Space target multi-dimensional detection device and method

Abstract

The invention discloses a space target multi-dimensional detection device and method, and relates to the technical field of photoelectric imaging detection, and the device comprises a tracking turntable subsystem, a telescope subsystem, a multi-spectral polarization imaging subsystem and an image processing display subsystem. The multispectral polarization imaging subsystem is connected with the image processing and displaying subsystem; the telescopic subsystem and the multispectral polarization imaging subsystem are integrated on the tracking turntable subsystem; the tracking turntable subsystem realizes rotation in a set angle range so as to drive the telescopic subsystem and the multispectral polarization imaging subsystem to rotate; the telescopic subsystem obtains a multi-field-angle light path and makes the light path enter the multi-spectrum polarization imaging subsystem; the multi-spectral polarization imaging subsystem determines polarization images under different field angles according to the multi-field angle light path; and the image processing display subsystem is used for splicing and fusing the polarization images under different field angles based on an image processing algorithm to obtain a wide-area detection image. According to the invention, the space coverage rate and resolution of observation are improved.

Description

Technical Field

[0001] The present application relates to the technical field of optoelectronic imaging detection, and particularly to a multi-dimensional detection device and method for space targets. Background Art

[0002] With the increasing frequency of space launch activities, the number of space targets has increased rapidly, and the risk of on-orbit satellites being threatened by space debris impacts has increased sharply. Detecting space targets has become extremely important. The ground-based space target detection system has become one of the important means of space target detection due to its advantages such as low cost, short construction period, and mature technology.

[0003] Traditional ground-based detection bands include visible and infrared bands. The visible and infrared bands have different detection advantages. Currently, existing integrated visible-infrared imaging optical systems can effectively reduce interference factors in the light propagation environment. However, the ground-based multi-dimensional detection system for space targets still has problems such as large volume and small field of view. A single detector cannot simultaneously meet the requirements of large field of view and high resolution in the space detection field. Summary of the Invention

[0004] The purpose of the present application is to provide a multi-dimensional detection device and method for space targets, which can obtain detailed space target characteristics with a large field of view and high resolution, and improve the space coverage rate and resolution of observations.

[0005] To achieve the above purpose, the present application provides the following solutions: In a first aspect, the present application provides a multi-dimensional detection device for space targets, including: A tracking turntable subsystem, a telescopic subsystem, a multi-spectral polarization imaging subsystem, and an image processing and display subsystem; the multi-spectral polarization imaging subsystem is connected to the image processing and display subsystem; the telescopic subsystem and the multi-spectral polarization imaging subsystem are integrated on the tracking turntable subsystem.

[0006] The tracking turntable subsystem is used to realize rotation within a set angle range, thereby driving the telescopic subsystem and the multi-spectral polarization imaging subsystem to rotate.

[0007] The telescopic subsystem is used to obtain multi-field-of-view optical paths and incident the multi-field-of-view optical paths into the multi-spectral polarization imaging subsystem; the multi-field-of-view optical paths include optical paths reflected or emitted by space targets at different field of views.

[0008] The multi-spectral polarization imaging subsystem is used to determine polarization images at different field of views according to the multi-field-of-view optical paths.

[0009] The image processing and display subsystem is used to splice and fuse polarization images at different field of view angles based on an image processing algorithm, obtain a wide-field detection image, and display the wide-field detection image.

[0010] In a second aspect, the present application provides a multi-dimensional detection method for space targets. The multi-dimensional detection method for space targets is used for the multi-dimensional detection device for space targets described in any one of the above, and the multi-dimensional detection method for space targets includes: Obtain polarization images at different field of view angles; the polarization images at different field of view angles are determined by the multi-spectral polarization imaging subsystem according to the multi-field of view optical path; the multi-field of view optical path includes the optical paths reflected or emitted by space targets at different field of view angles.

[0011] [[ID=⑧]]Splice and fuse the polarization images at different field of view angles based on an image processing algorithm, obtain a wide-field detection image, and display the wide-field detection image.

[0012] According to the specific embodiments provided by the present application, the present application has the following technical effects: The present application provides a multi-dimensional detection device and method for space targets. The telescopic subsystem and the multi-spectral polarization imaging subsystem are integrated on the tracking turntable subsystem. The tracking turntable subsystem realizes rotation within a set angle range, thereby driving the telescopic subsystem and the multi-spectral polarization imaging subsystem to rotate, enabling coverage of a larger space where the target is located, more comprehensively observing the trajectory, position, and attitude changes of space targets, achieving detection and identification over a larger range, solving the problem of the too small field of view of the imaging system of traditional single detectors, and thus realizing collaborative detection of space targets at different angles; by combining the target information obtained from the overlap of different fields of view, splicing and fusing multiple polarization images at different field of view angles based on an image processing algorithm can enhance image details, obtain more detailed target features, and output a complete and high-resolution spatial target scene image, that is, a wide-field detection image, thereby improving the spatial coverage rate and resolution of observations. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0014] Figure 1 It is a schematic diagram of the functional modules of a multi-dimensional detection device for space targets in an embodiment of the present application.

[0015] Figure 2Schematic diagram of functional modules of a multi-spectral polarization imaging subsystem in a spatial target multi-dimensional detection device provided by an embodiment of the present application.

[0016] Figure 3 Schematic diagram of a first adaptive optical module in a multi-spectral polarization imaging subsystem in a spatial target multi-dimensional detection device provided by an embodiment of the present application.

[0017] Figure 4 Model diagram of a spatial target multi-dimensional detection device provided by an embodiment of the present application.

[0018] Figure 5 Flowchart of a spatial target multi-dimensional detection method provided by an embodiment of the present application.

[0019] Reference numerals: 1 - First polarization modulation unit, 2 - Second polarization modulation unit, 3 - Third polarization modulation unit, 4 - First filter unit, 5 - Second filter unit, 6 - Third filter unit, 7 - First imaging lens unit, 8 - Second imaging lens unit, 9 - Third imaging lens unit, 10 - First imaging detection unit, 11 - Second imaging detection unit, 12 - Third imaging detection unit, 13 - First image acquisition unit, 14 - Second image acquisition unit, 15 - Second image acquisition unit. Detailed implementation manners

[0020] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0021] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0022] In an exemplary embodiment, as Figure 1 , Figure 2 , Figure 3 and Figure 4 shown, a spatial target multi-dimensional detection device is provided, including: a tracking turntable subsystem, a telescopic subsystem, a multi-spectral polarization imaging subsystem, and an image processing and display subsystem; the multi-spectral polarization imaging subsystem and the image processing and display subsystem are connected; the telescopic subsystem and the multi-spectral polarization imaging subsystem are integrated on the tracking turntable subsystem.

[0023] The tracking turntable subsystem is used to achieve rotation within a set angular range, thereby driving the telescope subsystem and the multi-spectral polarization imaging subsystem to rotate. Specifically, the tracking turntable subsystem can achieve rotation within the angular range of 0° to 180°.

[0024] The telescope subsystem is used to obtain multi-field-of-view optical paths and incident the multi-field-of-view optical paths onto the multi-spectral polarization imaging subsystem; the multi-field-of-view optical paths include the optical paths reflected or emitted by space targets at different field-of-view angles.

[0025] The multi-spectral polarization imaging subsystem is used to determine polarization images at different field-of-view angles based on the multi-field-of-view optical paths.

[0026] The image processing and display subsystem is used to splice and fuse the polarization images at different field-of-view angles based on image processing algorithms, obtain a wide-field detection image, and display the wide-field detection image.

