Method and system for monitoring mobile space objects

Abstract

The invention relates to a method for monitoring moving space objects, the method being implemented by a monitoring system (100), comprising the following steps: - sliding acquisition of at least one stack (12, 12') of image frames of space along a known trajectory on the celestial sphere, each stack of frames comprising at least three frames, each frame being recorded with an exposure time of less than 1 second, - detection, in the field of view, of a plurality of stars (14, 55), preferably several dozen, - estimation of the coordinates of the detected stars, - identification of the detected stars with a list of reference stars extracted from a stellar catalog, comprising several thousand reference stars, - establishment of a coordinate relation linking the celestial coordinates to the coordinates in the frames of the stars present in the list of reference stars, - detection of at least one moving space object (15,56) in at least one stack and estimation of their dated frame coordinates, - conversion of the dated frame coordinates of each detected moving space object into coordinates on the celestial sphere by the coordinate relation. Figure for abbreviation: [Fig. 1 ],

Description

Title of the invention: Method and system for monitoring mobile space objects. Technical field

[0001] The present invention relates to a method for monitoring moving space objects. The invention also relates to a system for monitoring moving space objects implementing such a method.

[0002] The field of the invention is, without limitation, that of space surveillance, and in particular that of fine optical estimation of the dated position of objects in Earth orbit.

[0003] In the present document, different types of objects present in space are considered.

[0004] The term “space object” refers to any type of object present in space, including stars, asteroids such as near-Earth objects, and artificial space objects in Earth orbit (RSOs, resident space objects according to English terminology).

[0005] The term “moving space object” refers to space objects, excluding stars. State of the art

[0006] Space surveillance has become a critical issue given the increasing number of satellites, the benefits derived from their operation (Earth observation, positioning, telecommunications, etc.), the proliferation of debris, and so on. Optical or radar measurements are continuously performed around the Earth to detect space-borne objects (SBOs), such as active or deactivated satellites, launch vehicle stages, and debris, visible from each location, and to estimate their state, that is, their positions and velocities at a known time, in a given reference frame. In this document, the state is considered to be their projection parallel to the line of sight, this quantity being accessible through passive optical measurements. The quality of these measurements is a key parameter for their use.They allow the detection of new RSOs as well as orbit estimation from their states, for example to manage collision risks or detect maneuvers.

[0007] Space surveillance also includes the search for near-Earth objects, such as asteroids that pass close to Earth, also called NEOs (near Earth objects) according to English terminology.

[0008] Space surveillance systems are intended, in particular, to maintain the most exhaustive list possible of RSOs and their movements, in order to recognize them each time they pass and monitor the evolution of their parameters. Excluding maneuvers, which are generally of small amplitude, their deterministic trajectory, governed The resolution of these objects, governed by the laws of space mechanics, is entirely determined by a set of six parameters. Ground stations are therefore used to measure the dated positions of these SORs in order to estimate these parameters. It should be noted that SORs are so distant that most are "unresolved" by ground-based observation systems; that is, their image (like that of a star) is indistinguishable from that of a point source, except for its movement relative to the background radiation.

[0009] For certain specific cooperative satellites, that is to say, equipped with laser retroreflectors, radio frequency transmitters / receivers, referred to herein as "reference satellites", ground-based means have been deployed in order to measure their position with centimeter-level accuracy.

[0010] For other satellites, measurement accuracy was not a priority for state-of-the-art space surveillance systems, for several reasons: - Exact orbital calculations are complex and computationally expensive. Simplified algorithms of limited precision (on the order of kilometers), taking into account the effect of higher-order perturbations, are still used and are sufficient for many needs. - Due to the low density of the space population, imprecise orbits were sufficient to identify RSOs, predict their future position and manage the risks of collisions. - It is very difficult to cover the entire celestial vault with high spatial and temporal resolution. The need to cover a wide field of view implies the difficulty of covering it finely, at a fixed data rate. - The measurement rate, that is, the number of square degrees of field per second and the sampling fineness, was limited by the performance of the image sensors and computers.

[0011] However, with the very strong growth in the number of RSOs in space, the precision requirements become more demanding. Description of the invention

[0012] An object of the present invention is to propose a method and a system for monitoring mobile space objects allowing such objects to be monitored more precisely.

[0013] In particular, one object of the present invention is to provide a method and a system for monitoring moving space objects that allows the detection of a potentially tenuous moving space object against a strong background.

[0014] It is another object of the present invention to propose a method and a system for monitoring moving space objects making it possible to locate a moving space object precisely on the celestial sphere at a given time.

[0015] At least one of these objectives is achieved with a method for monitoring moving space objects, a moving space object including an artificial orbital object or a near-Earth object, the method being implemented by a ground-based or space-based monitoring system comprising at least one optical tube or optical lens, at least one camera, a computing unit and a control unit, the method comprising the following steps: - pointing the optical tube along a known trajectory on the celestial sphere, - smooth acquisition, by the camera, of at least one stack of image frames of space according to a field of view, each stack of frames comprising at least three frames, each frame being recorded with an exposure time of less than 1 second, - detection, within the field of view, of a plurality of stars, preferably several dozen, - estimation of the coordinates, in at least one frame and at a given time, of the stars detected in the field of view, - identification of detected stars using a list of reference stars previously extracted from a stellar catalogue, the list comprising several thousand reference stars, - establishment of a relationship, called a coordinate relationship, linking the celestial coordinates to the coordinates in the frames of the detected stars present in the list of reference stars, - detection of at least one moving spatial object in at least one frame stack and estimation of its dated frame coordinates, - conversion of the dated frame coordinates of each detected moving spatial object into coordinates on the celestial sphere using the coordinate relation, and - transmission of coordinates on the celestial vault to the control unit or another computing unit.

