Method and device for orientation measurement based on optical compound eye sparse coding and contour detection

Abstract

The application relates to the technical field of target direction measurement, in particular to a direction measurement method and device based on optical compound eye sparse coding and profile detection, wherein the method comprises the following steps: acquiring light intensity profile data of an incident light spot, and generating corresponding light intensity vectors; determining a connected domain segmentation threshold of the light intensity profile data, and extracting sampling points with light intensity values satisfying preset conditions to determine one-dimensional connected domains and calculate one-dimensional light spot coordinate vectors; calculating the distance between adjacent light spots based on the one-dimensional light spot coordinate vectors to obtain mutual distance vectors, and determining light spots in the same sub-view field according to the mutual distance vectors to construct the spatial coding of the light spots; acquiring a sub-view field pattern according to the spatial coding to determine light spot pixel coordinates and absolute spatial pixel coordinates, and determining the direction of a light source according to the light spot pixel coordinates and the absolute spatial pixel coordinates. Thus, the problem that the conventional multi-aperture structure is easily disturbed, the corresponding relationship of the light spots is unstable, and the direction calculation accuracy of a target is affected is solved.

Description

Technical Field

[0001] This application relates to the field of target orientation measurement technology, and in particular to an orientation measurement method and apparatus based on optical compound eye sparse coding and contour detection. Background Technology

[0002] In related technologies, existing target orientation measurement devices generally adopt a digital imaging structure. This involves an optical imaging component imaging the incident light from the target onto a two-dimensional image detector. A processor then analyzes the position or shape of the light spot to determine the incident direction. The photoelectric conversion part of this type of system mainly consists of an optical system and an image detector. Its basic measurement principle is to use an optical imaging model to form an image point on the image plane from the radiated or reflected light from the target. The straight line connecting the centroid of the image point and the optical center of the optical system corresponds to the incident direction of the target. Based on different optical imaging methods, traditional imaging angle measurement systems can be divided into two main categories: lens-type and aperture-type. Lens-type systems typically consist of multiple lens groups and are typical single-aperture systems. They can converge light and form a high-resolution light spot with a large aperture, but their optical structure is complex, manufacturing costs are high, and the field of view decreases with the length of the modulator's working distance, making it difficult to simultaneously achieve a large field of view and high resolution. Aperture systems rely on tiny openings or structured blocking elements to form diffraction spots, and direction is calculated through the geometric correspondence between the aperture center and the spot center. Although the structure is simple and easy to miniaturize, the common single-aperture target direction measurement system is also subject to the inherent contradiction of not being able to simultaneously achieve the desired field of view and resolution. In order to overcome the limitations of single-aperture structures in terms of accuracy improvement, some technical solutions have tried to use multi-aperture structures, introducing multiple independent optical paths to enhance geometric constraints and cancel random noise.

[0003] However, conventional multi-aperture structures generate multiple light spots on the image detector. Since the position of these spots is easily affected by platform maneuvers, noise interference, brightness variations, and optical path conditions, it is often difficult to establish a robust correspondence between light spots generated by different apertures. This leads to uncertainty in the matching process, thus limiting the reliability and accuracy of target orientation calculation. Furthermore, both the lens-based and aperture-based classical schemes mentioned above rely on two-dimensional image detectors for complete image readout. Their frame rate, data processing volume, and power consumption are limited by the readout link, making it difficult to simultaneously meet real-time and stability requirements in scenarios involving high-speed targets, strong maneuvering attitude changes, or platforms with limited resources and power sensitivity. Therefore, it is necessary to introduce multi-aperture structures with coding characteristics. By establishing deterministic identifiers and constraints at the aperture level, ambiguities in multi-spot matching can be eliminated at the source, thereby improving the robustness and accuracy of target orientation measurement. Summary of the Invention

[0004] This application provides a method and apparatus for orientation measurement based on optical compound eye sparse coding and contour detection, in order to solve the problems in related technologies, such as the instability of light spot correspondence caused by the easy interference of conventional multi-aperture structures, which affects the accuracy of target orientation calculation, and the fact that traditional solutions rely on full-frame readout of two-dimensional image detectors, which are limited by frame rate, data volume and power consumption, making it difficult to meet the requirements of real-time performance and stability in high-speed, high-mobility and resource-constrained scenarios.

[0005] The first aspect of this application provides a method for azimuth measurement based on optical compound eye sparse coding and contour detection. The azimuth measurement device includes a photodetector and an optical compound eye sparse encoder. The method includes: forming an incident light spot through the photodetector and acquiring light intensity contour data of the incident light spot, generating a corresponding light intensity vector based on the light intensity contour data; determining a connected component segmentation threshold of the light intensity contour data based on the light intensity vector, and extracting sampling points in the light intensity vector whose light intensity values ​​satisfy preset conditions according to the connected component segmentation threshold, determining a one-dimensional connected component of the incident light spot based on the sampling points, and determining the one-dimensional connected component based on the one-dimensional connected component. A one-dimensional light spot coordinate vector is calculated; based on the one-dimensional light spot coordinate vector, the distance between adjacent light spots in the one-dimensional connected domain is calculated to obtain the mutual distance vector between the light spots, and the light spots in the same sub-field of view are determined according to the mutual distance vector, so as to construct the spatial code of the light spot based on the mutual distance relationship of the light spots in the same sub-field of view; the corresponding sub-field of view pattern in the compound eye sparse encoder is obtained according to the spatial code, so as to determine the light spot pixel coordinates and the absolute spatial pixel coordinates of the aperture in the sub-field of view corresponding to the light spot based on the sub-field of view pattern, and the light source orientation is determined according to the light spot pixel coordinates and the absolute spatial pixel coordinates.

[0006] Optionally, in one embodiment of this application, determining the light source orientation based on the spot pixel coordinates and the absolute spatial pixel coordinates includes: calculating the dual-axis orientation angle and orientation vector of the aperture within the sub-field of view based on the spot pixel coordinates and the absolute spatial pixel coordinates, and determining the light source orientation based on the dual-axis orientation angle and orientation vector.

[0007] Optionally, in one embodiment of this application, the biaxial orientation angle and orientation vector of the aperture within the sub-field of view are calculated using the following formulas, including: , , , in, i x_ij , i y_ij They respectively represent the results in the orthogonal directions according to the first... j Within the field of view of each individuali The direction angle is calculated from each aperture and its spot size. x s_ij , y s_ij Indicates the first j Within the field of view of each individual i The pixel coordinates of the light spot formed by the aperture on the photodetector in two orthogonal directions. x a_ij , y a_ij Indicates the first j Within the field of view of each individual i The absolute spatial pixel coordinates of each aperture in two orthogonal directions on an optical compound eye sparse encoder. h Indicates the preset working distance. Represents the direction vector. k Represents direction vector The third component.

[0008] Optionally, in one embodiment of this application, determining the orientation of the light source further includes: performing a direction vector fusion process; when the light source is a parallel light source, calculating the average value of the direction vectors to determine the incident direction of the light source based on the average value; when the light source is a point light source, determining the three-dimensional spatial position coordinates of the point light source by minimizing the sum of the orthogonal distances from the spatial point corresponding to the point light source to each spatial ray; and determining the orientation of the light source based on the incident direction and the three-dimensional spatial position coordinates.

[0009] Optionally, in one embodiment of this application, the formula for calculating the incident direction is: , , , in, Indicates the incident direction of a parallel light source. m This indicates the number of sub-fields of view contained in the contour data. n This indicates the number of apertures contained in each sub-field pattern. i x , i y It represents the direction angle in two orthogonal directions.

[0010] Optionally, in one embodiment of this application, the formula for calculating the three-dimensional spatial position coordinates is: , in, I Represents the identity matrix, ( I v ij v ij T () represents the projection matrix used to calculate the orthogonal distance from a spatial point to its corresponding spatial ray. p ij Indicates the first j Within the field of view of each individual i The known position vector of each aperture in space v ij Indicates the first j Within the field of view of each individual i The direction vector obtained from aperture imaging.

[0011] Optionally, in one embodiment of this application, the orientation measurement device further includes: an optical modulation device disposed at the front end of the optical compound eye sparse encoder, used to modulate the spectral characteristics, intensity distribution, phase characteristics, polarization state, wavefront morphology and / or transmission characteristics of the incident light; wherein, the photodetector is disposed at the rear end of the optical compound eye sparse encoder.