[0027] Image stitching technology has received relatively high attention in recent years. Most current image stitching technologies obtain images based on traditional optoelectronic detection methods. Due to the complex detection background in actual detection, there are problems such as interference from background stars, relatively weak target signals, weak beam penetration ability, and difficulty in distinguishing faint targets. The detection and recognition ability of traditional ground-based detection systems for targets is limited and the detection accuracy is not high. Therefore, wide-field high-resolution detection is still the current demand for ground-based space target detection and the development trend of space target detection. In this embodiment, by obtaining multiple polarization images at different field-of-view angles and performing image stitching and fusion on the multiple polarization images at different field-of-view angles based on image processing algorithms to generate a wide-field detection image, it is of great significance for detecting space targets and aerospace research.

[0028] Based on the images taken synchronously by multiple detectors in different directions with a certain overlap, through steps such as image registration and image fusion, a new complete image with a wide angle and high resolution without stitching traces is formed. Based on image stitching technology, a panoramic image with high resolution and large field of view can be obtained.

[0029] Polarization imaging technology digitally processes the measured polarization information of the space target field, and can expand the measured target information from light intensity and position to polarization degree, polarization angle, etc., so that the information dimension is expanded. Due to the differences in the polarization characteristics of artificial targets and deep space backgrounds, polarization imaging can highlight target contour information, enhance image details, and is conducive to identifying faint targets under strong light backgrounds. Combining polarization imaging technology with image stitching technology in a ground-based optoelectronic detection system can effectively reduce interference factors in the light propagation environment and achieve wide-field high-resolution space target detection.

[0030] The SIFT (Scale-Invariant Feature Transform) algorithm is a robust feature point detection and matching algorithm, which has been widely used in remote sensing image registration. However, when dealing with large-scale remote sensing images, the traditional SIFT algorithm has problems such as large computational complexity and low matching efficiency. At present, there are solutions that combine multi-scale wavelet transform and the SIFT algorithm, which can improve the image registration speed. However, due to the further development in the aerospace field, the efficiency of remote sensing image registration in this field still needs to be further improved.

[0031] The PSO (Particle Swarm Optimization) algorithm is an optimization algorithm based on swarm intelligence, which has advantages such as strong global search ability and fast convergence speed. Introducing the PSO algorithm into the multi-scale wavelet transform and the SIFT algorithm can further improve the efficiency and accuracy of feature point matching.

[0032] To address the above problems, this application combines multi-spectral polarization imaging technology, adaptive adjustment technology, and image stitching technology to propose a ground-based multi-dimensional detection system and a wide-area detection method for space targets. Based on the adaptive adjustment technology, the atmospheric wavefront interference is corrected. The large-field-of-view target measurement is achieved through the stitching of the polarization degree image fields of view. Combining the target information obtained from different field-of-view overlaps, the visible light / short-wave infrared polarization images of different fields of view are stitched and reconstructed through an image processing algorithm. During the stitching process, a fast remote sensing image registration algorithm that combines the wavelet transform and the SIFT algorithm is optimized based on the particle swarm algorithm. Through the corresponding relationship of the same feature points in different polarization images in the scene, the projection relationship between the images is calculated, and then multiple images are projected onto the same plane. Finally, a complete wide-area polarization degree image is output through the fusion method to obtain a high-resolution polarization image of the scene, from which detailed target features with a large field of view and high resolution are obtained.

[0033] In another exemplary embodiment of this application, the image processing and display subsystem includes: an information processing unit and a display unit; the information processing unit is respectively connected to the multi-spectral polarization imaging subsystem and the display unit.

[0034] The information processing unit is used for: performing clarification processing on the polarization images at different field-of-view angles based on the median filtering algorithm to obtain the images to be stitched at different field-of-view angles; stitching the images to be stitched at different field-of-view angles based on the wavelet transform algorithm, the scale-invariant feature transform algorithm, and the particle swarm algorithm to obtain the stitched image; fusing the overlapping regions of adjacent images in the stitched image based on the wavelet transform algorithm to obtain the wide-area detection image; the display unit is used for displaying the wide-area detection image.

[0035] In another exemplary embodiment of the present application, the telescopic subsystem includes: a first front telescopic unit, a second front telescopic unit, and a third front telescopic unit that are distributed in an equilateral triangle.

[0036] The first front telescopic unit is used to incident a first optical path into the multi-spectral polarization imaging subsystem; the first optical path is the optical path reflected or emitted by a space target at a first field of view angle.

[0037] The second front telescopic unit is used to incident a second optical path into the multi-spectral polarization imaging subsystem; the second optical path is the optical path reflected or emitted by a space target at a second field of view angle.

[0038] The third front telescopic unit is used to incident a third optical path into the multi-spectral polarization imaging subsystem; the third optical path is the optical path reflected or emitted by a space target at a third field of view angle.

[0039] The first optical path, the second optical path, and the third optical path are parallel.

[0040] In another exemplary embodiment of the present application, as Figure 2 shown, the multi-spectral polarization imaging subsystem includes: a spectral polarization state modulation module, a correction module, and an image acquisition module; the spectral polarization state modulation module is arranged on the output optical path of the telescopic subsystem; the correction module is arranged on the output optical path of the spectral polarization state modulation module; the image acquisition module is arranged on the output optical path of the correction module.

[0041] The spectral polarization state modulation module is used to generate polarization state modulation output light at different field of view angles according to the multi-field of view angle optical paths.

[0042] The correction module is used to correct the polarization state modulation output light at different field of view angles to obtain corrected output light at different field of view angles.

[0043] The image acquisition module is used to image the corrected output light at different field of view angles to obtain polarization images at different field of view angles.

[0044] In another exemplary embodiment of the present application, the spectral polarization state modulation module includes: a first polarization state modulation module, a second polarization state modulation module, and a third polarization state modulation module; the optical axis of the first polarization state modulation module is arranged on the output optical path of the first front telescopic unit, the optical axis of the second polarization state modulation module is arranged on the output optical path of the second front telescopic unit, and the optical axis of the third polarization state modulation module is arranged on the output optical path of the third front telescopic unit.

[0045] The first polarization state modulation module is used to generate polarization state modulation output light at the first field of view angle according to the first optical path.

[0046] The second polarization state modulation module is used to generate polarization state modulation output light at the second field of view angle according to the second optical path.

[0047] The third polarization state modulation module is used to generate polarization state modulation outgoing light at the third field of view angle according to the third optical path.

[0048] In another exemplary embodiment of the present application, the first polarization state modulation module includes: a first polarization modulation unit and a first filter unit; the first polarization modulation unit is arranged on the output optical path of the first front telescopic unit; the first filter unit is arranged on the output optical path of the first polarization modulation unit.

[0049] The first polarization modulation unit is used to generate linearly polarized light at the first field of view angle according to the first optical path. The linearly polarized light includes: 0° linearly polarized light, 45° linearly polarized light, 90° linearly polarized light, and 135° linearly polarized light.

[0050] The first filter unit is used to filter the linearly polarized light at the first field of view angle to obtain polarization state modulation outgoing light at the first field of view angle.

[0051] Further, the optical axes of the first front telescopic unit, the first polarization modulation unit, and the first filter unit are on the same straight line; the optical axes of the second front telescopic unit, the second polarization modulation unit, and the second filter unit are on the same straight line; the optical axes of the third front telescopic unit, the third polarization modulation unit, and the third filter unit are on the same straight line; the optical axes of the first polarization state modulation module, the second polarization state modulation module, and the third polarization state modulation module are parallel.

