test point is calculated.

[0019] Furthermore, the pre-set scan lookup table in step S3 includes the following steps: driving the optical phased array lidar to scan within the global field of view, recording the lateral angle of each scan phase angle and the corresponding driving voltage value, and establishing a lateral scan lookup table; recording the longitudinal angle of each scan phase angle and the corresponding laser emission wavelength value, and establishing a longitudinal scan lookup table; wherein, the lateral scan lookup table and the longitudinal scan lookup table are used to obtain the corresponding driving voltage value and laser wavelength value according to the coordinate mapping of the target point during the scanning process.

[0020] Furthermore, step S4 includes: the control module sets the emission wavelength of the laser and the driving voltage value of the optical phased array according to the set of control parameters, and controls the optical phased array lidar to perform line-by-line scanning of all test points in the corresponding region of interest.

[0021] This invention achieves the following beneficial effects: It utilizes a phased-array photodetector to acquire a two-dimensional grayscale image of a scene and identifies the region of interest (ROI) within it, thereby guiding an optical phased-array lidar for targeted scanning. This method eliminates the need for additional detection equipment such as cameras to acquire the two-dimensional grayscale image of the scene, simplifying the hardware system and effectively reducing cost and complexity. By preprocessing the two-dimensional grayscale image and leveraging the flexible steering advantage of the optical phased-array, it performs dense scanning of potentially important targets while sparsely scanning or skipping non-important targets, reducing redundant data and lowering the complexity of subsequent data processing.

[0022] This method optimizes resource allocation, concentrating limited detection capabilities on the Region of Interest (ROI), 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. Attached Figure Description

[0023] 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:

[0024] Figure 1 This is a flowchart of a scanning method based on effective targets provided according to an embodiment of the present invention;

[0025] Figure 2 This is a two-dimensional grayscale image of the scanning field of view of an optical phased array lidar provided according to an embodiment of the present invention;

[0026] Figure 3 It is a point cloud density map of the region of interest corresponding to each valid target according to an embodiment of the present invention. Detailed Implementation

[0027] 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.

[0028] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0029] 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.

[0030] 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.

[0031] The invention will now be described in detail with reference to specific embodiments.

[0032] like Figures 1 to 3 As shown in the illustration, an optical phased array lidar provided by this invention includes: a laser, an optical phased array, a planar photodetector, an image processing module, a data processing module, and a control module. The laser emits a laser beam. The optical phased array controls the laser beam through phase control to change its direction and shape. The planar photodetector acquires a two-dimensional grayscale image of the scene. The image processing module performs target recognition and analysis on the two-dimensional grayscale image to filter out effective targets and determine the region of interest and three-dimensional point cloud density corresponding to each effective target. The data processing module maps the three-dimensional point cloud coordinates to the driving voltage value of the optical phased array and the emission wavelength value of the laser according to a pre-set scan lookup table, generating a set of control parameters consisting of the driving voltage value and the emission wavelength value. The control module drives the optical phased array lidar to scan the region of interest according to the set of control parameters to obtain point cloud data.

[0033] A scanning method based on effective targets, utilizing the aforementioned optical phased array lidar, includes the following steps:

[0034] S1: The area array photodetector acquires a two-dimensional grayscale image of the scene, and performs target recognition and analysis on the two-dimensional grayscale image to select at least one valid target.

[0035] Specifically, the area array photodetector acquires a two-dimensional grayscale image of the scene. The image processing module performs target recognition and analysis on the two-dimensional 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).

[0036] 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.

[0037] S2: The deep learning-based target detection algorithm processes the two-dimensional grayscale image, extracts the region of interest corresponding to each valid target, assigns a three-dimensional point cloud density to each region of interest, and generates a set of three-dimensional point cloud coordinates; at the same time, it records the optical phased array scanning phase angle corresponding to each test point in the point cloud.

[0038] 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.

[0039] 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:

[0040] ;

[0041] in, S represents the value coefficient of the region of interest. iLet 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.

[0042] Based on the region of interest and the number of test points, the test points are evenly distributed within the region of interest in the form of a point matrix, 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; at the same time, it records the optical phased array scanning phase angle corresponding to each point to be measured.

[0043] 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.

[0044] 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.

[0045] S3: Based on the scanning phase angle, the data processing module maps the coordinates of each point 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, generating a set of control parameters consisting of the driving voltage value and the emission wavelength value.

[0046] 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 (y-axis) 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.