[0012] A second aspect of this application provides a orientation measurement device based on optical compound eye sparse coding and contour detection, comprising: an acquisition module, configured to form an incident light spot using a photodetector and acquire light intensity contour data of the incident light spot, so as to generate a corresponding light intensity vector based on the light intensity contour data; and a calculation module, configured to determine a connected component segmentation threshold of the light intensity contour data based on the light intensity vector, and extract sampling points in the light intensity vector whose light intensity values ​​satisfy preset conditions according to the connected component segmentation threshold, so as to determine a one-dimensional connected component of the incident light spot based on the sampling points, and calculate a one-dimensional light spot coordinate vector based on the one-dimensional connected component; and construct... The module is used to calculate the distance between adjacent light spots in the one-dimensional connected domain based on the one-dimensional light spot coordinate vector, so as to obtain the mutual distance vector between the light spots, and to determine the light spots in the same sub-field of view based on the mutual distance vector, so as to construct the spatial code of the light spots based on the mutual distance relationship of the light spots in the same sub-field of view; the measurement module is used to obtain the corresponding sub-field of view pattern in the compound eye sparse encoder according to the spatial code, so as to determine the light spot pixel coordinates and the absolute spatial pixel coordinates of the aperture in the sub-field of view corresponding to the light spot based on the sub-field of view pattern, and to determine the light source orientation according to the light spot pixel coordinates and the absolute spatial pixel coordinates.

[0013] Optionally, in one embodiment of this application, the measurement module includes: a first calculation unit, configured to calculate the dual-axis orientation angle and orientation vector of the aperture within the sub-field of view based on the light spot pixel coordinates and the absolute spatial pixel coordinates, and determine the orientation of the light source based on the dual-axis orientation angle and orientation vector.

[0014] Optionally, in one embodiment of this application, the biaxial orientation angle and orientation vector of the aperture within the sub-field of view are calculated using the following formulas, including: , , , in, i x_ij , i y_ij They respectively represent the results in the orthogonal directions according to the first... j Within the field of view of each individual i The direction angle is calculated from each aperture and its spot size. x s_ij , y s_ij Indicates the first j Within the field of view of each individual i The pixel coordinates of the light spot formed by the aperture on the photodetector in two orthogonal directions. x a_ij , y a_ij Indicates the first j Within the field of view of each individual i The absolute spatial pixel coordinates of each aperture in two orthogonal directions on an optical compound eye sparse encoder. h Indicates the preset working distance. Represents the direction vector. k Represents direction vector The third component.

[0015] Optionally, in one embodiment of this application, the measurement module further includes: a second calculation unit, configured to perform fusion processing on the direction vectors, and when the light source is a parallel light source, calculate the average value of the direction vectors to determine the incident direction of the light source based on the average value; a third calculation unit, configured to determine the three-dimensional spatial position coordinates of the point light source by minimizing the sum of the orthogonal distances from the spatial point corresponding to the point light source to each spatial ray when the light source is a point light source; and a determination unit, configured to determine the orientation of the light source based on the incident direction and the three-dimensional spatial position coordinates.

[0016] Optionally, in one embodiment of this application, the formula for calculating the incident direction is: , , , in, Indicates the incident direction of a parallel light source. mThis indicates the number of sub-fields of view contained in the contour data. n This indicates the number of apertures contained in each sub-field pattern. i x , i y It represents the direction angle in two orthogonal directions.

[0017] Optionally, in one embodiment of this application, the formula for calculating the three-dimensional spatial position coordinates is: , in, I Represents the identity matrix, ( I v ij v ij T () represents the projection matrix used to calculate the orthogonal distance from a spatial point to its corresponding spatial ray. p ij Indicates the first j Within the field of view of each individual i The known position vector of each aperture in space v ij Indicates the first j Within the field of view of each individual i The direction vector obtained from aperture imaging m This indicates the number of sub-fields of view contained in the contour data. n This indicates the number of apertures contained in each sub-field pattern.

[0018] Optionally, in one embodiment of this application, the orientation measurement device further includes: an optical modulation device disposed at the front end of the optical compound eye sparse encoder, used to modulate the spectral characteristics, intensity distribution, phase characteristics, polarization state, wavefront morphology and / or transmission characteristics of the incident light; wherein, the photodetector is disposed at the rear end of the optical compound eye sparse encoder.

[0019] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the orientation measurement method based on optical compound eye sparse coding and contour detection as described in the above embodiments.

[0020] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the orientation measurement method based on optical compound eye sparse coding and contour detection as described above.

[0021] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0022] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a orientation measurement method based on optical compound eye sparse coding and contour detection provided according to an embodiment of this application; Figure 2 This is a schematic diagram of the orientation measurement device based on optical spatial coding and contour detection according to a specific embodiment of this application; Figure 3 This is a pattern design layout for an optical compound eye sparse encoder according to a specific embodiment of this application; Figure 4 This is a schematic diagram of a single sub-field of view according to a specific embodiment of this application; Figure 5 This is a schematic diagram of a pixel distance coding grid according to a specific embodiment of this application; Figure 6 This is a schematic diagram showing the actual output of a contour detector and the results of two-dimensional image reconstruction and field of view matching according to a specific embodiment of this application; Figure 7 This is a schematic diagram of an orientation measurement device based on optical compound eye sparse coding and contour detection according to an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0023] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0024] The following description, with reference to the accompanying drawings, describes an orientation measurement method and apparatus based on optical compound eye sparse coding and contour detection according to embodiments of this application. Addressing the issues raised in the background section regarding conventional multi-aperture structures being susceptible to interference leading to unstable spot correspondence and affecting target orientation calculation accuracy, and the reliance on full-frame readout from two-dimensional image detectors, which are limited by frame rate, data volume, and power consumption, making it difficult to simultaneously meet real-time and stability requirements in high-speed, high-maneuverability, and resource-constrained scenarios, this application provides an orientation measurement method based on optical compound eye sparse coding and contour detection. In this method, an optical compound eye sparse coding structure can be employed. By designing the spatial arrangement of multiple apertures or sub-fields of view within the coding plane, the apertures or sub-fields of view can be spatially... This method exhibits a non-dense, distinguishable sparse distribution, enabling different incident rays to form uniquely geometrically shaped light spot profiles on the photodetector. This achieves sparse spatial encoding of the incident direction information at the optical level. Based on this, a contour detection method is used to obtain the one-dimensional intensity distribution characteristics of the light spot in two orthogonal directions (rows and columns). This transforms the traditional orientation resolution process, which relies on two-dimensional imaging, into an orientation calculation process based on one-dimensional contour signals, significantly reducing data dimensionality and computational complexity. Furthermore, the electronic system utilizes the contour features to match the light spot with the compound eye's field of view or aperture, and calculates the target's incident direction. This method achieves large field of view, high resolution, fast speed, and low power consumption orientation measurement without complex image processing, making it particularly suitable for power-sensitive applications and applications with high dynamic performance requirements, such as micro / nano satellites and drones.

[0025] Figure 1 This is a flowchart illustrating a method for orientation measurement based on optical compound eye sparse coding and contour detection, provided in an embodiment of this application.

[0026] like Figure 1 As shown, the orientation measurement method based on optical compound eye sparse coding and contour detection includes the following steps: In step S101, an incident light spot is formed by a photodetector, and the light intensity profile data of the incident light spot is acquired, so as to generate a corresponding light intensity vector based on the light intensity profile data.

[0027] Among them, orientation measurement can be achieved by setting up corresponding orientation measurement equipment, which may include photoelectric detectors and optical compound eye sparse encoders.

[0028] Optionally, in one embodiment of this application, the orientation measurement device may further include: an optical modulation device disposed at the front end of the optical compound eye sparse encoder, used to modulate the spectral characteristics, intensity distribution, phase characteristics, polarization state, wavefront morphology and / or transmission characteristics of the incident light; wherein, a photodetector is disposed at the rear end of the optical compound eye sparse encoder.

[0029] Specifically, as one feasible approach, the structure of the orientation measuring device is as follows: Figure 2 As shown, the device includes mechanical, optical, and electronic components. The mechanical components include a mechanical housing 101, a mechanical base 102, an outer pressure plate 103, an optical modulation device base 104, and an optical compound eye sparse encoder base 105. The optical components include an optical modulation device 201 and an optical compound eye sparse encoder 202. The electronic components include a photodetector 301, an electronics system 302, and an electrical connection unit 303. In practical implementation, this orientation measurement device may also include fasteners for structural assembly and fixation, such as screws (not shown in the figure). All components work together to acquire, code-match, and calculate the incident light spot contour information and incident direction.