[0016] The term "sliding acquisition" refers to the acquisition of frames, or images, according to the pointing trajectory. In other words, during the sliding acquisition of the frame stack, a pointing trajectory is applied to the optical tube.

[0017] Advantageously, the pointing trajectory is substantially linear and at uniform speed in the image plane of the camera.

[0018] According to one embodiment, the pointing trajectory can correspond to a stellar pursuit.

[0019] According to another embodiment, the pointing trajectory can correspond to a pointing trajectory with average speed weighted between the apparent speeds of the stars and the expected moving objects.

[0020] Alternatively, the pointing trajectory may be zero, that is, the optical tube is in fixed aiming.

[0021] Advantageously, the method may include the parameterized modeling of an image spot of a spatial object in the field of view, the image spot having a defined shape and movement, the spatial object comprising a star or a moving spatial object.

[0022] The parameterized model of the image spot can be used during the stages of detecting stars and / or moving space objects, and / or during the fine determination of the coordinates of space objects.

[0023] According to one embodiment, the detection of at least one space object may include the following steps, the space object comprising a star or a moving space object: - choice of at least one exploration path for the frame stack, the exploration path being defined as an offset dx(k), dy(k) applied to each pixel (x, y) in the frame with index k, - calculation in the frame stack, along each exploration path, of a test statistic map for a plurality of pixels (x, y) and offsets dx(k), dy(k) of interest, and - possible extraction of spatial objects whose test statistic is greater than a threshold value.

[0024] It is possible to iterate these steps over a group of exploration trajectories of interest and to extract the spatial objects only at the end of the exploration.

[0025] For example, for stars, the sidereal trajectory can be followed with possible variations to integrate a tracking defect of the mount or field rotation.

[0026] For known RSOs, the expected trajectory can be followed with a margin of variation; for unknown RSOs, a large list of potential velocity vectors can be used, these vectors covering an area of ​​interest in the two-dimensional space of apparent velocities.

[0027] Advantageously, the exploration trajectory can correspond to a uniform linear motion, resulting from the combination of the movement of the spatial objects and the pointing trajectory, the movement of the spatial objects and the pointing trajectory being substantially linear over the duration of the frame stack.

[0028] According to one embodiment, the method further comprises a step of determining the coordinates of the detected space object, the space object comprising a star or a moving space object, the determination of the coordinates comprising at least one of the following steps: - approximation of the spatial object's position by its integer coordinates (x, y) corresponding to the local maxima of the previously calculated test statistic map, - estimation of the sub-pixel coordinates of the detected spatial object through finer positioning of the detected maximum, - refinement of the position of the detected spatial object by optimizing the detection signal-to-noise ratio, with a classic iterative algorithm not based on the quantification of the parameters sought.

[0029] According to one embodiment, the method according to the invention further comprises a step of finely determining the coordinates of a detected space object, the space object comprising a star or a moving space object, the finely determining comprising at least one of the following steps: - modeling the displacement of the moving space object and the observer during the light propagation time between the moving space object and the camera, - modeling of the effect of annual aberration, experienced by stars but not by moving space objects, - modeling, for a scanning sensor, of the effects of variation in the field at the actual time of measurement, - modeling of optical tube distortion using a polynomial of at least third order to establish the coordinate relation, - Modeling of chromatic effects by taking into account a correction term based on the spectral distribution of the spatial object, - modeling the effects of variation in the field of atmospheric refraction, of diurnal aberration by using a polynomial of at least third order to establish the coordinate relation, - modeling of the parallax effect induced by atmospheric refraction.

[0030] These steps allow, alone or in combination, a so-called fine determination of the coordinates of at least one spatial object.

[0031] The coordinates of a moving spatial object include its position.

[0032] Advantageously, the detection of at least one moving space object may also include determining its velocity in the observed plane, its average magnitude and / or its photometric variation.

[0033] The average magnitude can in particular be determined by means of a magnitude relation established using reference stars.

[0034] According to some embodiments, the list of reference stars can be determined from a star catalogue by: the selection of stars based on at least one of the following characteristics: magnitude, temperature, multiplicity, variability, distance to neighboring stars, updating the coordinates of the stars in the list with the Earth's orbital parameters and the characteristics of the stars (distance, proper motion).

[0035] The number of stars detected and the richness of the reference list being such that several dozen stars are identified in the stack of images.

[0036] The sublist of reference stars, obtained by intersecting the stars of the reference star list extracted from the catalog for most of the celestial sphere and the stars detected in the field of view, preferably includes several dozen stars, or even preferably more than a hundred stars. This requires a list of reference stars with a very large number of stars, depending on the field of view of the sensor.

[0037] The reference list can be updated to a date sufficiently close to the observation to take into account the position of the stars at that date.

[0038] Advantageously, the method according to the invention may include a preprocessing step of each stack of frames, prior to the step of detecting a plurality of stars in the field of view.

[0039] According to some embodiments, the pretreatment step may include one or more of the following steps: filtering of frames in the frame stack to eliminate a static background, grouping of frame pixels, reducing the field of view, and / or frame correction based on the system calibration database monitoring.