[0047] The coordinates of the points to be measured for each valid target are (x1, y1), (x2, y2), ..., (x Mi y Mi ), where Mi represents the Mi-th point. A set of control parameters (V1, λ1), (V2, λ2), ..., (V...) is mapped to the driving voltage value and emission wavelength value corresponding to each point using horizontal and vertical scan lookup tables. Mi , λ ri), ri is the row number of the test point in Ri, corresponding to ri scanning wavelengths.

[0048] S4: Based on the set of control parameters, the control module controls the optical phased array lidar to scan each region of interest in sequence, generating three-dimensional point cloud data.

[0049] 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.

[0050] 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 region of interest R1; according to the driving voltage value obtained in step 3, control the OPA to complete the scanning of the first row of test points in the region of interest R1.

[0051] Adjust the laser emission wavelength to λ2, ..., λ r1 Where r1 is the number of rows of points to be measured in the region of interest R1, corresponding to r1 scanning wavelengths. The above process is repeated until all points to be measured in the region of interest R1 are measured.

[0052] Steps S1 to S4 are executed iteratively to continuously generate 3D point cloud data of the region of interest.

[0053] The scanning method based on effective targets of the present invention will be described below with reference to a specific embodiment:

[0054] like Figure 2 As shown, a target detection algorithm is used to process the original two-dimensional grayscale image acquired by an area array photodetector, identifying and extracting the effective targets TE1 and TE2. Simultaneously, the regions of interest R1 and R2 corresponding to the effective targets TE1 and TE2 are determined. The value coefficient of region of interest R1 is higher than that of region of interest R2.

[0055] Dense scanning is performed on region of interest R1 based on value coefficients, and the number of test points in region of interest R1 is defined as r1×c1; sparse scanning is performed on region of interest R2, and the number of test points in region of interest R2 is defined as r2×c2, where r1 and c1 are the number of rows and columns of test points in region of interest R1, respectively, and r2 and c2 are the number of rows and columns of test points in region of interest R2, respectively.

[0056] like Figure 3As shown, firstly, the laser wavelength is set to λ11. Under this wavelength condition, the optical phased array sequentially applies a set of driving voltages V11, V12, ..., V1c1, each corresponding to a test point in the first row, to achieve sequential scanning of all test points in that row. Subsequently, for each subsequent row in the region of interest R1, the laser wavelength is sequentially switched to λ12, ..., λ1r1, and the optical phased array continues to use the driving voltages V11, ..., V1c1 matched to the first row. These are applied in the same order to complete the row scan. The row scan process is repeated once a new set of parameters is configured, until all test points in all rows within the region of interest R1 are measured.

[0057] After completing the scan of region of interest R1, the scan of region of interest R2 is then performed. At this time, the laser wavelengths are sequentially set to λ21, ..., λ2r2, and the optical phased array is synchronously switched to driving voltages V21, ..., V2c2 corresponding to the positions of each test point in region of interest R2. The driving voltage applied to the test points at each corresponding position in each row of region of interest R2 remains consistent. For each set of wavelength and voltage parameters, a complete row scan is performed until all test points within region of interest R2 have been measured.

[0058] Table 1. Correspondence between the measurement point in region of interest R1 and the driving voltage and emission wavelength.

[0059]

[0060] As shown in Table 1, taking the region of interest R1 as an example, the specific scanning order is (x11, y11), (x12, y11), ..., (x1c1, y11); (x11, y12), (x12, y12), ..., (x1c1, y12); ...; (x11, y1r1), (x12, y1r1), ..., (x1c1, y1r1). Where (x11, y11) represents the coordinates of the point to be measured in the first row and first column of the region of interest R1; (x12, y11) represents the coordinates of the point to be measured in the first row and second column of the region of interest R1; ..., (x1c1, y11) represents the coordinates of the point to be measured in the first row and c1 column of the region of interest R1; (x11, y12) represents the coordinates of the point to be measured in the second row and first column of the region of interest R1; and (x12, y12) represents the coordinates of the point to be measured in the second row and first column of the region of interest R1. The coordinates of the point to be measured in the second row and second column of R1, ..., (x1c1, y12) are the coordinates of the point to be measured in the second row and c1 column of the region of interest R1; ...; (x11, y1r1) are the coordinates of the point to be measured in the first column of the first row of the region of interest R1, (x12, y1r1) are the coordinates of the point to be measured in the second column of the first row of the region of interest R1, ..., (x1c1, y1r1) are the coordinates of the point to be measured in the first column of the first row of the region of interest R1, ..., (x1c1, y1r1) are the coordinates of the point to be measured in the first column of the first row of the region of interest R1.