[0052] Further, the first, second, and third polarization modulation units use a high-speed and high-positioning-accuracy rotating wheel to quickly drive the polarizing plates to rotate synchronously.

[0053] The second polarization state modulation module includes a second polarization modulation unit and a second filter unit; the third polarization state modulation module includes a third polarization modulation unit and a third filter unit; the second polarization state modulation module and the third polarization state modulation module have the same structure as the first polarization state modulation module, and will not be introduced here.

[0054] Since there may be atmospheric interference information in the polarization state modulation outgoing light, after obtaining the polarization state modulation outgoing light, it is also necessary to remove the atmospheric interference information in the polarization state modulation outgoing light, as follows.

[0055] In another exemplary embodiment of the present application, the correction module includes: a first adaptive optics module, a second adaptive optics module, and a third adaptive optics module; the first adaptive optics module is arranged on the output optical path of the first polarization state modulation module; the second adaptive optics module is arranged on the output optical path of the second polarization state modulation module; the third adaptive optics module is arranged on the output optical path of the third polarization state modulation module.

[0056] The first adaptive optics module is used to remove the atmospheric interference information in the polarization state modulated outgoing light at the first field of view angle, and obtain the corrected outgoing light at the first field of view angle.

[0057] The second adaptive optics module is used to remove the atmospheric interference information in the polarization state modulated outgoing light at the second field of view angle, and obtain the corrected outgoing light at the second field of view angle.

[0058] The third adaptive optics module is used to remove the atmospheric interference information in the polarization state modulated outgoing light at the third field of view angle, and obtain the corrected outgoing light at the third field of view angle.

[0059] In another exemplary embodiment of the present application, as Figure 3 shown, the first adaptive optics module includes: a first wavefront correction unit, a first beam splitting unit, a first wavefront sensing unit, and a first wavefront control unit; the first wavefront sensing unit and the first wavefront control unit are connected.

[0060] The first wavefront correction unit includes: a deformable mirror and a deformable mirror driver; the deformable mirror driver is respectively connected to the deformable mirror and the first wavefront control unit; the deformable mirror is arranged on the output optical path of the first polarization state modulation module; the first beam splitting unit is arranged on the output optical path of the deformable mirror; the first wavefront sensing unit is arranged on the output optical path of the first beam splitting unit.

[0061] The deformable mirror is used to deform the polarization state modulated outgoing light at the first field of view angle to generate the deformed outgoing light at the first field of view angle.

[0062] The first beam splitting unit is used to split the deformed outgoing light at the first field of view angle into two beams and enter the first wavefront sensing unit and the image acquisition module respectively.

[0063] The first wavefront sensing unit is used to: perform real-time measurement on the deformed outgoing light at the first field of view angle to obtain the first wavefront aberration.

[0064] The first wavefront control unit is used to generate a control signal according to the first wavefront aberration and send it to the deformable mirror driver; the first wavefront aberration is the optical wave aberration generated by the deformed outgoing light at the first field of view angle under the influence of atmospheric interference. The first wavefront control unit is used to judge whether the first wavefront aberration is within the set aberration range; if the first wavefront aberration is within the set aberration range, no control signal is generated, that is, the deformable mirror driver is not controlled; if the first wavefront aberration exceeds the set aberration range, a control signal is generated to control the deformable mirror driver.

[0065] The deformable mirror driver is used to change the shape of the deformable mirror according to the control signal to generate the corrected outgoing light at the first field of view angle.

[0066] The first beam splitting unit may use a beam splitter, the main purpose of which is to separate the light path to ensure that the light paths of the wavefront sensor and the imaging system do not interfere with each other and avoid blocking the imaging light path.

[0067] The second adaptive optical module includes: a second wavefront correction unit, a second beam splitting unit, a second wavefront sensing unit and a second wavefront control unit; the third adaptive optical module includes: a third wavefront correction unit, a third beam splitting unit, a third wavefront sensing unit and a third wavefront control unit. The second adaptive optical module and the third adaptive optical module have the same structure as the first adaptive optical module and will not be introduced here.

[0068] The modulated output light from the first optical path enters the first adaptive optical module, the first wavefront correction unit reflects the target light beam, and enters the first wavefront sensing unit through the beam splitting unit. The first wavefront sensing unit measures the wavefront distortion of the target light beam in real time, transmits the wavefront distortion signal to the first wavefront control unit, and generates a control signal for the first wavefront correction unit. Finally, the first wavefront correction unit corrects the originally distorted light beam into a plane wave. The entire system realizes closed-loop negative feedback, completes the correction of aberrations, and improves the resolution of the system.

[0069] The light of the second optical path and the light of the third optical path are respectively incident on the second adaptive optics module and the third adaptive optics module to correct the aberration in the same steps.

[0070] The first wavefront sensing unit, the second wavefront sensing unit and the third wavefront sensing unit all use Hartmann-Shack sensors, and the first wavefront correction unit, the second wavefront correction unit and the third wavefront correction unit change the direction of the light beam by installing multiple piezoelectric ceramic drivers on the deformable mirror.

[0071] In another exemplary embodiment of the present application, the image acquisition module includes: a first image acquisition module, a second image acquisition module and a third image acquisition module connected to the image processing and display subsystem; the first image acquisition module is arranged on the output optical path of the first adaptive optical module; the second image acquisition module is arranged on the output optical path of the second adaptive optical module; and the third image acquisition module is arranged on the output optical path connected to the third adaptive optical module.

[0072] The first image acquisition module is used to image the corrected emergent light at a first field of view angle to obtain a polarization image at the first field of view angle.

[0073] The second image acquisition module is used to image the corrected emergent light at a second field of view angle to obtain a polarization image at the second field of view angle.

[0074] The third image acquisition module is used to image the corrected emergent light at a third field of view angle to obtain a polarization image at the third field of view angle.

[0075] Among them, the first, second, and third image acquisition modules acquire real-time acquired picture streams, and use the respective wavefront aberration thresholds set in the first, second, and third wavefront control units to screen clear pictures. The process is as follows: First, each wavefront sensing unit measures the respective wavefront aberrations in real time at a high frequency (500 Hz). Each wavefront control unit drives the deformable mirror to compensate for the aberrations and calculates the corrected wavefront residual (RMS value). Each image acquisition module continuously captures at a slightly lower frequency (such as 50 Hz), and each frame of image is marked with the start and end time stamps of the exposure (accuracy ≤ 1 μs).

[0076] Secondly, when the wavefront residual RMS value is lower than the threshold for multiple consecutive frames (10 frames @ 500 Hz = 20 ms), it is determined as a stable period. Record the start time stamp (T_start) and end time stamp (T_end) of the stable period.

[0077] Furthermore, select the images that are completely included within [T_start, T_end] from the massive image stream, that is, the frames with the best correction effect for post-processing.

[0078] The first image acquisition module includes a first imaging lens unit, a first imaging detection unit, and a first image acquisition unit connected in sequence; the second image acquisition module includes a second imaging lens unit, a second imaging detection unit, and a second image acquisition unit connected in sequence; the third image acquisition module includes a third imaging lens unit, a third imaging detection unit, and a third image acquisition unit connected in sequence.

[0079] The optical axes of the first imaging lens unit, the first imaging detection unit, and the first image acquisition unit are on the same straight line; the optical axes of the second imaging lens unit, the second imaging detection unit, and the second image acquisition unit are on the same straight line; the optical axes of the third imaging lens unit, the third imaging detection unit, and the third image acquisition unit are on the same straight line; the optical axes of the first image acquisition module, the second image acquisition module, and the third image acquisition module are parallel.