[0040] According to one embodiment, the method includes fixing the camera integration time for each frame so that during the acquisition time, the movement of a spatial object covers less than 10 pixels of a frame in the frame stack, and preferably less than one pixel.

[0041] Advantageously, the method according to the invention may include precise dating of a frame from the frame stack, preferably at a central instant in the stack.

[0042] This precise timing is on the order of milliseconds, with a typical variation, depending on the precision sought, between ten milliseconds and one tenth of a millisecond.

[0043] The method according to the invention may further include a preliminary step of determining the terrestrial coordinates of the surveillance system.

[0044] The method according to the invention may also include a preliminary or regular calibration step of the monitoring system, and therefore in particular of the telescope and the computing unit or units, by observation of at least one reference satellite.

[0045] According to another aspect of the same invention, a system for monitoring mobile space objects is proposed, comprising: - at least one optical tube or lens, configured to be pointed along a known trajectory on the celestial sphere, - at least one camera, configured for the sliding acquisition of a stack of frames of space according to a field of view produced by the optical tube, the frame stack comprising at least three frames, each frame being recorded with an exposure time of less than 1 second, - a unit of calculation, - a control unit,

[0046] the system being configured to implement a method for monitoring mobile space objects according to the invention.

[0047] Such a system, also called a ground or space station, is a combination of an opto-mechanical device (comprising one or more optical tubes or lenses focusing a stellar field, or field of view, optionally the mount associated with each tube), an image capture system (comprising one or more cameras), acquisition, processing and control means (comprising one or more computers, including RAM memories, possibly graphics processors, storage and communication devices), implementing the algorithms of the process according to the invention.

[0048] The optical tube operates in particular in a wide range of wavelengths, from ultraviolet to infrared.

[0049] The term tube is generally reserved for astronomical instruments. They are sometimes replaced by lenses, a term used in photography.

[0050] Advantageously, the system according to the invention may further comprise one or more spectral filters. These may be put in place, for example, using an insertion module.

[0051] One or more spectral filters can for example be used to reduce the sky background in degraded conditions (for example, during daytime observations).

[0052] The method and system for monitoring moving space objects can be implemented to perform precise orbitography from detailed position and velocity measurements. This allows for better prediction of a satellite's trajectory, for example, opening the way to numerous applications: - maintaining a private catalogue, including items not listed in online catalogues, - early detection of satellite maneuvers, - precise piloting from the ground for on-orbit servicing missions, - more precise assessment of collision risks to minimize the cost of avoidance maneuvers. Description of the figures and methods of implementation

[0053] Other advantages and features will become apparent upon examination of the detailed description of non-limiting examples and the accompanying drawings, in which: - [Fig. 1] [Fig. 1] is a schematic representation of a non-limiting example of a system for monitoring mobile space objects according to the invention, - [Fig.2] [Fig.2] illustrates the principle of generating a pseudo-long-exposure image obtained in the process according to the invention, - [Fig.3] [Fig.3] is a schematic representation of an example of sampling a moving point by a matrix image sensor, - [Fig. 4] [Fig. 4] is a schematic representation of the steps in the monitoring process according to one embodiment of the invention, and - [Fig.5] [Fig.5] illustrates parasitic effects induced during the passage of light through the atmosphere.

[0054] It is understood that the embodiments described below are in no way limiting. In particular, variants of the invention may be conceived comprising only a selection of the features described below, isolated from the other features described, if this selection of features is sufficient to confer a technical advantage or to differentiate the invention from the prior art. This selection includes at least one preferably functional feature without structural details, or with only a portion of the structural details if this portion alone is sufficient to confer a technical advantage or to differentiate the invention from the prior art.

[0055] In particular, all the variants and all the embodiments described are combinable with each other if nothing prevents this combination from a technical point of view.

[0056] In the figures, elements common to several figures may retain the same reference.

[0057] Figure 1 is a schematic representation of a non-limiting example of a system 100 for monitoring moving space objects, which can be implemented within the scope of the present invention. The system 100 according to the example represented can in particular be implemented in a method for monitoring mobile space objects according to the invention.

[0058] The system 100 according to the invention comprises an opto-mechanical system 10, that is, a telescope, for observing the sky from a space or ground station. In the example shown in [Fig. 1], this is a ground station. The telescope 10 comprises an optical tube. The system 10 may also comprise one or more mounts and several optical tubes.

[0059] The optical tube includes optics for focusing a star field, or field of view. The optical tube is pointed by the mount along a known trajectory T on the celestial sphere. One or more image sensors, such as cameras, record series of image stacks 12 of the sky according to a field of view.

[0060] The image sensor, or image sensors, is preferably a CMOS (Complementary Metal Oxide Semiconductor) camera. These cameras with a parallel architecture make it possible to combine a wide field of view with a high readout speed. Even though CMOS sensors may have higher readout noise than CCD cameras, this noise can remain lower than the noise resulting from background accumulation.

[0061] The acquisition with the camera or cameras is a so-called sliding acquisition, due to the realization of the trajectory T by the tube, which can be fixed.

[0062] The acquired images include stars and any moving space objects, such as RSOs. The stars 14 exhibit a deterministic apparent motion R induced by the Earth's rotation (15 arcseconds per second); other motions of lesser amplitude are also present (including annual and diurnal aberration, annual parallax, and proper motion). The moving space objects 15 have an apparent velocity S that varies in direction and magnitude, from approximately 0 (objects near geostationary orbit) to 1 degree per second (objects in low Earth orbit).