[0030] Among them, the optical modulation device 201 is located at the front end of the optical compound eye sparse encoder 202, and the photodetector 301 is located at the rear end of the optical compound eye sparse encoder 202. The three together constitute the core components of the optical path in the orientation measurement device.

[0031] An optical modulation device 201 can be disposed at the front end of the optical path to modulate the spectral characteristics, intensity distribution, phase characteristics, polarization state, wavefront morphology, and / or transmission characteristics of the incident light, thereby suppressing ambient stray light, optimizing the energy distribution of the incident light, and improving the system signal-to-noise ratio. An optical compound eye sparse encoder 202 can be provided with multiple sets of apertures, each set of apertures can be arranged according to preset rules to form a pattern structure with unique spatial coding characteristics, so that the incident light, after being encoded and modulated, forms a distinguishable light spot contour distribution with unique spatial coding characteristics on the photodetector. The photodetector 301 and the electronic system 302 can be used to generate, acquire, and process the light spot contour information, calculate the centroid position of the target light spot, and complete the matching of the light spot with the sub-field pattern and aperture according to preset field-of-view coding rules, thereby obtaining the orientation information of a single target light source relative to the device. The electrical connection unit 303 can be used to realize information interaction and energy supply between various functional modules within the device and between the device and external devices to support the normal operation of the device; it can be in wired or wireless form. Mechanical components can be used to install, position, and fix the various functional units to ensure the overall structural stability and optical alignment accuracy of the system.

[0032] In this process, the incident light rays are modulated by different apertures on the optical compound eye sparse encoder 202, forming multiple imaging light spot responses on the surface of the photodetector 301. The spatial arrangement of each aperture in the optical compound eye sparse encoder 202 is pre-designed so that the corresponding light spots have a distinguishable relative positional relationship on the detector surface, thereby forming a light spot distribution pattern with specific spatial coding.

[0033] Furthermore, a protective structure and / or protective coating can be installed on the outside of the equipment to provide environmental protection capabilities, including but not limited to dustproof, moisture-proof, waterproof, corrosion-proof, radiation-proof, electromagnetic interference-proof, stray light-proof, anti-static, impact-resistant, vibration-resistant, and thermal protection. The specific structural form, material type, installation location, and implementation method of the protective structure and / or protective coating are not specifically limited here; they can be implemented using an outer shell structure, sealing structure, shielding structure, coating structure, multi-layer composite structure, or equivalent forms.

[0034] The overall shape and size of the optical compound-eye sparse encoder 202 are not limited and can be designed according to the system structure layout, field of view requirements, and processing conditions. The optical compound-eye sparse encoder 202 can adopt an axisymmetric or centrosymmetric geometric structure, and its specific form can be a planar geometric structure with a closed contour, such as a structure composed of straight boundaries, curved boundaries, or a combination of both. Its shape and dimensional parameters can be selected and determined according to specific application requirements and manufacturing process feasibility. After determining the overall shape and size, the optical compound-eye sparse encoder 202 can be processed using microelectromechanical systems (MEMS) technology. Specifically, a layer of chromium can be deposited on a quartz glass substrate, then patterned using photolithography to transfer the aperture pattern onto the chromium layer, and finally the aperture pattern is etched.

[0035] Furthermore, multiple sets of sub-field aperture patterns can be arrayed on the optical compound eye sparse encoder 202, and the sub-fields are spliced ​​together to form the overall field of view. Among them, a single sub-field adopts a long modulator working distance optical configuration to obtain higher angular resolution, thereby taking into account both field of view range and resolution. Each sub-field of view may include several apertures arranged in a predetermined direction (e.g., an inclined direction) within the plane of the optical compound eye sparse encoder 202. The spacing between adjacent apertures in two orthogonal directions may be all the same, all different, or partially the same. The aforementioned spacing relationship is used to construct spatial coding features that distinguish different sub-fields of view. The geometry of the apertures may be set to rectangles. The dimensional parameters of each aperture may be the same or different in one or more directions. For example, the apertures may have the same minor axis dimension but different major axis dimensions to optimize the roundness of the imaging spot; the same major axis dimension but different minor axis dimensions, or different major axis dimensions and minor axis dimensions at the same time, to form a spot feature with field of view distinction. The major axis direction of the aperture is consistent with or substantially consistent with the direction of the line connecting the center of the aperture to the center of the overall pattern of the optical compound eye sparse encoder 202 to optimize the imaging effect of the sub-field of view.

[0036] The optical compound eye sparse encoder divides the overall field of view into multiple sub-fields of view and encodes them spatially. Light rays from different incident directions can excite different aperture combinations and their spot distribution characteristics, thereby effectively expanding the overall field of view without significantly increasing the detector size and the number of pixels. At the same time, individual sub-fields of view can be configured to achieve high resolution, thus enabling the co-detection of high resolution and a large field of view.

[0037] In one embodiment of this application, the overall pattern of the optical compound eye sparse encoder 202 can be configured to be formed by stitching together 27 sub-field patterns in the encoder plane, each sub-field pattern corresponding to a different field of view region, such as... Figure 3 As shown. In this embodiment, the pattern of a single sub-field of view can be composed of two rectangular apertures. The two rectangular apertures are arranged in an inclined manner in the plane of the optical compound eye sparse encoder 202, and the line connecting their aperture centers is inclined at a certain angle relative to the horizontal direction. Under the direction definition adopted in this embodiment, the inclined direction is that the whole is offset downward when extending from left to right. The optical compound eye sparse encoder 202 has a rectangular structure, and an assembly mark is provided at its upper right corner to indicate the direction reference of the encoder so as to determine the spatial orientation of the pattern during assembly and calibration.

[0038] As another feasible approach, the aperture in the optical compound eye sparse encoder 202 can be integrated with a lens structure. This lens structure includes, but is not limited to, conventional refractive lenses, microlens arrays, superlenses, or any combination thereof. The geometry of the lens or microlens is not limited and can be one or more of the following: spherical, aspherical, ellipsoidal, parabolic, freeform, or multifaceted composite surfaces. The superlens can be composed of subwavelength-scale nanostructures. The shape, size, period, arrangement, and material type of these nanostructures are not limited and can be columnar, grooved, annular, cross-shaped, polygonal, or any other structural form capable of phase modulation. Any optical structure capable of wavefront modulation, focusing, or encoding of incident light can be used as an equivalent implementation of the aperture.

[0039] Furthermore, the aperture on the optical compound eye sparse encoder 202 can be a regular or irregular planar graphic structure, and its geometry is not specifically limited herein. In one or more embodiments, the geometry of the aperture may include rectangle, ellipse, circle, polygon, rounded polygon, strip, spindle, rhombus, racetrack, sector, or any combination thereof.

[0040] In one embodiment of this application, the major and minor axis dimensions of the rectangular aperture in the optical compound eye sparse encoder 202 change with the position of the sub-field of view in the overall field of view. Specifically, the major axis dimension gradually increases outward from the center of the field of view, while the minor axis dimension gradually decreases outward from the center of the field of view; and both the increase and decrease of the major axis dimension are non-uniform changes. The direction of the major axis of the rectangular aperture is parallel or approximately parallel to the direction of the line connecting the center of the aperture to the center of the overall pattern of the optical compound eye sparse encoder 202 (as the origin of the coordinate system). The center-to-center spacing of adjacent rectangular apertures in the row and column orthogonal directions is pre-designed and encoded, so that the relative positional relationship between the imaging spots formed on the photodetector 301 has spatial coding characteristics corresponding to the aperture arrangement, such as... Figure 4 As shown.

[0041] In one embodiment of this application, the optical compound eye sparse encoder 202 can encode spatial information according to the following rules:

[0042]

[0043] In the formula, [ Code x , Code y ] is pixel distance encoding; [ L x , L y ] is the physical distance code; l pixel It refers to pixel size; L s It is the safe pixel spacing that does not cause interference, and the safe pixel spacing is determined through numerical simulation.

[0044] A spatial coding grid is constructed based on the above coding formula, and each coding element in the grid is unique. In one implementation, the parameters used to define the coding grid include at least the positive first element, the negative first element, and the coding step size; wherein, the spatial coding of the central field of view is always set to (0, 0), thereby forming a simple field of view coding grid without repeated elements. For example, when the positive first element is 10, the negative first element is 5, and the step size is 10, an exemplary coding grid can be formed, such as... Figure 5 As shown. It should be noted that while increasing the encoding value can improve the robustness of the field-of-view recognition algorithm, it also leads to an increase in the size of the pattern group corresponding to a single sub-field of view. This necessitates stitching together more sub-fields of view to form the overall field of view. Therefore, in practical design, a trade-off must be struck between recognition robustness and system complexity. Subsequently, the physical distance encoding is determined based on the field-of-view encoding.L x , L y [, to determine the actual physical spacing of the actual pattern.]