[0080] The first, second, and third imaging detection units are electrically connected to the first, second, and third image acquisition units respectively; the first, second, and third image acquisition modules are electrically connected to the information processing unit, and the information processing unit is electrically connected to the display unit.

[0081] In addition, the first, second, and third image acquisition modules are also connected to the display unit.

[0082] The multi-dimensional detection device for space targets also includes a control subsystem.

[0083] Further, the telescopic subsystem is connected to the multi-spectral polarization imaging subsystem, the multi-spectral polarization imaging subsystem is connected to the image processing and display subsystem, and the control subsystem is respectively connected to the multi-spectral polarization imaging subsystem, the image processing and display subsystem, and the tracking turntable subsystem.

[0084] The first, second, and third imaging and detection units complete polarization imaging in the visible and near-infrared 0.4 - 1.7 μm band, and the first, second, and third image acquisition units acquire images in the visible and near-infrared 0.4 - 1.7 μm band at the same moment and the same field of view.

[0085] Further, the information processing unit obtains polarization degree and polarization angle images of different fields of view based on the obtained target information images, and stitches and reconstructs the polarization degree images of different field angles through an image processing algorithm to output a complete wide-area detection image; the display unit will display the linear polarization image and the wide-area detection image based on the polarization degree.

[0086] The tracking turntable system can rotate at an angle of 0° - 180°, and acquire images of the target from multiple different perspectives.

[0087] The control subsystem provides regulation and control for the multi-spectral polarization imaging subsystem and the image processing and display subsystem.

[0088] The imaging system of a traditional single detector has too small a field of view. Detecting with multiple detectors stitched at an angle can expand the field of view and achieve monitoring and recognition over a larger range. Dividing the target reflected light into three paths is equivalent to three detectors performing cooperative detection on the target at different angles. Stitching two detectors has insufficient field of view coverage and the fault tolerance ability decreases. Once one of the systems fails, the wide-area detection advantage is lost. Cooperative detection with four detectors has high costs for both detection and maintenance, and high requirements for the accuracy of hardware and software. Considering comprehensively, three paths with three detectors are used to detect the target. Each path of light will generate different degrees of errors due to atmospheric wavefront interference, so all three paths of light need to be corrected.

[0089] The three paths of light have different detection angles for the target, and all three detectors can image the target. The target is in different regions of the fields of view of different detectors. The optical axes of the three optical paths are parallel, and the three detectors are distributed in an equilateral triangle. During the actual detection process, the detectors are aligned with the target through the tracking turntable subsystem for shooting.

[0090] The modules and hardware used in the three paths are the same, and their functions are also the same, that is, to correct aberration to obtain clear polarization images. The difference is that the three detectors have different detection angles for the target, so the backgrounds are different, and the interference with light is also different. Each path corrects different aberrations with the same modules and methods, but the specific parameters are different.

[0091] Further, the working mode of the multi-dimensional detection device for space targets is as follows.

[0092] S1. The control system powers the polarization modulation unit, the filter unit, the imaging detection unit, and the image processing and display subsystem. The following polarization modulation unit, filter unit, imaging detection unit, imaging lens unit, and image acquisition unit all include the first, second, and third polarization modulation units, filter units, imaging detection units, imaging lens units, and image acquisition units.

[0093] S2. The target reflected light interfered by atmospheric turbulence enters the multi-spectral polarization imaging subsystem through the first, second, and third telescopic subsystems. The light in the visible / near-infrared band of 0.4 - 1.7 μm passes through the polarization modulation unit, and the polarization plate is rapidly rotated by a high-speed and high-positioning-accuracy rotating wheel, enabling the polarization modulation unit to achieve linear polarization modulation; the light in the visible / near-infrared band of 0.4 - 1.7 μm passes through the filter unit, and the filter is rotated by a high-speed and high-positioning-accuracy filter rotating wheel to achieve multi-spectral observation of the 0.44 μm, 0.694 μm, and 1.49 μm filters. Switching to the panchromatic channel enables panchromatic polarization detection. The modulated outgoing light carries polarization information and atmospheric interference information.

[0094] S3. Taking the first adaptive optical module as an example, the modulated outgoing light enters the first wavefront sensing unit through the first wavefront correction unit and the first beam splitting unit.

[0095] The control system powers the first wavefront correction unit, the first beam splitting unit, the first wavefront sensing unit, and the first wavefront control unit. The first wavefront sensing unit uses a Hartmann-Shack sensor to segment and sample the wavefront of the target reflected light through a lens array. The wavefront tilt within each sub-aperture range will cause the focused spot of the unit lens to drift laterally. The drift amount of the spot center in two directions relative to the reference position calibrated with parallel light is measured, thereby obtaining the average slope of the wavefront in two directions within each sub-aperture range, realizing real-time measurement of the wavefront distortion amount of the target beam, and transmitting the wavefront distortion signal to the first wavefront control unit.

[0096] The first wavefront control unit calculates the wavefront phase through the wavefront slope obtained by the sensor, converts it into a control signal for the first wavefront correction unit, and feeds it back to the deformable mirror driver to change the shape of each aperture module of the deformable mirror to compensate for the distorted wavefront, correcting the originally distorted beam into a plane wave. The entire system realizes closed-loop negative feedback to complete the correction of aberration. The outgoing light carries polarization information and corrects atmospheric interference information.

[0097] The steps of the second and third adaptive optical modules are the same as those of the first adaptive optical module.

[0098] S4. The emitted light corrected by the correction module is imaged on the imaging detection unit through the imaging lens unit, and after passing through the image acquisition unit, four polarized linear polarization components with different viewing angles are obtained on the display unit.

[0099] S5. The image processing and display subsystem includes an information processing unit and a display unit. The information processing unit obtains target information images with different viewing angles and different polarization angles, that is, polarization images at different field of view angles, based on the above subsystems.

[0100] S6. The reflected light of the target object needs to pass through optical components such as optical lenses, and the clarity of the polarization image will be affected to a certain extent. The polarization images obtained from different sensors are respectively preprocessed by a median filtering algorithm based on variance.

[0101] S7. Based on the preprocessed polarization images, obtain the 、 、 、 information of the space target at different viewing angles, representing the irradiance of the corresponding light beam, and through the Stokes component calculation formula, obtain the 、 、 、 component images, and finally calculate the degree of polarization ( ) and the polarization angle ( ) images.

[0102] S8. A fast remote sensing image registration algorithm based on the optimization of the particle swarm algorithm combined with wavelet transform and SIFT algorithm.

[0103] S9. Project multiple images onto the same plane, and use wavelet transform to perform pixel-level fusion processing on the overlapping areas of adjacent images to eliminate the stitching seam and obtain a smooth and seamless panoramic image.

[0104] This application combines multi-spectral polarization imaging technology, adaptive adjustment technology, and image stitching technology, and proposes a multi-dimensional detection device and method for space targets, which has the following beneficial effects.

[0105] (1) This application can obtain intensity detection and polarization information of visible light and short-wave infrared. Based on the polarization advantage, it can realize multi-dimensional space target detection, obtain a high-resolution polarization degree image of the scene, enhance image details, and obtain more detailed target features.