[0061] Through the above process, the optical phased array lidar generates 3D point cloud data for all regions of interest. Once all designated target areas have been scanned, the system will cycle back to the initial step: the area array photodetector will again acquire a 2D grayscale image of the scene, performing a new round of target recognition and adaptive scanning, thereby achieving continuous updating of the 3D point cloud data for the regions of interest.

[0062] In summary, the effective target-based scanning method of this invention utilizes a planar array photodetector to acquire a two-dimensional grayscale image of the scene and identifies the region of interest (ROI) within it, thereby guiding an optical phased array lidar for targeted scanning. This method eliminates the need for additional detection equipment such as cameras to acquire a two-dimensional grayscale image of the scene, simplifying the hardware system and effectively reducing cost and complexity.

[0063] By preprocessing the two-dimensional grayscale image and leveraging the flexible steering advantage of the optical phased array, dense scanning of potentially important targets is performed, while sparse scanning or skipping of less important targets is performed. This reduces redundant data and lowers the complexity of subsequent data processing.

[0064] 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.

[0065] 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. A scanning method based on effective targets, implemented using an optical phased array lidar, characterized in that, Includes the following steps: S1: The area array photodetector acquires a two-dimensional grayscale image of the scene, and performs target recognition and target analysis on the two-dimensional grayscale image to filter out valid targets; S2: The deep learning-based target detection algorithm processes the two-dimensional grayscale image, extracts the region of interest corresponding to each effective target, assigns point cloud density to each region of interest, generates a set of point cloud coordinates, and records the optical phased array scanning phase angle corresponding to each test point in the point cloud. S3: Based on the scanning phase angle, the coordinates of each point to be tested 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; S4: Based on the set of control parameters, control the optical phased array lidar to scan each of the regions of interest sequentially to generate point cloud data.

2. The scanning method based on effective targets according to claim 1, characterized in that, Step S1 includes performing target recognition and target analysis on the two-dimensional grayscale image to obtain target category and size information; Based on the target's category and size information, determine the target's value coefficient; Targets whose value coefficients meet preset conditions are selected as valid targets.

3. The scanning method based on effective targets according to claim 2, characterized in that, In step S2, assigning point cloud density to each region of interest specifically includes: Based on the value coefficient of the effective target, point cloud density is allocated to the corresponding region of interest to achieve dense or sparse scanning; the point cloud density is determined by the number of points to be measured per unit area. The number of points to be measured in the point cloud within each region of interest is M. i Calculated using the following formula: ； in, S is the value coefficient of the region of interest. i Let k be the area of ​​the region of interest, and k be the scaling factor.

4. The scanning method based on effective targets according to claim 3, characterized in that, Based on the region of interest and the number of points to be measured, the points to be measured are evenly distributed in the region of interest in the form of a dot matrix, and the coordinates of each point to be measured are determined to form a point cloud coordinate set. Based on the point cloud coordinate set, calculate the scanning phase angle of the optical phased array corresponding to each point to be measured.

5. The scanning method based on effective targets according to claim 1, characterized in that, The pre-set scan lookup table in step S3 includes the following steps: The optical phased array lidar is driven to scan within the global field of view, and the lateral angle of each scanning phase angle and the corresponding driving voltage value are recorded to establish a lateral scan lookup table. Record the longitudinal angle of each scanning phase angle and the corresponding laser emission wavelength value, and establish a longitudinal scanning lookup table; The horizontal scan lookup table and the vertical scan lookup table are used to obtain the corresponding driving voltage value and laser wavelength value according to the coordinate mapping of the target point during the scanning process.

6. The scanning method based on effective targets according to claim 5, characterized in that, Step S4 includes: The control module sets the emission wavelength value of the laser and the driving voltage value of the optical phased array according to the set of control parameters, and controls the optical phased array lidar to scan all test points in the region of interest line by line.

7. An optical phased array lidar for implementing the scanning method based on an effective target as described in claim 1, characterized in that, include: A laser is used to emit a laser beam to scan objects in a scene. An optical phased array is used to control a laser beam through phase control, thereby changing the direction and shape of the laser beam; A planar photodetector is used to acquire a two-dimensional grayscale image of the scene. The image processing module is used to perform target recognition on the two-dimensional grayscale image to filter out effective targets from the targets and determine the region of interest and point cloud density corresponding to the effective targets. The data processing module is used to map the point cloud coordinates to the driving voltage value of the optical phased array and the emission wavelength value of the laser according to the pre-set scanning lookup table, and generate a set of control parameters consisting of the driving voltage value and the emission wavelength value. The control module is used to control the optical phased array lidar to scan the region of interest according to the set of control parameters, so as to obtain point cloud data.

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