[0045] Regarding the photodetector 301 in the aforementioned orientation measurement device, it is preferably a detection device capable of directly outputting information related to the light spot contour, such as a contour detector. This type of device can output spatial distribution information of light intensity along the row and column directions respectively, thereby characterizing the contour features of the incident light spot in one-dimensional data form. By directly obtaining the one-dimensional light intensity distribution vectors in the row and column directions, pixel-by-pixel reading and processing of the complete two-dimensional image can be avoided, reducing data processing complexity, improving signal processing speed, and reducing overall system power consumption. The output data format of the photodetector 301 is as follows: Figure 6 As shown, the two sets of one-dimensional light intensity distribution vectors located at the bottom and right are the actual output results of the photodetector 301; the image located at the top left is a schematic result of the light spot distribution obtained by reconstructing based on the one-dimensional light intensity distribution vector and combining it with the field of view matching algorithm.

[0046] As another possible approach, the photodetector 301 can also be an image detector with row and column accumulation output function, or the acquisition of light spot contour information can be achieved by setting a corresponding row and column accumulation circuit around the image detector. No limitation is made here.

[0047] Similarly, the embodiments of this application do not limit the external shape of the photodetector 301, which can be designed according to system integration requirements. For example, the photodetector 301 has a rectangular structure, but in other embodiments, it can also adopt an axisymmetric or centrally symmetric geometry.

[0048] The photodetector 301 can be positioned below the optical path of the optical compound eye sparse encoder 202. The size of its effective photosensitive area is preferably smaller than the overall size of the optical compound eye sparse encoder 202. It is used to receive the incident light modulated by the optical compound eye sparse encoder 202 and form a corresponding imaging response.

[0049] In one embodiment of this application, the line connecting the geometric center of the overall aperture pattern of the optical compound eye sparse encoder 202 and the center of the photosensitive area of ​​the photodetector 301 is preferably substantially perpendicular to the plane in which the optical compound eye sparse encoder 202 and the photodetector 301 are located, and a certain assembly deviation is allowed.

[0050] Furthermore, the electronic system 302 is electrically connected to the photodetector 301, used to read, process, and calculate the optical signals acquired by the photodetector, and to execute corresponding control and data output according to external input commands. The electrical connection unit 303 is used to realize the electrical connection and information exchange between the measuring device and external devices.

[0051] Specifically, the electronic system 302 can be used to acquire, process, and calculate the contour data output by the photodetector 301 to obtain the orientation information of the incident light from the target. It may include a processing unit and a storage unit. The processing unit is configured to perform contour data analysis, centroid calculation, and multi-aperture joint matching calculation.

[0052] The electronic system 302 can also be implemented based on a microcontroller, digital signal processor, field-programmable gate array, system-on-a-chip, or any combination thereof. Its specific hardware structure and software implementation can be adjusted according to application requirements, and are not specifically limited in the embodiments of this application.

[0053] Mechanical components are used to install, position, and fix optical and electronic components to ensure the stability of the relative positional relationship between the components and to improve the overall structural stability and reliability of the measuring equipment.

[0054] The mechanical component may have an optical opening in the optical axis direction for the incident of target light to define the effective detection field of the optical system, and an interface area in the non-optical axis direction for the electrical connection unit 303 to connect with an external system.

[0055] Furthermore, the optical modulation device 201 is disposed in the incident optical path of the optical compound eye sparse encoder 202, and its plane is basically parallel to the plane of the optical compound eye sparse encoder 202; under the premise of satisfying the system imaging and modulation functions, a certain installation angle or position error is allowed between the two.

[0056] Specifically, the optical modulator 201 can be disposed on the top layer of the orientation measurement device and fixed by the outer pressure plate 103. It is used to perform spectral selection on the incident light entering the device, ensuring that light signals within the target spectral range can effectively reach and image onto the detector surface, thereby reducing the influence of stray ambient light on the measurement process. The external shape of the optical modulator 201 is not a necessary limitation for achieving the technical effect of this application; it is preferably configured to match the shape of the optical compound eye sparse encoder 202. The optical modulator 201 is preferably a planar optical structure with its upper and lower surfaces parallel to each other, avoiding the introduction of additional light refraction errors, thus helping to ensure the accuracy of orientation measurement.

[0057] The optical modulation device 201 is not essential and can be selectively configured according to specific application requirements. In one or more embodiments, the optical modulation device 201 can be disposed on the surface or inside the optical compound eye sparse encoder 202 in the form of an optical coating, forming an integrated structure with the optical compound eye sparse encoder 202. Furthermore, the optical coating can be one or more functional coatings, including but not limited to narrowband filter coatings, broadband filter coatings, anti-reflection coatings, reflection enhancement coatings, polarization selective coatings, anti-stray light coatings, environmental protection coatings, or combinations thereof, to achieve modulation and optimization of the spectrum, intensity, polarization state, or transmission characteristics of incident light.

[0058] In one embodiment of this application, the distance between the lower surface of the optical compound eye sparse encoder 202 and the upper surface of the photosensitive area of ​​the photodetector 301 can be set to a preset working distance value of the optical modulator 201. The working distance value of the optical modulator 201 can be determined according to the accuracy requirements of the target orientation measurement, and its value relationship is shown in the following formula.

[0059]

[0060] In the formula, h is the modulator working distance, which is calculated as the modulator working distance parameter determined under the most unfavorable operating condition of the system's angular resolution, to ensure that the system meets the predetermined angular resolution requirements throughout the entire field of view; d c Indicates the system's c direction( c = x , y ) azimuth resolution; d( l γ ) indicates that the photodetector is in c The minimum equivalent spatial resolution in orientation is determined by the pixel size of the image sensor and the subdivision factor, which is related to the signal processing or centroid calculation algorithm used. The spatial resolution of an image sensor is limited by its pixel size, but by performing sub-pixel-level position calculation on the imaging spot, the equivalent resolution can be further improved based on the pixel size, thereby enhancing the system's angle measurement resolution. Based on the specified resolution requirement d... c The modulator's working distance can be calculated. Preferably, the calculated value can be rounded up to a value that facilitates processing and assembly.

[0061] In this embodiment, the pixel size of the photodetector can be set to 7.8 μm × 7.8 μm. After algorithmic subdivision, the resolution of the photodetector can reach 0.1 pixels. Therefore, d( l γWith a focal length of 0.78 μm and a resolution index set at 0.005° (18''), the modulator working distance is 8.94 mm. For ease of manufacturing, it is rounded up to 9 mm. The actual worst angular resolution of the device manufactured with a focal length of 9 mm is 0.00497° (17.892'').

[0062] In one embodiment of this application, the field of view of the orientation measuring device is determined by the following formula.

[0063]

[0064] In the formula, l sensor This represents the dimension of the photodetector in this direction; l pattern The dimension of the optical compound eye sparse encoder in this direction; l m The size of the central field-of-view pattern; h This is the preset modulator working distance.

[0065] In actual execution, the photodetector can be set as a contour detector. The contour detector can directly acquire the light intensity distribution information of the incident light spot in two mutually orthogonal directions to characterize the contour features of the incident light spot on the detection plane. The contour detector can directly output the light intensity distribution data in the row and column directions. The contour information is output in the form of a one-dimensional light intensity vector or a two-dimensional contour representation composed of the light intensity distribution in two orthogonal directions. The two-dimensional contour is represented as compressed contour data without pixel-by-pixel two-dimensional image data.

[0066] After acquiring the light intensity profile data of the photodetector in two orthogonal directions, the obtained profile data in the two orthogonal directions are denoted as light intensity vectors Ix and Iy, respectively. The vector length is less than or equal to the number of pixels in the corresponding direction. The light intensity vector can be further processed by unbiased filtering to suppress random noise without introducing systematic offset, so as to obtain a filtered light intensity vector with noise suppression and no systematic bias.

[0067] Unbiased filtering can be understood as filtering out errors caused by noise and interference (such as ambient light fluctuations and brightness anomalies caused by detector noise) without changing the true trend of light intensity data (unbiased), making the data cleaner and more stable, and the subsequent orientation calculation more accurate.

[0068] It should be noted that in step S101, the detection and acquisition of light intensity contour data can be achieved in many ways, and is not limited to one specific method.