[0106] (2) By combining the target information obtained from the overlap of different fields of view and using image processing algorithms to stitch and reconstruct the visible light / short-wave infrared polarization degree images of different fields of view, the observation field of view can be extended, enabling the detection of space targets with a large field of view. A complete wide-field polarization degree detection image is output, covering a larger space where the target is located, and enabling a more comprehensive observation of the trajectory, position, and attitude changes of space targets. The remote sensing image fast registration algorithm optimized by combining the particle swarm algorithm with the wavelet transform and SIFT algorithm can improve the efficiency and accuracy of the algorithm, increase the image registration speed, and further enhance the detection efficiency and accuracy of the system for space targets.

[0107] This application combines multi-spectral polarization imaging technology, adaptive adjustment technology, and image stitching technology to generate wide-field detection images, which have extensive application value in space target observation and can improve the spatial coverage rate, resolution, and accuracy of observation. This method has significant positive benefits in aspects such as the monitoring, early warning, and trajectory prediction of space targets.

[0108] For the processes of image acquisition and image processing, two embodiments are respectively provided to illustrate this.

[0109] Embodiment 1.

[0110] In view of the problems of traditional optoelectronic detection methods being easily affected by the environment, the actual detection background being complex, the space target signal being relatively weak, the beam penetration ability being weak, the atmospheric interference affecting the imaging quality, and it being difficult to distinguish dim targets, this embodiment provides a multi-dimensional detection device for space targets based on adaptive adjustment technology and multi-spectral polarization imaging technology to achieve the acquisition of polarization images from different perspectives.

[0111] In this embodiment.

[0112] (1) The first, second, and third polarization modulation units all use the wire grid polarizer WP50L-UB from Thorlabs.

[0113] (2) The first, second, and third filter units all use the filter wheel FW102CWNEB driven by a stepper motor from Thorlabs, and the filters selected are the FBH440-10 type, FBH694-10 type, and FBH1490-12 type filters from Thorlabs.

[0114] (3) The first, second, and third imaging lens units all use the short-wave infrared lens M5018-VSW from Lingyun Optoelectronics.

[0115] (4) The first, second, and third imaging detection units all use the short-wave infrared detection module Cobra2000-U31280-130VT1-00 from Lingyun Optoelectronics.

[0116] In the embodiment, the control subsystem supplies power to the spectral polarization modulation module, the calibration module, the image acquisition module, and the image processing and display subsystem.

[0117] The target reflected light rays disturbed by atmospheric turbulence enter the multi-spectral polarization imaging subsystem through the telescopic subsystem. The high-speed and high-positioning-accuracy rotating wheel quickly drives the polarizer to rotate. The light rays in the first optical path pass through the first polarization modulation unit, the light rays in the second optical path pass through the second polarization modulation unit, and the light rays in the third optical path pass through the third polarization modulation unit, realizing polarization modulation including 0° linear polarization, 45° linear polarization, 90° linear polarization, and 135° linear polarization.

[0118] The high-speed and high-positioning-accuracy filter rotating wheel drives the filter to rotate. Each filter unit has 4 channels, including three spectral channels and one all-pass channel. The visible light filter unit includes filter plates with central wavelengths of 0.44um, 0.694um, and 1.49um. The electronically controlled high-speed and high-positioning-accuracy filter rotating wheel can be switched to the filter position to realize multi-spectral observation. When switched to the panchromatic channel, panchromatic polarization detection can be realized. The modulated outgoing light carries polarization information and atmospheric interference information.

[0119] The light corrected by the adaptive optical module passes through the first, second, and third imaging lens units and is imaged on the first, second, and third imaging detection units respectively. By rotating the polarizer, the rotating polarization directions of 0°, 45°, 90°, and 135° are obtained. The image acquisition unit can obtain images with different spectral intensities, which are 0°, 45°, 90°, and 135° polarization images, completing polarization imaging in the visible light near-infrared 0.4~1.7um band. The first, second, and third image acquisition units respectively acquire images in the visible light near-infrared wave 0.4~1.7um band in different fields of view at the same moment and display them on the display unit to obtain four polarization linear polarization components.

[0120] This embodiment can obtain intensity detection and polarization information in multiple bands and multiple dimensions of visible light and short-wave infrared, can realize multi-dimensional space target detection, obtain a high-resolution polarization degree image of the scene, and obtain more detailed target characteristics.

[0121] Embodiment 2.

[0122] In this embodiment, aiming at the problem that it is difficult to simultaneously meet high resolution and small volume in traditional optoelectronic detection systems, based on the image processing and display subsystem, the target information image obtained above is processed by a median filtering algorithm based on variance. By obtaining polarization degree and polarization angle images in different fields of view, and based on the particle swarm optimization algorithm combined with wavelet transform and SIFT algorithm, the polarization degree images and polarization angle images of adjacent detectors at different field of view angles are stitched pairwise to generate a complete seamless imaging result for the same field of view, and a complete wide-field high-resolution detection image is output. The processed image is displayed on the display unit.

[0123] The specific method of this embodiment is as follows Figure 5 shown below.

[0124] Step 1: Input the image to be registered.

[0125] The image processing and display subsystem includes an information processing unit and a display unit. The information processing unit processes the target information images obtained from different perspectives and different polarization angles.

[0126] Step 2: Preprocess the image to be registered.

[0127] The reflected light of the target object needs to pass through optical components such as optical lenses, and the clarity of the polarization image will be affected to a certain extent. The polarization images obtained from different sensors are preprocessed respectively by the median filtering algorithm based on variance.

[0128] Set the sampling window to traverse the target polarization image. With a window size of 5×5, 25 pixel points form a combination, and the coordinates of the center point are denoted as , and the gray value is . Its average value can be expressed as: .

[0129] The variance is: .

[0130] When the gray value satisfies , then keep the pixel point value.

[0131] When the gray value satisfies , using the neighborhood substitution method, replace the pixel point value with the maximum gray value of the pixels in the 3×3 neighborhood. Based on the principle of the median filtering algorithm, take the median of the useful signal value points as the new median in the 5×5 neighborhood, which can effectively filter out noise and at the same time can better protect the edge detail information of the target image.

[0132] Step 3: Obtain polarization information.

[0133] Based on the preprocessed polarization image, obtain the , , , information of the spatial target from different perspectives. Through the Stokes component calculation formula, obtain the , , , component images, and finally calculate the degree of polarization ( ) and the polarization angle ( ) images.

[0134] The various polarization states of light waves are represented by the Stokes vector. The four parameters of the Stokes vector are: .

[0135] It is the total irradiance of the 0° polarization component plus the total irradiance of the 90° polarization component, which represents the total irradiance of the beam; It is the total irradiance of the 0° polarization component minus the total irradiance of the 90° polarization component; It is the total irradiance of the 45° polarization component minus the total irradiance of the 135° polarization component; is the total irradiance of the right-hand polarized component minus the total irradiance of the left-hand polarized component.

[0136] The degree of polarization (DOP) and angle of polarization (AOP) are two indicators for studying the polarization state of light. Changes in the polarization state and polarization angle can represent the polarization characteristics of polarized light.

[0137] .

[0138] .

[0139] Step 4: Wavelet decomposition preprocessing.

[0140] Based on the two-dimensional discrete wavelet transform (DWT), the input image is decomposed layer by layer in the horizontal and vertical directions, and the image is decomposed into a low-frequency component (LL) and three high-frequency components (LH, HL, HH). The low-frequency information is retained to obtain a low-frequency image containing a large amount of information.

[0141] For the image matrix , first perform wavelet decomposition on the image in the row direction (horizontal) to generate low-frequency and high frequency sub-band .

[0142] .