[0063] Each image stack, or image frame stack, recorded can be transmitted to a computer, or computing unit 13. This computer detects the stars and any moving space objects present and extracts their image coordinates (x, y) into a reference frame whose precise date is known. These two categories of objects can be distinguished by their velocities, as specified above. From a list of reference stars extracted from a stellar catalog G, a correspondence is established between the image coordinates (x, y) of the stars and the celestial coordinates (a, ô). The image coordinates (x, y) of the space objects can then be converted into celestial coordinates (a, ô). Similarly, in addition, the correspondence between the photometric levels of the pixels and the stellar magnitude scale can be established using the stars in the reference list, constituting a magnitude relation, and thus the magnitudes of the space objects. The apparent speed of moving objects can be estimated. This information is transmitted to a downstream computer, or computing unit. This downstream computer can, for example, perform an orbit estimation.

[0064] The system 100 is governed by a controller 19, or control unit, configured to coordinate the operations performed by the mount, the camera(s) and the computing units 13, 11.

[0065] The computing unit 13 can be located near the telescope 10. It can be connected, for example, by a fiber optic link, or any other high-speed link.

[0066] The downstream computing unit 11 can be located remotely from the telescope 10. A high-speed link is not required.

[0067] For example, for a space system, the computing unit 13 must be on board, and the downstream computing unit 11 can be on the ground.

[0068] The computing units 13 and 11 can also be combined into a single unit. The control unit 19 can also be physically combined with the computing unit(s) 13 and 11.

[0069] These units may include one or more computers, including RAM, possibly graphics processors, storage and communication devices.

[0070] According to one embodiment, a massively parallel computation 13a is performed on a large number of pixels and potentially velocities in order to detect spatial objects of previously unknown position and velocity. In some cases, the velocity may be known (for example, the case of stars).

[0071] This calculation can be performed, for example, by at least one graphics processor, GPU (“graphics processing unit”), to determine indices (position, speed) on a quantized exploration grid.

[0072] According to another embodiment, the detections made during processing 13a are processed in a second pass 13b by a finer calculation from the initial frame stack, restricting the analysis to local areas around the previously made detections. Finer effects, such as chromatic aberration of the refraction or the tube, or the parallax of moving space objects 15 relative to the stars 14, can be included, making it possible to reduce the measurement error to a few tens of milliarcseconds. Thus, from a coordinate relation identified on the stars present in the field and an interpolation polynomial to take into account variations in the field (variation of refraction with the zenith angle, distortion of the optical tube), a precision of less than one arcsecond can be obtained.

[0073] The position (a, ô) of the stars depends slightly on the position of the Earth 27 on its solar orbit, on effects due to its rotation speed (around the Sun 28 and on itself) and on the orientation of its north-south axis in space.

[0074] The image processing carried out by the computer 13 according to the different embodiments will be described in more detail below.

[0075] Advantageously, the system according to the invention may also include one or more spectral filters. These can be put in place, for example, using an insertion module.

[0076] These spectral filters can, for example, be used to reduce the sky background under degraded conditions (for example, during daytime observations).

[0077] Spectral filters, for example in the red - near-infrared and / or in the blue - green, can also be used to estimate a color index on a detected moving space object and on stars, in order to better constrain the chromatic model.

[0078] The surveillance system according to the invention, for example according to the embodiment shown in [Fig.1], can be implemented in a method of monitoring mobile space objects according to the present invention.

[0079] The method according to the invention includes a step of pointing the optical tube by the mount along a known trajectory on the celestial vault.

[0080] Preferably, the pointing trajectory is substantially linear and at uniform speed in the image plane of the camera.

[0081] The pointing trajectory can correspond to a stellar pursuit where the telescope mount compensates for the Earth's rotation.

[0082] The pointing trajectory can also correspond to a pursuit of a moving spatial object, such as an RSO.

[0083] The pointing trajectory can still correspond to a pursuit on a weighted average speed between the stars and a moving space object.

[0084] Alternatively, the pointing trajectory may be zero, that is to say, the optical tube is in fixed aiming.

[0085] During an acquisition step, at least one stack of images of space according to a field of view is acquired. Each image frame stack comprises at least three image frames.

[0086] The image stack can also be called a frame stack, or even an image frame stack.

[0087] Each stack of images or frames comprises a series of consecutive images where the viewing, or pointing, direction varies almost continuously between each image over time. There is no temporal or spatial jump between the images. image stack constitutes a three-dimensional array of values, I(x, y, k), with, for each image, the index k and the pixels (x, y).

[0088] A plurality of frame stacks can be acquired for a plurality of pointing trajectories. These trajectories can be linked, for example, by performing successive aiming directions to perform a monitoring loop for a certain time.

[0089] Each image frame is recorded with an exposure time of less than 1 second. These are therefore called "short-exposure" frames, due to their short exposure time.

[0090] Images from a stack of images acquired in short exposure allow to generate a posteriori an image called pseudo long exposure.

[0091] This pseudo long-exposure image can be used to illustrate the combined effect of the proper motion of space objects, the pointing trajectory of the telescope during acquisition and the multiple stack exploration trajectories selected during processing, as set out below.

[0092] Figure 2 illustrates the principle of generating a pseudo-long-exposure image from a stack of 12 (temporal, along k) images. Each image comprises an (x, y) grid of pixels. The images are acquired in "short exposure" mode (i.e., with an exposure time of less than 1 second) while the telescope follows a predetermined pointing trajectory. The observed field includes 14 stars and potentially at least one moving space object 15, such as a solar SAR.