[0069] Preferably, this can be achieved through a contour detector, which can directly output the light intensity distribution data of the target spot in two orthogonal directions, namely the row and column directions, or the equivalent two-dimensional spot contour information, without forming complete two-dimensional image data. This significantly reduces the amount of data and processing complexity, and can achieve a higher frame rate with lower power consumption. This method is the recommended implementation method in the embodiments of this application.

[0070] In another implementation, it can be based on a conventional two-dimensional image detector. The contour features of the target spot are extracted by accumulating, projecting, integrating or weighting the two-dimensional pixel data output by the image detector in the row and / or column directions. The contour extraction process can be completed by peripheral circuits, including but not limited to application-specific integrated circuits, field-programmable gate arrays, programmable logic devices or other digital or analog circuit structures.

[0071] In a further implementation, it can also be achieved through a customized photodetector. The photodetector has photosensitive units or photosensitive area arrays arranged in a specific layout in its photosensitive area. By converging, summing or projecting the light signal at the pixel level or region level, the contour information of the target light spot can be output directly or indirectly.

[0072] In the above embodiments, the contour information is output in the form of a one-dimensional light intensity vector, a two-dimensional contour representation, or an equivalent form. The two-dimensional contour representation is a compressed data form obtained by projection, accumulation, integration, or weighting in the row and / or column directions. It is not limited to forming complete two-dimensional image data with pixel-by-pixel light intensity information. As long as it can characterize the energy distribution characteristics of the target spot in space, it can be used for subsequent centroid calculation, aperture matching, and target orientation determination.

[0073] In step S102, the connected component segmentation threshold of the light intensity profile data is determined based on the light intensity vector, and sampling points whose light intensity values ​​in the light intensity vector meet the preset conditions are extracted according to the connected component segmentation threshold. The one-dimensional connected component of the incident light spot is determined based on the sampling points, and the one-dimensional light spot coordinate vector is calculated based on the one-dimensional connected component.

[0074] In actual implementation, the embodiments of this application can estimate the background light intensity of the light intensity contour data after unbiased filtering, and determine the connected component segmentation threshold of the light intensity contour data based on the background light intensity estimate. The connected component segmentation threshold can be obtained by superimposing a fixed bias on the background light intensity estimate, or by superimposing a scaling factor of less than 1 on the peak height of the light spot. The connected component segmentation threshold can be determined separately or uniformly in two orthogonal directions.

[0075] Furthermore, the light intensity vector can be thresholded based on the connected component segmentation threshold, and sampling points with light intensity values ​​greater than the connected component segmentation threshold can be extracted. The set of sampling points with continuous index positions can be regarded as a one-dimensional connected region, thereby obtaining a one-dimensional connected region corresponding to the target incident light spot. Within the one-dimensional connected region, the one-dimensional centroid coordinates of the target incident light spot in two orthogonal directions are obtained by weighted calculation based on the position index of the sampling points and their corresponding light intensity values, forming a one-dimensional light spot coordinate vector.

[0076] As one possible approach, embodiments of this application can regard the contour light intensity vectors Ix and Iy as signals with target incident light spots superimposed on the background light intensity. First, the background light intensity in the light intensity contour is estimated, and the background light intensity can be estimated using methods such as histogram statistics. After obtaining the estimated background light intensity, a threshold for connected component segmentation is determined. This threshold can be determined based on the estimated background light intensity plus a fixed bias, or dynamically determined based on the estimated background light intensity plus a scaling factor less than 1 multiplied by the peak height of the light spot. The connected component segmentation threshold can be calculated independently for the contour light intensity vectors Ix and Iy, or the same connected component segmentation threshold can be used in both directions. Based on the connected component segmentation threshold, the contour light intensity vectors Ix and Iy are thresholded, and sampling points with light intensity values ​​greater than the threshold are extracted. The set of sampling points with continuous index positions is regarded as a connected region, thereby obtaining a one-dimensional connected region corresponding to the target spot in the contour light intensity vector. The centroid is calculated in the connected region to obtain the one-dimensional spot coordinate vectors Cx and Cy of the target incident spot in two orthogonal directions. The centroid coordinates can be calculated by weighted summation based on the position index of each sampling point in the connected region and its corresponding light intensity value. The number of elements in the one-dimensional spot coordinate vectors Cx and Cy is consistent with the number of connected regions extracted in the corresponding direction.

[0077] This application embodiment determines the connected component segmentation threshold of light intensity contour data based on the light intensity vector, which can accurately extract effective sampling points and determine the one-dimensional connected component of the incident light spot, and then calculate the one-dimensional light spot coordinate vector. This can effectively eliminate noise and interference points, highlight the real and effective area of ​​the light spot, improve the accuracy and stability of light spot positioning, and provide high-precision and high-reliability coordinate data for subsequent target orientation calculation.

[0078] In step S103, the distance between adjacent light spots in a one-dimensional connected domain is calculated based on the one-dimensional light spot coordinate vector to obtain the mutual distance vector between light spots. The light spots in the same sub-field of view are determined according to the mutual distance vector, and the spatial coding of light spots is constructed based on the mutual distance relationship of light spots in the same sub-field of view.

[0079] In actual implementation, the embodiments of this application can calculate the distance between adjacent light spots in the connected domain based on the one-dimensional light spot coordinate vector to obtain mutual distance vectors in two orthogonal directions, which are used to characterize the relative positional relationship between adjacent light spots. According to the mutual distance vector, the distance between adjacent light spots is compared with the preset sub-field of view distance range. When the distance between adjacent light spots falls within the distance range, it is determined that the corresponding light spots belong to the same sub-field of view, and a unified sub-field of view number is assigned to the light spots in the same sub-field of view. Then, a spatial code is constructed based on the mutual distance relationship between the light spots in the same sub-field of view.

[0080] As one possible approach, the number of elements in the mutual distance vectors Dx and Dy is equal to the number of elements in the corresponding one-dimensional spot coordinate vectors Cx and Cy minus 1, respectively. Each element in the mutual distance vector is used to represent the distance between two adjacent spot coordinates in the one-dimensional spot coordinate vector, which is the absolute value of the difference between the two corresponding spot coordinates.

[0081] In one embodiment of this application, light spots in the same sub-field of view can be determined based on mutual distance vectors as follows: The optical compound eye sparse encoder 202 is designed with a distance range for the spacing between adjacent spots within the same sub-field of view. This range includes an upper and lower threshold. For any element in the mutual distance vector, when its value falls within the corresponding distance range, the spots corresponding to the coordinates of the two adjacent spots forming that element are determined to be in the same sub-field of view. This yields the discrimination result for spots in the same sub-field of view, and spots matching the same sub-field of view group are assigned a unified sub-field of view number j. Here, j is the sub-field of view number index, used to identify different sub-fields of view determined in the photodetector output. j starts from 1 and increments sequentially, with a maximum value representing the total number of sub-fields of view contained in the current output data of the photodetector.

[0082] Furthermore, embodiments of this application can calculate the spatial encoding of the light spots within the j-th sub-field of view based on the mutual distance vectors between the light spots and the discrimination results of the light spots within the same sub-field of view. Code x_j , Code y_j ].in Code x_j = [ Code x_j1 , Code x_j2 , Code x_j3 , …, Code x_j(n-1) ] is a vector with n-1 components, representing the spatial encoding of the j-th sub-field of view in the orthogonal direction 1. Code y_j Length and Codex_j "Same" indicates the spatial encoding of the j-th sub-field of view in orthogonal direction 2. n is the number of apertures in the sub-field of view; this value is typically less than the lengths of the mutual distance vectors Dx and Dy, meaning that a single frame of output allows for pattern imaging of multiple sub-fields of view. Spatial Encoding Code x_j , Code y_j Each component in Code x_j1 , Code x_j2 , Code x_j3 , …, Code x_j(n-1) , Code y_j1 , Code y_j2 , Code y_j3 , …, Code y_j(n-1) It is corresponding D x , D y The function of the relative distance component of the corresponding subfield of view can be matched with a unique subfield pattern on the optical compound eye sparse encoder according to a spatial code.

[0083] By using the above-mentioned technical means, the distance between adjacent light spots is calculated based on the one-dimensional light spot coordinate vector and mutual distance vectors are generated. Light spots belonging to the same sub-field of view can be accurately identified. Based on their distance relationship, a light spot spatial code is constructed, which can effectively solve the problems of fuzzy light spot correspondence and unreliable matching under multi-aperture conditions, improve the stability of light spot association and recognition, and provide a reliable spatial coding basis for high-precision target orientation calculation.