[0143] .

[0144] These two formulas represent the wavelet decomposition of the image in the row direction (horizontal). First, each row of the original image is extracted and wavelet decomposition is performed to obtain the high and low frequency information in the horizontal direction.

[0145] Direction is the direction of the row, Direction is the column direction, fixed Direction, yes Direction filtering, the formula The abscissa representing the image is fixed in this formula, that is, operations are only performed on the pixels in a certain vertical direction of the image. n is a variable representing traversing all the pixels of the input image in the vertical direction, i.e., the y direction. For each fixed , will take on all the values in the direction.

[0146] and represent the low-pass and high-pass filters, containing the filtering coefficients of low frequency and high frequency, and are used to extract the low-frequency approximate information and high-frequency detail information of the image row.

[0147] represents the displacement of the filter along the row direction ( direction).

[0148] is the filter function, which calculates the pixel values of the output image based on the neighborhood pixels in the vertical direction of the input image.

[0149] represents the horizontal low-frequency component, indicating the smoothing information.

[0150] represents the horizontal high-frequency component, indicating the horizontal edge information.

[0151] The wavelet decomposition of the image has been performed in the row direction above, and it is divided into high frequency and low frequency , which belongs to one-dimensional transformation. Apply wavelet decomposition to each column of these two sub-bands, extract each column, perform wavelet decomposition, and obtain the high- and low-frequency information in the vertical direction.

[0152] Apply one-dimensional wavelet decomposition to each column of and to generate four sub-bands , , , .

[0153] .

[0154] .

[0155] .

[0156] .

[0157] Among them: represents the low-frequency sub-band, containing the main structural information of the image; represents the low-frequency horizontal component and the high-frequency vertical component, indicating the vertical edge information of the image; represents the high-frequency horizontal component and the low-frequency vertical component, indicating the horizontal edge information of the image; represents the high-frequency sub-band, indicating the diagonal information of the image.

[0158] The above four formulas represent wavelet decomposition in the column direction (vertical) of two sub-bands, The direction is the row direction, The direction is the column direction, fixed direction, for direction filtering, in the formula represents the ordinate of the image, which is fixed in this formula, that is, only the pixels in a certain horizontal direction of the image are operated on. is a variable, representing traversing all pixels of the input image in the horizontal direction. For each fixed , will take all values in the direction.

[0159] Through multi-level wavelet decomposition, the sub-band can be further decomposed to generate new , , and sub-bands. The decomposition can continue for multiple levels to form a pyramid structure of multi-scale image decomposition, obtaining the wavelet pyramid of the image.

[0160] In this embodiment, a three-level wavelet pyramid is obtained. The SIFT algorithm is used to extract features from the low-frequency sub-image of the wavelet pyramid, converting the registration problem of the high-resolution image into the registration problem of the low-frequency approximate component image, achieving rough registration of the image in the large-scale (low-resolution) space. Then, taking the obtained registration result as the initial value, the phase correlation method is used to perform translational compensation on the roughly registered image to achieve fine registration of the image and improve the registration efficiency.

[0161] Step Five: Feature extraction using the SIFT algorithm.

[0162] Based on the feature point monitoring technology, the polarization degree or polarization angle images from different perspectives are registered. First, the polarization degree images of adjacent detectors are matched and stitched. The polarization degree images of adjacent detectors are denoted as and , and the SIFT (Scale-Invariant Feature Transform) algorithm is used to extract features from the LL sub-band of the low-frequency image, extracting the feature points in the polarization degree images or polarization angle images obtained and processed by different perspectives, that is, different detectors, and extracting image feature points in the scaled space.

[0163] The spatial transformation utilizes a two-dimensional Gaussian distribution function. The image is transformed to form an image sequence in the multi-scale space, and then scale-invariant feature points are searched for on these image sequences. The form of the two-dimensional Gaussian distribution function is as follows.

[0164] .

[0165] is the variance of the two-dimensional standard normal distribution.

[0166] The Gaussian function is used to blur and downsample the image to obtain the Gaussian pyramid of the image, and the Gaussian scale space is constructed. During the process of scaling the space: .

[0167] represents a two-dimensional image, represents convolution. This formula represents a certain point on the image Based on the two-dimensional Gaussian distribution function, the spatial convolution is transformed to the Gaussian scale space with the scale factor being the variance On the Gaussian scale space, according to the scale factor The value of, the Gaussian pyramid is constructed from small to large . The difference Gaussian pyramid is established by using the difference between adjacent Gaussian scale spaces.

[0168] .

[0169] Among them, That is, it represents the scale factors of different scale spaces; represents different scale spaces in the Gaussian pyramid; represents the difference pyramid.

[0170] The scale factor The change will have an impact on the scale space. When it becomes smaller, the Gaussian filter (two-dimensional Gaussian distribution function) has a weaker smoothing effect on the image, and will retain the details and edge information of the image. When it becomes larger, the Gaussian filter (two-dimensional Gaussian distribution function) increases the smoothing effect on the image, and will remove the small details and noise in the image and blur the image. By changing the value of the scale factor The value of, the features of the image at different scales can be obtained. That is, it represents different scale factors. According to the different scale factors The value of, the Gaussian pyramid containing different scale spaces is constructed from small to large .

[0171] is the Gaussian pyramid, which provides the representation of the image in different scale spaces and does not provide the change information of different scale spaces. It represents the Difference Pyramid. In the Gaussian Pyramid, except for the topmost and bottommost groups, subtracting adjacent two layers in each group (subtracting the upper layer from the lower layer) generates the Gaussian Difference Pyramid. Each difference image reflects the detailed information of the image at that scale, representing the information that can be represented at the current scale in the Gaussian Pyramid but cannot be represented at the smoother scale of the upper layer. It can effectively extract the positions of stable key points of the image in the scale space.

[0172] The key points are composed of local extreme points in the space of the Difference Gaussian Pyramid. Each pixel point needs to be compared with all its adjacent points to see if it is larger or smaller than its adjacent points in the image domain and scale domain. The middle detection point is compared with 8 adjacent points at the same scale and 9×2 points corresponding to the adjacent scales above and below, a total of 26 points, to ensure that extreme points are detected in both the scale space and the two-dimensional image space. After detecting the extreme points in the discrete space, a quadratic curve fitting is performed on the obtained local extreme points to more precisely mark the position and scale value of the feature points. The fitting method is as follows.

[0173] Assume there is a point in the space of a certain Difference Gaussian Pyramid , by performing series expansion on the scale space of this point and taking terms up to the square term, the first-order derivative is obtained to determine the extreme value.

[0174] .

[0175] .

[0176] .

[0177] D in the above formula is , the content in the brackets is hidden during the series expansion and is represented by the following formula.

[0178] , .

[0179] is the scale coordinate, , is the corresponding extreme position and extreme value.

[0180] Set a threshold , the feature point satisfies , and it is obtained as a candidate feature point. Take the threshold as 0.03. After determining the feature points, calculate the main direction of the eigenvalue, calculate the product of the gradient values in each direction around the feature point and the contribution degree (weight value) of each direction to the center point, sum them separately in eight directions, and the direction of the maximum value is used as the main direction. Search for similar matching points in the three polarization images for pairing, and randomly select four pairs of matching points to linearly estimate the projection matrix M.

[0181] 。

[0182] Establish a distance estimation function for feature point pairs: 。

[0183] Among them, , is a pair of matching feature points, M is the projection matrix reflecting the coordinate transformation of feature points between images, m 0、 m 1、 m 2、 m 3、 m 4、 m 5、 m 6、 m 7 is an element in the projection matrix M among them.