[0093] The calculation of the so-called pseudo long-exposure image amounts to summing the image frames of the stack 12 by applying a certain offset dx(k), dy(k) 13 on each frame.

[0094] The image stack 12 can be acquired using different sliding acquisition modes, depending on the pointing trajectory chosen. Regardless of the pointing trajectory chosen, it is possible to calculate a posteriori numerous pseudo long-exposure images according to the chosen offset, as illustrated at the bottom of [Fig. 2].

[0095] Indeed, the offset 13 between the frames can be obtained either during acquisition, by choosing the pointing trajectory, or a posteriori during the calculation of the pseudo long-exposure image. In the first case, the offset is unique and fixed during acquisition. In the second case, the offset is adjustable at will during processing.

[0096] Fig. 2(a) represents the pseudo-long-exposure image obtained with zero offset, symbolized by arrows 16, applied to the battery 12 while the telescope is in sidereal tracking. In this case, the telescope corrects for the Earth's rotation. The fixed stars form spots 14' on the pseudo-long-exposure image. The moving SAR appears as a trail 15'.

[0097] Fig. 2(b) corresponds to the pseudo long-exposure image calculated with zero offset, symbolized by arrow 17', in the case where the telescope is tracking the RSO, giving rise to another 12' stack of frames. On the sensor, the RSO produces a 15' spot and the stars form elongated 14' tracks.

[0098] It should be noted that a similar pseudo long-exposure image can be produced with stack 12 (i.e., with the telescope in sidereal pursuit) by shifting the frames according to 17 during summation.

[0099] Fig. 2(c) corresponds to the pseudo long-exposure image calculated in an intermediate case.

[0100] According to a first possibility, this intermediate case can be obtained with the telescope in stellar tracking (the frames are then aligned as in the left stack 12) and an offset according to arrow 18.

[0101] According to a second possibility, the telescope is tracking the SSR, producing a stack of 12' images, and an 18' offset is applied to this 12' stack.

[0102] According to yet another possibility (not shown), the pointing trajectory follows the average speed between the sidereal speed and the speed of the SSR, and the offset during summation is zero.

[0103] In the case of [Fig.2](c), the two types of objects produce 14', 15' tracks of identical length. The directions of movement of the SAR spot on the one hand and the star spots on the other are reversed.

[0104] In the illustrated example, in [Fig.2](c), the length of the traces corresponds to half that of the traces in Figures 2(a) and 2(b), respectively.

[0105] The acquisition of a stack of frames 12, combined with the calculation of a pseudo-long-exposure image with a shift 13, allows, for example, while the telescope is in stellar tracking mode, the synthesis of both a pseudo-long-exposure image of the stars (simple sum of the frames along 16, image in [Fig. 2](a)) and a pseudo-long-exposure image in tracking mode on the SAR (oblique sum of the frames with a suitable shift 17, image in [Fig. 2](b)). This allows for better detection of both the SAR and the stars.

[0106] Furthermore, in the image of [Fig. 2](a), the direction of movement of the SNR cannot be determined from the pseudo-long-exposure image alone, or from the long-exposure image that would have been obtained with a single frame associated with the total integration time. It is nevertheless possible to determine it from the short-exposure images by producing the pseudo-long-exposure image with an offset corresponding to the speed of the SNR to form the image of [Fig. 2](b). This makes it possible to identify the speed and therefore the type of objects in the image, including in a case such as that leading to the image of [Fig. 2](c), which can be obtained by a combination of the pointing trajectories and the applied offset.

[0107] As explained above, the pseudo long-exposure image of [Fig.2](c) can be obtained in at least three ways: with a pointing trajectory following the stars or the RSO, and the associated offsets 18 or 18' when processing the stack, or with a pointing speed equal to the average of the two previous pointing speeds, and a zero offset.

[0108] Advantageously, in the latter case, the apparent velocity of the image spots, formed by moving sources such as SORs or stars, is halved on the camera. Indeed, the overall performance of the monitoring system depends on the ability to locate both the SORs and the reference stars. Tracking one of these objects can lead to an inaccurate estimation of the other, particularly due to the elongation of the spot introduced by the movement of an object within each frame. With average-velocity tracking, possibly weighted by the characteristics (number, magnitude) of the objects (stars, SORs) expected in the field, the apparent velocities of the star and the SOR are jointly reduced, and intra-frame displacement is minimized. Reducing the size of the image spot increases measurement accuracy. It also increases the integration time, leading to a gain in sensitivity.As a result, the number of frames to be processed can be reduced, and the signal-to-noise ratio on these frames can be increased.

[0109] During the acquisition step, the camera integration time for each frame is fixed so that during the acquisition time, the movement of a spatial object covers less than ten pixels of a frame in the frame stack, and preferably less than one pixel.

[0110] The integration time can be set based on prior knowledge of the moving space objects to be detected or observed. For example, for slow-moving targets, integration times that are not too short, representing a compromise between a good signal-to-noise ratio and perturbations induced by turbulence, can be chosen. The faster the moving space objects to be observed or detected, for example in lower orbits, the more beneficial it is to reduce the integration time, within the limits of the camera and computing unit's capabilities.

[0111] Fig. 3 is a schematic representation of an example of sampling a moving point by a matrix sensor, such as a camera.