[0084] In step S104, the corresponding sub-field pattern in the compound eye sparse encoder is obtained according to the spatial encoding. Based on the sub-field pattern, the pixel coordinates of the light spot and the absolute spatial pixel coordinates of the aperture in the sub-field corresponding to the light spot are determined, and the orientation of the light source is determined according to the pixel coordinates of the light spot and the absolute spatial pixel coordinates.

[0085] The orientation measurement method provided in this application embodiment can spatially encode the incident light using a multi-field aperture structure. By analyzing the contour features of the imaging spot of each aperture, the correspondence between the geometric distribution of the spot and the sub-field of view of the optical compound eye sparse encoder is established, thereby realizing the calculation of the target incident direction.

[0086] In this method, the position information of the multi-aperture imaging spot can first be extracted from the contour detection result, and a discriminative spatial coding feature can be formed based on the relative geometric relationship of the spot in two orthogonal directions. Then, the spatial coding is matched with the pre-designed sub-field pattern of the optical compound eye sparse encoder to determine the combination of apertures involved in imaging and their spatial position in the optical compound eye sparse encoder. Furthermore, by establishing the geometric mapping relationship between the spot position and the corresponding aperture center position, the incident light direction vector corresponding to each aperture is calculated.

[0087] For a set of direction vectors formed by multiple apertures, this embodiment can perform fusion calculation based on the target light source type: when the target is a far-field parallel light source, the incident direction of the target is obtained by averaging the multiple direction vectors; when the target is a near-field point light source, the spatial position of the target is determined based on the parallax relationship between the multiple direction vectors. This method does not rely on a complete two-dimensional image processing process, and significantly improves the calculation speed and robustness while ensuring measurement accuracy.

[0088] Specifically, in this embodiment, after constructing a spatial code based on the mutual distance relationship of light spots within the same sub-field of view, the spatial code is used to match the corresponding sub-field of view pattern in the optical compound eye sparse encoder, thereby obtaining the absolute spatial pixel coordinates of each aperture in the sub-field of view in two orthogonal directions; the light spots determined to be in the same sub-field of view in the contour data are matched one by one with the apertures in the corresponding sub-field of view in the optical compound eye sparse encoder, thereby obtaining the pixel coordinates of the light spots in the photodetector coordinate system and the absolute spatial pixel coordinates of the corresponding apertures.

[0089] For example, embodiments of this application can retrieve the corresponding sub-field pattern in the optical compound eye sparse encoder based on the constructed spatial coding, and obtain the absolute spatial pixel coordinate vectors of n apertures in two orthogonal directions within the sub-field. X a_j , Y a_j ,in, X a_j = [ x a_j1 , x a_j2 , x a_j3 , …, x a_jn ] is a vector with n components, representing the absolute spatial pixel coordinate vector of the j-th sub-field of view in the orthogonal direction 1; Y a_j = [ y a_j1 , y a_j2 , ya_j3 , …, y a_jn [] is a vector with n components, representing the absolute spatial pixel coordinate vector of the j-th sub-field of view in orthogonal direction 2. The meaning of n is the same as before; absolute spatial pixel coordinate vector X a_j , Y a_j It has been uniformly transformed to the photodetector coordinate system according to the preset mapping criteria, and the unit coordinates are consistent with the one-dimensional spot coordinate vector. C x , C y The units of the elements are the same.

[0090] Furthermore, the light spots identified as being within the same sub-field of view in the contour data are matched one-to-one with the corresponding apertures within the sub-field of view on the optical compound eye sparse encoder; this is achieved through a one-dimensional light spot coordinate vector. C x , C y Obtain the pixel coordinates of each light spot within the sub-field of view on the photodetector, and then use the absolute spatial pixel coordinate vector of the sub-field of view. X a_j , Y a_j Read the pixel coordinates of each aperture in the sub-field of view on the optical compound eye sparse encoder.

[0091] By matching the sub-field pattern corresponding to the compound eye sparse encoder with the spatial coding, the absolute spatial pixel coordinates of the light spot and the corresponding aperture can be accurately determined, thereby solving the orientation of the light source. This enables a reliable correlation between the light spot and the aperture, effectively eliminates ambiguity in matching multi-aperture light spots, and significantly improves the stability and measurement accuracy of the light source orientation solution.

[0092] Optionally, in one embodiment of this application, determining the orientation of the light source based on the spot pixel coordinates and the absolute spatial pixel coordinates includes: calculating the dual-axis orientation angle and orientation vector of the aperture within the sub-field of view based on the spot pixel coordinates and the absolute spatial pixel coordinates, and determining the orientation of the light source based on the dual-axis orientation angle and orientation vector.

[0093] Specifically, based on the spot pixel coordinates and the absolute spatial pixel coordinates of the aperture, the dual-axis orientation angle and orientation vector of the aperture within the sub-field of view can be calculated using the following formulas, including: , , , in, i x_ij , iy_ij These are the directional angles calculated in orthogonal directions one and two based on the i-th aperture and its spot within the j-th sub-field of view; x s_ij , y s_ij These are the pixel coordinates of the light spot formed by the i-th aperture within the j-th sub-field of view on the photodetector in two orthogonal directions. x a_ij , y a_ij Indicates the first j Within the field of view of each individual i The absolute spatial pixel coordinates of each aperture in two orthogonal directions on an optical compound eye sparse encoder, where h is the preset working distance. k Represents direction vector The third component takes a value of +1 or -1. When the z-axis points from the center of the photodetector to the center of the optical compound eye sparse encoder, the direction vector... v ij The third component k Take -1, otherwise, when the z-axis points from the center of the optical compound eye sparse encoder to the center of the photodetector, k Take 1.

[0094] Optionally, in one embodiment of this application, determining the orientation of the light source further includes: performing direction vector fusion processing; when the light source is a parallel light source, calculating the average value of the direction vectors to determine the incident direction of the light source based on the average value; when the light source is a point light source, determining the three-dimensional spatial position coordinates of the point light source by minimizing the sum of the orthogonal distances from the spatial point corresponding to the point light source to each spatial ray; and determining the orientation of the light source based on the incident direction and the three-dimensional spatial position coordinates.

[0095] Specifically, when the target incident light source is a parallel light source, the incident direction of the target incident light source is determined by the average value of the direction vectors obtained from imaging at each aperture. When the target incident light source is a point light source, the spatial rays corresponding to each direction vector can be jointly solved based on the parallax relationship between multiple direction vectors, thereby determining the three-dimensional spatial coordinates (x, y, z) of the point light source.

[0096] Specifically, the space ray corresponding to the i-th aperture within the j-th sub-field of view can be represented as:

[0097] in, p ij This represents the known position vector of the i-th aperture within the j-th sub-field of view in space. It can be determined based on the absolute spatial pixel coordinate vectors of the n apertures within the j-th sub-field of view in two orthogonal directions. X a_j , Ya_j The result was obtained through calculation; v ij This represents the direction vector obtained from imaging with this aperture. t ij is a scalar parameter along the direction vector.

[0098] The formula for calculating the incident direction is: , , , in, Indicates the incident direction of a parallel light source. m This indicates the number of sub-fields of view contained in the contour data. n This indicates the number of apertures contained in each sub-field pattern. i x , i y It represents the direction angle in two orthogonal directions.

[0099] Due to measurement errors and system noise, the spatial rays typically do not intersect precisely. The spatial position of the point light source is obtained through joint estimation in the least squares sense, that is, by minimizing the sum of the orthogonal distances from the spatial point to each spatial ray. The formula for calculating the three-dimensional spatial position coordinates is as follows: , in, I For identity matrix, ( I v ij v ij T () is the projection matrix, used to calculate the orthogonal distance from a spatial point to its corresponding spatial ray. m This indicates the number of sub-fields of view contained in the contour data. n This indicates the number of apertures contained in each sub-field pattern.

[0100] Furthermore, in one embodiment of this application, based on the above-mentioned target orientation measurement method, in order to evaluate the orientation accuracy of the orientation measurement device, the device is installed on a three-degree-of-freedom turntable. By controlling the attitude change of the turntable at different angular positions, the orientation measurement result output by the calibrated device is obtained and compared with the nominal angle of the turntable, thereby evaluating the orientation accuracy of the device.