[0184] When the calculated distance is less than a certain threshold, retain the matching point pairs, otherwise eliminate them, and remove key points with low contrast and unstable edge response points to enhance the matching stability.

[0185] Step Six: Construct a feature point descriptor.

[0186] Assign directions to key points. Using a histogram, statistically calculate the pixel gradient directions in the neighborhood of the key points, and the peak value is the direction of the key point. Rotate the coordinate axis to the direction of the key point, then select a window with the key point as the center, divide it into 4×4 small regions, calculate the gradient histograms in 8 directions on each small region, calculate the cumulative value on each gradient, and a seed point can be obtained. The number of seed points is 16, and each seed point consists of eight numbers, so a 4×4×8 = 128-dimensional descriptor is formed, which has the characteristics of scale, rotation, and affine invariance. Through the comparison of feature point descriptors, feature point matching is realized.

[0187] Step Seven: Optimize feature matching based on the particle swarm algorithm.

[0188] Take the feature point matching result as the initial solution of the particle swarm algorithm, encode the particles based on the particle swarm algorithm (PSO), represent each particle as a vector, which contains the translation and rotation parameters of the images to be registered, define a fitness function to evaluate the registration effect of each particle, and use the matching degree of feature points as the evaluation index.

[0189] Randomly generate a certain number of particles and initialize their positions and velocities. According to the current positions and velocities of the particles, use the PSO algorithm to update the positions and velocities of the particles.

[0190] Calculate the fitness value of each particle, select the optimal particle according to the fitness value, and record its position as the current optimal solution to find the optimal matching result.

[0191] Judge whether the termination condition is met, such as reaching the maximum number of iterations or the fitness value reaching the threshold, and output the registration parameters corresponding to the optimal solution, that is, the translation and rotation parameters of the image.

[0192] Step Eight: Image Registration.

[0193] Perform perspective transformation and resampling on the image to achieve rough image registration, and use the phase correlation method to perform translation compensation on the roughly registered image to achieve fine image registration.

[0194] First, use the extracted feature point pairs for rough registration to estimate the initial transformation matrix. Assume that the feature points in two low-frequency images correspond to , . The transformation relationship between the two is as follows.

[0195] .

[0196] .

[0197] .

[0198] is the transformation matrix, and this transformation can be translation, rotation, scale change or affine transformation; , represent the scaling and rotation in the horizontal direction; , represent the scaling and rotation in the vertical direction; , represent the translation amounts in the horizontal and vertical directions respectively.

[0199] Use all the feature point pairs and use the least squares method to fit the transformation matrix to obtain a system of equations.

[0200] .

[0201] , is the column vector containing all the feature points. , is the matrix containing all the feature points.

[0202] , is the column vector of the transformation matrix parameters.

[0203] Based on the least squares method, it can be obtained that: , where the superscript T represents transpose. By obtaining six matrix parameters, and can be roughly registered.

[0204] .

[0205] represents the image after transformation; represents the coordinates after inverse transformation, giving the corresponding pixel positions in . The image will be preliminarily registered and transformed and aligned to the image to obtain the roughly aligned image.

[0206] Optimize the transformation matrix based on the phase correlation method , to achieve fine registration in the high-resolution space. The scale parameter and rotation parameter of the image remain unchanged, only considering the translation transformation. Based on the Fourier transform, the translation amount of the image is estimated by calculating the phase information in the frequency domain. The two images are Fourier-transformed, and the cross-spectrum in the frequency domain of the two images is calculated. Calculate the inverse Fourier transform of the cross-spectrum to obtain the cross-correlation function in the spatial domain, and find the position of its maximum value, which represents the translation amount of the two images. The maximum value is . The translation transformation matrix for fine matching is: .

[0207] The final fine registration transformation matrix is: .

[0208] .

[0209] In the high-resolution space, represents the translation amounts of the image in the horizontal and vertical directions, represents the image after transformation; represents the coordinates after inverse transformation, giving the corresponding pixel positions in . The image will be finely registered and transformed and aligned to the image to obtain the aligned image.

[0210] Stitch the third image based on the same steps.

[0211] Step Nine: Image fusion processing.

[0212] Use wavelet transform to perform pixel-level fusion processing on the overlapping regions of adjacent images, eliminate the stitching seam, and obtain a smooth and seamless panoramic image.

[0213] The original image to be fused is subjected to wavelet transform, and then decomposed into different feature domains (high-frequency components and low-frequency components) on different frequency bands; and in combination with the respective characteristics of the high-frequency components and low-frequency components, image fusion is performed separately, forming a new wavelet pyramid structure, and performing inverse wavelet transform on it to synthesize the fused image. Pixel-by-pixel fusion processing is performed on the corresponding pixels of the corresponding sub-band images in each layer and each direction, generating the fused sub-band images, and then performing inverse wavelet transform on the sequence of the fused sub-band images to reconstruct the fused image.

[0214] The obtained image is enhanced by using the wavelet transform algorithm for the fused image. According to the principle of multi-resolution analysis of wavelets, the image is subjected to multi-level two-dimensional discrete wavelet transform, decomposing the image into a low-frequency sub-band of the image approximation signal and a high-frequency sub-band of the image detail signal. Nonlinear image enhancement is performed on the low-frequency sub-band, and wavelet denoising is performed on the high-frequency part to reduce the influence of noise on the image and enhance the contrast of the image. Finally, wavelet reconstruction is performed to obtain the enhanced image, and the display unit displays the processed image, outputting a complete wide-field detection image.

[0215] This embodiment combines the target information obtained by different field-of-view overlaps, and stitches and reconstructs the visible light / short-wave infrared polarization images of different fields of view through an image processing algorithm, which can realize the detection of large-field-of-view space targets, output a complete wide-field polarization detection image, improve the registration speed of the image, and have a better recognition effect of space targets under the space background.

[0216] Based on the same inventive concept, the embodiment of the present application also provides a method for multi-dimensional detection of space targets for implementing the above-mentioned multi-dimensional detection device for space targets. The method for multi-dimensional detection of space targets includes: acquiring polarization images at different field angles; the polarization images at different field angles are determined by the multi-spectrum polarization imaging subsystem according to the multi-field-angle optical path; the multi-field-angle optical path includes the optical paths reflected or emitted by space targets at different field angles. Based on the image processing algorithm, the polarization images at different field angles are stitched and fused to obtain a wide-field detection image and display the wide-field detection image.

[0217] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0218] Specific examples are used in this article to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A multi-dimensional detection device for space targets, characterized in that, The multi-dimensional detection device for space targets includes: a tracking turntable subsystem, a telescopic subsystem, a multi-spectral polarization imaging subsystem, and an image processing and display subsystem; the multi-spectral polarization imaging subsystem is connected to the image processing and display subsystem; the telescopic subsystem and the multi-spectral polarization imaging subsystem are integrated on the tracking turntable subsystem; The tracking turntable subsystem is used to realize the rotation within a set angle range, so as to drive the telescopic subsystem and the multi-spectral polarization imaging subsystem to rotate; The telescopic subsystem is used to obtain optical paths with multiple field of view angles and incident the optical paths with multiple field of view angles on the multi-spectral polarization imaging subsystem; the optical paths with multiple field of view angles include the optical paths reflected or emitted by space targets at different field of view angles; The multi-spectral polarization imaging subsystem is used to determine polarization images at different field of view angles according to the optical paths with multiple field of view angles; The image processing and display subsystem is used to splice and fuse the polarization images at different field of view angles based on image processing algorithms to obtain a wide-area detection image and display the wide-area detection image.