[0112] As illustrated in [Fig. 3](a), for a single image or frame, the Cartesian geometry of the pixels allows, on the one hand, the measurement of an average value on each pixel (represented by the hatched area 31) and, on the other hand, the performance of sampling represented by the disks 32 designating the locations where these average values ​​are measured. The sampling interval then corresponds to a square such as that represented by the dotted square 33.

[0113] In [Fig. 3](b), we consider the case of a star 34 moving at an angle of 45° relative to the sensor's pixel grid, the displacement being indicated by arrow 35. The 45° angle is an example chosen to simplify the demonstration. Of course, the angle relative to the grid can have other values. If the star's speed is known, it is possible, by adjusting the sensor's integration time, to perform sampling when the star's displacement distance is equal to half a pixel diagonal. It is then equivalent to moving the sensor in front of the fixed star, which amounts to sampling it on an offset pixel grid, this offset grid being represented by rings 32'. The combination, over two successive frames, of these two grids ultimately gives an oblique square grid with a pitch 2-l' less than the sampling pitch in the case of [Fig. 3](a).This reduced sampling step is represented by the dotted square 33' in [Fig.3](b).

[0114] Moving the observed spatial object in front of the sensor then increases the sensor's sampling resolution. This technique can be implemented in several ways in the method according to the invention using image stacks, and in particular with a sliding acquisition:

[0115] - exploitation of the natural displacement of a RSO, even if unknown, in standby mode with stellar pursuit,

[0116] - application of a known displacement to improve star sampling, for example such as in [Fig.3] of half a pixel at 45°,

[0117] - in the case where the speed of the RSO is too high to constrain The elongation of the image spot to a small value in one direction, it is possible, by choosing the pointing speed during two successive sliding acquisitions, to force the elongation of the spot in two orthogonal directions judiciously oriented with respect to the pixels in order to measure alternately and precisely each of the two components.

[0118] At least one frame in the frame stack is precisely time-stamped, preferably at a central point in the stack. This time-stamping can be achieved by TTL synchronizing the camera to a reference signal, for example, from a GPS sensor. Thus, the recorded images are correctly time-stamped using a Coordinated Universal Time (UTC) reference.

[0119] A timing on the order of milliseconds makes it possible to obtain, on an object of the type of positioning satellite (global navigation satellite System, GNSS), moving at about 40 arcsec / s and for this single error station, a precision of a few tens of arc milliseconds.

[0120] In [Fig.1], the dating is illustrated by a clock symbol.

[0121] According to embodiments, the process according to the invention includes a preprocessing step for each stack of frames.

[0122] The preprocessing step may include, on the one hand, steps or actions to correct the image stacks.

[0123] The frames in the frame stack can be filtered to eliminate a static background. Reducing the background allows, in particular, an increase in the detection limit magnitude.

[0124] A pixel binning technique can be applied. Pixel binning can be achieved, for example, by retaining the maximum of the pixels, or of the pixels correlated by the kernel of a suitable filter, or by retaining the average value of the pixels.

[0125] The images in the image stack can be corrected on the calibration database of the monitoring system, allowing for the correction of disparities between pixels.

[0126] On the other hand, preprocessing makes it possible to reduce each stack of images.

[0127] In particular, it is possible to reduce the field of view. Reducing the field to a region of interest or binning allows processing on the fastest SARs or the widest fields.

[0128] Preprocessing the image stack thus makes it possible to eliminate certain unnecessary signals (by removing the background or transient events). It also makes it possible to accelerate processing (by reducing the field of view or grouping pixels) or to correct calibrated defects (pixel gain map).

[0129] During a processing phase of the method according to the invention, the image frame stack(s) are processed in order to detect any moving spatial objects in these images. According to embodiments, the processing phase comprises the following steps.

[0130] During a modeling step, an image spot of a spatial object in the field of view is represented by a parameterized model. The image spot has a defined shape and motion. The spatial object may be a star or a moving spatial object.

[0131] The image spot can be modeled by a spot of known shape, for example of Gaussian shape, of width l, moving in a uniform rectilinear motion of speed v passing through a position p. The parameters p, v and l are then sought.

[0132] In the case where a small optical telescope is used and over relatively short periods of time, the image spot of a space object is a spot in uniform rectilinear motion for the pointing trajectories considered. The space object is characterized by a position (x0, y0) at an arbitrary time, a velocity (u, v) and a light intensity (expressed by an energy level deposited on the pixel), which can be expressed, after calibration of the camera, by a number of photons N per unit time.

[0133] The coordinates, in the image plane of each frame, of stars present in the field of view are estimated.

[0134] For this purpose, a plurality of stars, preferably several dozen, are detected in the field of view. This detection can be carried out on a suitable pseudo-long-exposure image (fixed stars) or by searching along a suitable exploration trajectory.

[0135] The search along an exploration trajectory is carried out as set out below with reference to [Fig.4].

[0136] Stars can be distinguished from other space objects by their specific apparent motion.

[0137] The coordinates of the stars are represented in the image plane by the indices of the corresponding pixels (two pixel indices, which may optionally be interpolated).

[0138] The detected stars are then identified using a reference star list extracted from a stellar catalogue. This list includes a very large plurality of stars, preferably several thousand, so that several dozen stars from this plurality can be used in each acquisition field.

[0139] To carry out this step, the stars detected in the field of view are identified using the reference star list and suitable software known to those skilled in the art. Their positions in the image are then associated with their coordinates from the star list.