[0101] For example, based on the settings of the orientation measurement device with an optical modulation device 201 working distance of 5.5 mm, an optical compound eye sparse encoder size of 17.6 mm × 22.6 mm, an effective aperture pattern area of ​​15 mm × 15 mm, a photodetector pixel size of 7.8 μm × 7.8 μm, and a pixel count of 512 × 512, those skilled in the art obtained lsensor = 3.9936 mm, lm = 392 μm, a field of view of 118.8044° × 118.8044°, x and y orientation measurement accuracy of 0.0350° (3σ) and 0.0343° (3σ) respectively, a frame rate of 1602 Hz, and a power consumption of only about 30 mW. This achieves a frame rate far exceeding that of traditional image sensor-based orientation measurement devices with ultra-low power consumption, and achieves high accuracy with a large field of view approaching 120°.

[0102] The orientation measurement method based on optical compound eye sparse coding and contour detection proposed in this application can employ an optical compound eye sparse coding structure. By designing the spatial arrangement of multiple apertures or sub-fields of view within the coding plane, the apertures or sub-fields of view exhibit a non-dense, distinguishable sparse distribution in space. This allows different incident rays to form a uniquely geometrically shaped light spot contour distribution on the photodetector, achieving sparse spatial coding of the incident direction information at the optical level. Based on this, contour detection is used to obtain the one-dimensional intensity distribution characteristics of the light spot in two orthogonal directions (row and column). This transforms the traditional orientation resolution process, which relies on two-dimensional imaging, into an orientation calculation process based on one-dimensional contour signals, significantly reducing data dimensionality and computational complexity. Furthermore, the electronic system is used to match the light spot with the compound eye sub-fields of view or aperture based on the contour features, and to calculate the target incident direction. This method can achieve large field of view, high resolution, fast speed, and low power consumption orientation measurement without complex image processing, making it particularly suitable for power-sensitive applications and applications with high dynamic performance requirements, such as micro / nano satellites and drones. This solves the problems in related technologies, such as the instability of light spot correspondence caused by the susceptibility of conventional multi-aperture structures to interference, which affects the accuracy of target direction calculation, and the difficulty in meeting the requirements of real-time performance and stability in high-speed, high-mobility and resource-constrained scenarios due to the limitation of frame rate, data volume and power consumption by traditional solutions relying on full-frame readout of two-dimensional image detectors.

[0103] Next, refer to the appendix. Figure 7 This application describes a orientation measurement device based on optical compound eye sparse coding and contour detection, according to an embodiment of the present application.

[0104] Figure 7 This is a block diagram of an orientation measurement device based on optical compound eye sparse coding and contour detection according to an embodiment of this application.

[0105] like Figure 7As shown, the orientation measurement device 10 based on optical compound eye sparse coding and contour detection includes: an acquisition module 100, a calculation module 200, a construction module 300, and a measurement module 400.

[0106] The acquisition module 100 is used to form an incident light spot through a photodetector and acquire the light intensity contour data of the incident light spot, so as to generate a corresponding light intensity vector based on the light intensity contour data.

[0107] The calculation module 200 is used to determine the connected component segmentation threshold of the light intensity profile data based on the light intensity vector, and extract sampling points in the light intensity vector that meet the preset conditions according to the connected component segmentation threshold, so as to determine the one-dimensional connected component of the incident light spot based on the sampling points, and calculate the one-dimensional light spot coordinate vector based on the one-dimensional connected component.

[0108] The construction module 300 is used to calculate the distance between adjacent light spots in a one-dimensional connected domain based on the one-dimensional light spot coordinate vector, so as to obtain the mutual distance vector between the light spots, and to determine the light spots in the same sub-field of view based on the mutual distance vector, so as to construct the spatial encoding of the light spots based on the mutual distance relationship of the light spots in the same sub-field of view.

[0109] The measurement module 400 is used to obtain the corresponding sub-field pattern in the compound eye sparse encoder according to the spatial encoding, so as to determine the pixel coordinates of the light spot and the absolute spatial pixel coordinates of the aperture in the sub-field corresponding to the light spot based on the sub-field pattern, and determine the orientation of the light source according to the pixel coordinates of the light spot and the absolute spatial pixel coordinates.

[0110] Optionally, in one embodiment of this application, the measurement module 400 includes: a first calculation unit, which is used to calculate the dual-axis orientation angle and orientation vector of the aperture in the sub-field of view based on the spot pixel coordinates and the absolute spatial pixel coordinates, and to determine the orientation of the light source based on the dual-axis orientation angle and orientation vector.

[0111] Optionally, in one embodiment of this application, the biaxial orientation angle and orientation vector of the aperture within the sub-field of view are calculated using the following formulas, including: , , , in, i x_ij , i y_ij They respectively represent the results in the orthogonal directions according to the first... j Within the field of view of each individual i The direction angle is calculated from each aperture and its spot size. x s_ij , y s_ij Indicates the first jWithin the field of view of each individual i The pixel coordinates of the light spot formed by the aperture on the photodetector in two orthogonal directions. x a_ij , y a_ij Indicates the first j Within the field of view of each individual i The absolute spatial pixel coordinates of each aperture in two orthogonal directions on an optical compound eye sparse encoder. h Indicates the preset working distance. Represents the direction vector. k Represents direction vector The third component.

[0112] Optionally, in one embodiment of this application, the measurement module 400 further includes: a second calculation unit, a third calculation unit, and a determination unit; wherein, the second calculation unit is used for direction vector fusion processing, and when the light source is a parallel light source, it calculates the average value of the direction vector to determine the incident direction of the light source based on the average value; the third calculation unit is used to determine the three-dimensional spatial position coordinates of the point light source by minimizing the sum of the orthogonal distances from the spatial point corresponding to the point light source to each spatial ray when the light source is a point light source; the determination unit is used to determine the orientation of the light source based on the incident direction and the three-dimensional spatial position coordinates.

[0113] Optionally, in one embodiment of this application, the formula for calculating the incident direction is: , , , in, Indicates the incident direction of a parallel light source. m This indicates the number of sub-fields of view contained in the contour data. n This indicates the number of apertures contained in each sub-field pattern. i x , i y It represents the direction angle in two orthogonal directions.

[0114] Optionally, in one embodiment of this application, the formula for calculating the three-dimensional spatial position coordinates is: , in, I Represents the identity matrix, ( I v ij v ij T() represents the projection matrix used to calculate the orthogonal distance from a spatial point to its corresponding spatial ray. p ij Indicates the first j Within the field of view of each individual i The known position vector of each aperture in space v ij Indicates the first j Within the field of view of each individual i The direction vector obtained from aperture imaging m This indicates the number of sub-fields of view contained in the contour data. n This indicates the number of apertures contained in each sub-field pattern.

[0115] Optionally, in one embodiment of this application, the orientation measurement device further includes: an optical modulation device disposed at the front end of the optical compound eye sparse encoder, used to modulate the spectral characteristics, intensity distribution, phase characteristics, polarization state, wavefront morphology and / or transmission characteristics of the incident light; wherein, a photodetector is disposed at the rear end of the optical compound eye sparse encoder.

[0116] It should be noted that the foregoing explanation of the orientation measurement method based on optical compound eye sparse coding and contour detection also applies to the orientation measurement device based on optical compound eye sparse coding and contour detection in this embodiment, and will not be repeated here.

[0117] The orientation measurement device based on optical compound eye sparse coding and contour detection proposed in this application can employ an optical compound eye sparse coding structure. By designing the spatial arrangement of multiple apertures or sub-fields of view within the coding plane, the apertures or sub-fields of view exhibit a non-dense, distinguishable sparse distribution in space. This allows different incident rays to form a uniquely geometrically shaped light spot contour distribution on the photodetector, achieving sparse spatial coding of the incident direction information at the optical level. Based on this, contour detection is used to obtain the one-dimensional light intensity distribution characteristics of the light spot in two orthogonal directions (row and column). This transforms the traditional orientation resolution process, which relies on two-dimensional imaging, into an orientation calculation process based on one-dimensional contour signals, significantly reducing data dimensionality and computational complexity. Furthermore, the electronic system uses contour features to match the light spot with the compound eye sub-fields of view or aperture, and calculates the target incident direction. This method achieves large field of view, high resolution, fast speed, and low power consumption orientation measurement without complex image processing, making it particularly suitable for power-sensitive applications and applications with high dynamic performance requirements, such as micro / nano satellites and drones. This solves the problems in related technologies, such as the instability of light spot correspondence caused by the susceptibility of conventional multi-aperture structures to interference, which affects the accuracy of target direction calculation, and the difficulty in meeting the requirements of real-time performance and stability in high-speed, high-mobility and resource-constrained scenarios due to the limitation of frame rate, data volume and power consumption by traditional solutions relying on full-frame readout of two-dimensional image detectors.