2. The multi-dimensional detection device for space targets according to claim 1, characterized in that, The image processing and display subsystem includes: an information processing unit and a display unit; the information processing unit is respectively connected to the multi-spectral polarization imaging subsystem and the display unit; The information processing unit is used for: Performing sharpening processing on the polarization images at different field of view angles based on a median filtering algorithm to obtain the images to be spliced at different field of view angles; Splicing the images to be spliced at different field of view angles based on wavelet transform algorithms, scale-invariant feature transform algorithms, and particle swarm algorithms to obtain a spliced image; Fusing the overlapping regions of adjacent images in the spliced image based on wavelet transform algorithms to obtain the wide-area detection image; The display unit is used to display the wide-area detection image.

3. The multi-dimensional detection device for space targets according to claim 1, wherein The telescopic subsystem includes: a first front telescopic unit, a second front telescopic unit, and a third front telescopic unit that are distributed in an equilateral triangle; The first front telescopic unit is used to incident a first optical path on the multi-spectral polarization imaging subsystem; the first optical path is the optical path reflected or emitted by a space target at a first field of view angle; The second front telescopic unit is used to incident a second optical path on the multi-spectral polarization imaging subsystem; the second optical path is the optical path reflected or emitted by a space target at a second field of view angle; The third front telescopic unit is used to incident a third optical path on the multi-spectral polarization imaging subsystem; the third optical path is the optical path reflected or emitted by a space target at a third field of view angle; The first optical path, the second optical path, and the third optical path are parallel.

4. The multi-dimensional detection device for space targets according to claim 3, wherein The multi-spectral polarization imaging subsystem includes: a spectral polarization state modulation module, a correction module, and an image acquisition module; the spectral polarization state modulation module is arranged on the output optical path of the telescopic subsystem; the correction module is arranged on the output optical path of the spectral polarization state modulation module; the image acquisition module is arranged on the output optical path of the correction module; The spectral polarization state modulation module is used to generate polarization state modulated outgoing light at different field of view angles according to the optical paths with multiple field of view angles; The correction module is used to correct the polarization state modulated outgoing light at different field angles of view to obtain the corrected outgoing light at different field angles of view; The image acquisition module is used to image the corrected outgoing light at different field angles of view to obtain the polarization images at different field angles of view.

5. The multi-dimensional detection device for space targets according to claim 4, characterized in that, The spectral polarization state modulation module includes: a first polarization state modulation module, a second polarization state modulation module, and a third polarization state modulation module; the optical axis of the first polarization state modulation module is arranged on the output optical path of the first front telescopic unit, the optical axis of the second polarization state modulation module is arranged on the output optical path of the second front telescopic unit, and the optical axis of the third polarization state modulation module is arranged on the output optical path of the third front telescopic unit; The first polarization state modulation module is used to generate the polarization state modulated outgoing light at the first field angle of view according to the first optical path; The second polarization state modulation module is used to generate the polarization state modulated outgoing light at the second field angle of view according to the second optical path; The third polarization state modulation module is used to generate the polarization state modulated outgoing light at the third field angle of view according to the third optical path.

6. The multi-dimensional detection device for space targets according to claim 5, wherein The first polarization state modulation module includes: a first polarization modulation unit and a first filter unit; the first polarization modulation unit is arranged on the output optical path of the first front telescopic unit; the first filter unit is arranged on the output optical path of the first polarization modulation unit; The first polarization modulation unit is used to generate linearly polarized light at the first field angle of view according to the first optical path; The first filter unit is used to filter the linearly polarized light at the first field angle of view to obtain the polarization state modulated outgoing light at the first field angle of view.

7. The multi-dimensional detection device for space targets according to claim 5, characterized in that The correction module includes: a first adaptive optics module, a second adaptive optics module, and a third adaptive optics module; the first adaptive optics module is arranged on the output optical path of the first polarization state modulation module; the second adaptive optics module is arranged on the output optical path of the second polarization state modulation module; the third adaptive optics module is arranged on the output optical path of the third polarization state modulation module; The first adaptive optics module is used to remove the atmospheric interference information in the polarization state modulated outgoing light at the first field angle of view to obtain the corrected outgoing light at the first field angle of view; The second adaptive optics module is used to remove the atmospheric interference information in the polarization state modulated outgoing light at the second field angle of view to obtain the corrected outgoing light at the second field angle of view; The third adaptive optics module is used to remove the atmospheric interference information in the polarization state modulated outgoing light at the third field angle of view to obtain the corrected outgoing light at the third field angle of view.

8. The multi-dimensional detection device for space targets according to claim 7, characterized in that, The first adaptive optics module includes: a first beam splitting unit, a first wavefront correction unit, a first wavefront sensing unit, and a first wavefront control unit; the first wavefront sensing unit is connected to the first wavefront control unit; The first wavefront correction unit includes: a deformable mirror and a deformable mirror driver; the deformable mirror driver is respectively connected to the deformable mirror and the first wavefront control unit; the deformable mirror is disposed on the output optical path of the first polarization state modulation module; the first beam splitting unit is disposed on the output optical path of the deformable mirror, and the first wavefront sensing unit is disposed on the output optical path of the first beam splitting unit; The deformable mirror is configured to deform the polarization state modulated outgoing light at the first field of view angle to generate deformed outgoing light at the first field of view angle; The first beam splitting unit is configured to split the deformed outgoing light at the first field of view angle into two beams and respectively enter the first wavefront sensing unit and the image acquisition module; The first wavefront sensing unit is configured to: perform real-time measurement on the deformed outgoing light at the first field of view angle to obtain a first wavefront aberration; the first wavefront aberration is the optical wave aberration generated by the deformed outgoing light at the first field of view angle under the influence of atmospheric interference; The first wavefront control unit is configured to generate a control signal according to the first wavefront aberration and send it to the deformable mirror driver; The deformable mirror driver is configured to change the shape of the deformable mirror according to the control signal to generate corrected outgoing light at the first field of view angle.

9. The multi-dimensional detection device for space targets according to claim 7, characterized in that The image acquisition module includes: a first image acquisition module, a second image acquisition module, and a third image acquisition module connected to the image processing and display subsystem; the first image acquisition module is disposed on the output optical path of the first adaptive optical module; the second image acquisition module is disposed on the output optical path of the second adaptive optical module; the third image acquisition module is disposed on the output optical path connected to the third adaptive optical module; The first image acquisition module is configured to image the corrected outgoing light at the first field of view angle to obtain a polarization image at the first field of view angle; The second image acquisition module is configured to image the corrected outgoing light at the second field of view angle to obtain a polarization image at the second field of view angle; The third image acquisition module is configured to image the corrected outgoing light at the third field of view angle to obtain a polarization image at the third field of view angle.

10. A multi-dimensional detection method for space targets, characterized in that, The multi-dimensional detection method for space targets is used for the multi-dimensional detection device for space targets according to any one of claims 1-9; The multi-dimensional detection method for space targets includes: Obtaining polarization images at different field of view angles; the polarization images at different field of view angles are determined by the multi-spectral polarization imaging subsystem according to the multi-field of view optical path; the multi-field of view optical path includes the optical paths of the space target reflected or emitted at different field of view angles; Based on an image processing algorithm, stitching and fusing the polarization images at different field of view angles to obtain a wide-area detection image and display the wide-area detection image.

Images