[0140] Celestial coordinates may include, for example, right ascension and declination in the International Celestial Reference System (ICRS).

[0141] The list of the plurality of reference stars can be established by selecting stars based on at least one of the following characteristics: magnitude, temperature, multiplicity, variability, distance to neighboring stars.

[0142] In the method according to the invention, a relationship, called a coordinate relationship, linking celestial coordinates of the reference stars to the coordinates of the stars in the image frames is then established.

[0143] According to one embodiment, establishing the coordinate relationship between pixel and celestial coordinates can be achieved by taking into account one or more spectral characteristics of the observed stars, such as temperature, a color index, or a magnitude difference between two spectral bands. These spectral characteristics are also provided by a star catalog and allow the establishment of the coordinate relationship to be refined by a chromatic refraction model.

[0144] Advantageously, the use of a large number of reference stars in establishing the coordinate relation makes it possible to precisely adjust a interpolation polynomial of sufficient order. It also allows averaging, in the field, the residuals of atmospheric turbulence, representing one of the most difficult stochastic perturbations to correct.

[0145] The list can be updated by updating the coordinates of the stars in the list with the Earth's orbital parameters and the characteristics from the catalogue of these stars, at a time sufficiently close to the observation. For this purpose, the list of stellar reference stars is adjusted prior to the observation, at a date close to the time of observation or detection, with all known deterministic elements, such as those resulting from the proper motion of the stars or of the Earth (stellar parallaxes, aberrations of light).

[0146] During a detection step, one or more moving spatial objects are detected in at least one frame stack.

[0147] According to one embodiment, to perform this detection, at least one exploration path of the frame stack is chosen. The exploration path is defined as an offset dx(k), dy(k) applied to each pixel (x, y) in the frame with index k.

[0148] Preferably, the exploration trajectory corresponds to a uniform linear motion, or its approximation over an entire grid, resulting from the combination of the motion of the spatial objects and the pointing trajectory, the motion of the spatial objects and the pointing trajectory being substantially linear over the duration of the frame stack.

[0149] The pixels of interest, forming the exploration path, may exclude, in particular, pixels close to the edge of the frames because image processing is not applicable there due to the offsets induced by the exploration path.

[0150] In the frame stack, a test statistic map is calculated for a plurality of pixels (x, y) and dx(k), dy(k) offsets of interest along each scan path.

[0151] From the statistical test map, spatial objects whose test statistic is greater than a threshold value can be extracted.

[0152] The test statistic map can be obtained by dividing the sum, on each frame k of the frame stack, of the intensity of each pixel I(x, y, k) by the sum of the inverses of the standard deviations of the fluctuations associated with the pixel at I(x, y, k). This is equivalent to calculating a signal-to-noise ratio on a pseudo-long-exposure image.

[0153] Advantageously, the test statistic map can also be obtained by suitable filtering, in particular by summing along the exploration path of each frame k the intensity of the pixels I(x + dx(k), y + dy(k), k) on the shape and position of the expected image spot, with inverse signal-to-noise weighting and ad-hoc normalization.

[0154] This calculation will be described in more detail with reference to [Fig.4].

[0155] It is possible to iterate these steps over a group of exploration trajectories of interest. To do this, it would ultimately be necessary to identify the maximum values ​​of the test statistic for all the explored trajectories. To limit the volume of data to be stored, it is possible to store (for example, in two dedicated numerical arrays referred to here as maps), for each value of the position (x0, y0) defining the exploration trajectory, the current maximum of the test statistic and the associated velocity index. At the end of the iteration, analysis of the maps can determine the detections and the associated velocity parameters.

[0156] It is important to note that the exploration trajectory, applied a posteriori to the image frame stack and not during acquisition as does the pointing trajectory, acts on the displacement of the moving object from one frame to the next (inter-frame effect) but that it cannot, unlike the pointing trajectory, act on the effect of the movement of the object during the integration of each frame (intra-frame effect). Thus, for [Fig.2](b), the pseudo-long exposure image associated with an SAR tracking (12' stack) and a summation along 17' will produce an SAR image spot of smaller extent, and therefore positioned with better precision, than the pseudo-long exposure image associated with a sidereal tracking (12' stack) and a summation along 17. It is to simultaneously minimize the extension due to the intra-frame displacement of stars and SARs that the average pointing trajectory is proposed ([Fig.2](c)).The inter-frame extension is corrected by the exploration trajectory specific to each object.

[0157] It is possible to fail to detect moving space objects in certain frame stacks. For example, several stacks may be recorded for different successive directions, where only some of the stacks contain moving space objects. For another part, the images may have been taken in a region of the sky where no moving space objects are present, or sufficiently visible.

[0158] The dated frame coordinates of the moving spatial objects are estimated.

[0159] The dated frame coordinates of the detected moving spatial objects are converted into coordinates on the celestial vault by the coordinate relation established previously.

[0160] The coordinates of a moving space object include its position.

[0161] The moving space object can also be characterized by its speed in the observed plane, and / or its average magnitude and / or its photometric variation.

[0162] According to one embodiment, the determination of the coordinates of a detected spatial object can be carried out according to one or more of the following variants.

[0163] According to a first variant, the position of the spatial object is approximated by its integer coordinates (x, y) associated with the maxima of the statistical test map calculated during the detection step.