[0118] In summary, to address the aforementioned problems in the background technology, inspired by the visual mechanism of biological compound eyes, this application proposes a method and device for orientation measurement based on optical compound eye sparse coding and contour detection. It employs an optical compound eye sparse coding structure, designing the spatial arrangement of multiple apertures or sub-fields of view within the coding plane to achieve a non-dense, distinguishable sparse distribution of apertures or sub-fields of view in space. This allows different incident rays to form uniquely geometrically shaped light spot contours on the photodetector, achieving sparse spatial coding of incident direction information at the optical level. The optical compound eye sparse coding structure consists of multiple sub-fields of view stitched together to form the overall field of view. Each sub-field of view uses a high-resolution optical configuration to achieve high angular resolution, while multiple sub-fields of view are sparsely combined spatially to achieve large field-of-view coverage, thus simultaneously achieving both a large field of view and high resolution at the system level. Building upon this, this embodiment employs contour detection to acquire the one-dimensional intensity distribution characteristics of the light spot in two orthogonal directions (rows and columns). This transforms the traditional orientation resolution process, which relies on two-dimensional imaging, into an orientation calculation process based on one-dimensional contour signals, significantly reducing data dimensionality and computational complexity. The electronic system matches the light spot with the compound eye's sub-field of view or aperture based on the contour features and calculates the target's incident direction. Based on optical compound eye sparse coding and contour detection, this application achieves large field of view, high resolution, fast speed, and low power consumption orientation measurement without complex image processing. It is particularly suitable for power-sensitive applications and applications with high dynamic performance requirements, such as micro / nano satellites and drones.

[0119] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 801, the processor 802, and the computer program stored on the memory 801 and capable of running on the processor 802.

[0120] When the processor 802 executes the program, it implements the orientation measurement method based on optical compound eye sparse coding and contour detection provided in the above embodiments.

[0121] Furthermore, electronic devices also include: Communication interface 803 is used for communication between memory 801 and processor 802.

[0122] The memory 801 is used to store computer programs that can run on the processor 802.

[0123] The memory 801 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0124] If the memory 801, processor 802, and communication interface 803 are implemented independently, then the communication interface 803, memory 801, and processor 802 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized into address buses, data buses, control buses, etc. For ease of representation, Figure 8 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0125] Optionally, in a specific implementation, if the memory 801, processor 802, and communication interface 803 are integrated on a single chip, then the memory 801, processor 802, and communication interface 803 can communicate with each other through an internal interface.

[0126] The processor 802 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0127] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described orientation measurement method based on optical compound eye sparse coding and contour detection.

[0128] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0129] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0130] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0131] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0132] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0133] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0134] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0135] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for orientation measurement based on optical compound eye sparse coding and contour detection, characterized in that, The orientation measurement device includes a photodetector and an optical compound eye sparse encoder, and the method includes: An incident light spot is formed by the photodetector, and the light intensity profile data of the incident light spot is acquired, so as to generate a corresponding light intensity vector based on the light intensity profile data. Based on the light intensity vector, a connected component segmentation threshold for the light intensity contour data is determined, and sampling points whose light intensity values ​​in the light intensity vector meet preset conditions are extracted according to the connected component segmentation threshold. Based on the sampling points, a one-dimensional connected component of the incident light spot is determined, and a one-dimensional light spot coordinate vector is calculated based on the one-dimensional connected component. The distance between adjacent light spots in the one-dimensional connected domain is calculated based on the one-dimensional light spot coordinate vector to obtain the mutual distance vector between the light spots. The light spots in the same sub-field of view are determined according to the mutual distance vector, and the spatial encoding of the light spots is constructed based on the mutual distance relationship of the light spots in the same sub-field of view. The corresponding sub-field pattern in the compound eye sparse encoder is obtained according to the spatial encoding. Based on the sub-field pattern, the pixel coordinates of the light spot and the absolute spatial pixel coordinates of the aperture in the sub-field corresponding to the light spot are determined. The orientation of the light source is determined according to the pixel coordinates of the light spot and the absolute spatial pixel coordinates.

2. The method according to claim 1, characterized in that, Determining the light source orientation based on the light spot pixel coordinates and the absolute spatial pixel coordinates includes: Based on the light spot pixel coordinates and the absolute spatial pixel coordinates, the dual-axis orientation angle and orientation vector of the aperture within the sub-field of view are calculated, and the orientation of the light source is determined based on the dual-axis orientation angle and orientation vector.

3. The method according to claim 2, characterized in that, The biaxial orientation angle and orientation vector of the aperture within the sub-field of view are calculated using the following formulas, including: ， ， ， in, θ x_ij , θ y_ij They respectively represent the results in the orthogonal directions according to the first... j Within the field of view of each individual i The direction angle is calculated from each aperture and its spot size. x s_ij , y s_ij Indicates the first j Within the field of view of each individual i The pixel coordinates of the light spot formed by the aperture on the photodetector in two orthogonal directions. x a_ij , y a_ij Indicates the first j Within the field of view of each individual i The absolute spatial pixel coordinates of each aperture in two orthogonal directions on an optical compound eye sparse encoder. h Indicates the preset working distance. Represents the direction vector. k Represents direction vector The third component.

4. The method according to claim 2, characterized in that, Determining the orientation of the light source also includes: For the direction vector fusion process, when the light source is a parallel light source, the average value of the direction vector is calculated to determine the incident direction of the light source based on the average value; When the light source is a point light source, the three-dimensional spatial position coordinates of the point light source are determined by minimizing the sum of the orthogonal distances from the spatial point corresponding to the point light source to each spatial ray; The orientation of the light source is determined based on the incident direction and the three-dimensional spatial coordinates.

5. The method according to claim 4, characterized in that, The formula for calculating the incident direction is: ， ， ， in, Indicates the incident direction of a parallel light source. m This indicates the number of sub-fields of view contained in the contour data. n This indicates the number of apertures contained in each sub-field pattern. θ x , θ y It represents the direction angle in two orthogonal directions.

6. The method according to claim 4, characterized in that, The formula for calculating the three-dimensional spatial position coordinates is as follows: ， in, I Represents the identity matrix, ( I v ij v ij T () represents the projection matrix used to calculate the orthogonal distance from a spatial point to its corresponding spatial ray. p ij Indicates the first j Within the field of view of each individual i The known position vector of each aperture in space v ij Indicates the first j Within the field of view of each individual i The direction vector obtained from aperture imaging m This indicates the number of sub-fields of view contained in the contour data. n This indicates the number of apertures contained in each sub-field pattern.

7. The method according to claim 1, characterized in that, The orientation measuring device also includes: An optical modulation device is disposed at the front end of the optical compound eye sparse encoder and is used to modulate the spectral characteristics, intensity distribution, phase characteristics, polarization state, wavefront morphology and / or transmission characteristics of the incident light; wherein, the photodetector is disposed at the rear end of the optical compound eye sparse encoder.

8. A orientation measurement device based on optical compound eye sparse coding and contour detection, characterized in that, include: The acquisition module is used to form an incident light spot through a photodetector and acquire the light intensity contour data of the incident light spot, so as to generate a corresponding light intensity vector based on the light intensity contour data. The calculation module is used to determine the connected component segmentation threshold of the light intensity contour data based on the light intensity vector, and extract sampling points in the light intensity vector that meet the preset conditions according to the connected component segmentation threshold, so as to determine the one-dimensional connected component of the incident light spot according to the sampling points, and calculate the one-dimensional light spot coordinate vector based on the one-dimensional connected component. The construction module is used to calculate the distance between adjacent light spots in the one-dimensional connected domain based on the one-dimensional light spot coordinate vector, so as to obtain the mutual distance vector between the light spots, and to determine the light spots in the same sub-field of view based on the mutual distance vector, so as to construct the spatial encoding of the light spots based on the mutual distance relationship of the light spots in the same sub-field of view; The measurement module is used to obtain the corresponding sub-field pattern in the compound eye sparse encoder according to the spatial encoding, so as to determine the spot pixel coordinates and the absolute spatial pixel coordinates of the aperture in the sub-field corresponding to the spot based on the sub-field pattern, and determine the light source orientation according to the spot pixel coordinates and the absolute spatial pixel coordinates.

9. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, the processor executing the program to implement the orientation measurement method based on optical compound eye sparse coding and contour detection as described in any one of claims 1-6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the orientation measurement method based on optical compound eye sparse coding and contour detection as described in any one of claims 1-6.

Images