[0164] According to a second variant, sub-pixel coordinates are obtained by a continuous estimator (such as the position of the center of gravity or interpolation in the vicinity of a vertex assumed to be locally parabolic) applied around the maximum, corresponding to the detection of the object, of an image map. The image map can be the statistical test performed or the pseudo-long-exposure image resulting from the exploration trajectory associated with the detection.

[0165] Advantageously, according to a third variant, the non-integer values ​​of the coordinates (a, b) and the velocities (un, vn) are sought by maximizing the signal-to-noise ratio (SNR). This simply requires using a conventional iterative optimizer, known to those skilled in the art, applied to the calculation of the SNR defined below. This procedure can be initialized with the values, integer or non-integer, obtained by one of the two preceding variants. Advantageously, the calculation can be performed on only a sub-part in (x, y) of the image frame stack, extracted in the vicinity of the scanning path that led to the detection.

[0166] The coordinates on the celestial vault thus measured are transmitted to a control unit or another computing unit, for example, for orbitographic calculations.

[0167] Figure 4 is a schematic representation of steps in the monitoring process, and including steps in the processing phase including the detection of spatial objects, according to a non-limiting example of an embodiment of the invention.

[0168] Figure 4 represents the two extreme frames (k = 0 and k = Kl) of a stack of K images, in which a space object moved during the acquisition. In the example shown, the space object is a star. Of course, it could also be a solar ion.

[0169] The stack of recorded frames is I(x, y, k) where k denotes the frame index and (x, y) the two-dimensional coordinates of the pixels of each frame.

[0170] The coordinates on the pixel grid of the successive positions of the star, or of the displacement vectors, are not a priori integers.

[0171] To exploit the fact that the movement of the spatial object is rectilinear and uniform, the processing relies on adapted filtering, which consists of projecting the stack onto a series of known trajectories. These trajectories are defined by a point, for example the coordinates (a, b) in the first frame (k = 0), and a two-dimensional velocity with components (un, vn), expressed in pixels per frame.

[0172] The velocities are indexed by an index n which can take many values. For example, for satellites in circular orbit between the upper part of the medium Earth Orbit (MEO) moving at about 50 arcseconds / s and the geostationary Earth Orbit (GEO) with very low speed, a granularity of 0.5'7s in the velocity grid leads to a 100x100 grid, i.e. 10000 velocities to be considered.

[0173] In particular, for the search for satellites without preconceptions, setting a maximum search altitude leads to a maximum apparent velocity. It is then possible to explore all velocities (u, v) within a disk whose radius is this maximum velocity and whose granularity is adapted to the desired accuracy, the available computing power, and the expected signal-to-noise ratio (SNR).

[0174] The calculation, or the processing, can be broken down into two steps.

[0175] First, on each frame k, the signal S and noise B contributions are calculated on each trajectory:

[0176] [Math.l] 5^(^0)=2^ / (^ h(xa-ku n ,yb-kv n ) w 2 (x, y),

[0177] [Math.2] B^a, b) =^ x h 2 (xa-ku a , yb-kv D ) w 2 (x, y),

[0178] where h is a model of the shape of the image spot, which can cover several pixels as illustrated by disk 41 of [Fig.4], and has a very rapid decay.

[0179] Of course, to limit the computational volume, for each value of (a, b) the sum over (x, y) may only cover the few pixels defined by the support of h, that is, the area over which h is significantly non-zero. We recognize in kun and kvn the the previously mentioned shifts dx(k) and dy(k), which could have been applied to I and w, but which are here applied to h, unique and of small support.

[0180]

[0181] The term w(x, y) is a weighting map of each pixel in the stack and in based on its noise characteristics: [Math.3] '0 if pixel defective' . [ ^ron^' y)+MfoBd(x, y)]

[0182] where oron is the standard deviation of the image sensor read noise determined during a preliminary calibration of the sensor, and Mond, determined during preprocessing, is the average sky background level. Since these noises are uncorrelated, their variances are additive. It is assumed that the spatiotemporal variation of the background is negligible along the pointing trajectory during image stack acquisition.

[0183] Secondly, the total contributions per frame are calculated on each trajectory:

[0184] [Math.4] S a (a,b)=\S nJ[ (a,b);

[0185] [Math.5] Bl(a,b) =\B 2 j.(a,b);

[0186] [Math.6] T' / ~ RA _ Sn(a,b) 1 n\d, JJ) - B^y

[0187] The final statistical test Tn is recognized as a statistical test based on an adapted filtering, projection of the current signal weighted by its noise onto the expected signal and normalized by the projection of the expected signal onto itself.

[0188] A satellite is considered detected when Tn exceeds a typical value of 7. The associated position in a reference frame is then given in (a, b), and an estimate of the velocity in (un, vn). An estimate of the magnitude is provided by S. These quantities, in coordinates or pixel levels, are then converted into stellar data (angles, angular velocities, and magnitudes) by the correspondence established on the reference stars, that is, using the coordinate and magnitude relationships established previously.

[0189] Possible false detections can be rejected during later steps, for example during revisit steps or orbitographic calculations.

[0190] The two-step calculation as described above allows for the simple elimination of "outliers," that is, aberrant values, such as those originating from cosmic rays. To achieve this, for each n, the one or two highest values ​​of the 5nJt, as well as their associated Bnk values, are not taken into account in the calculation of Sn and Bn. For example, when the calculation involves K = 100 frames, the systematic loss of 2 frames has very little effect on the result.

[0191] The difficulty with this calculation is that the final result, which can be written as RSBn(a, b), has a dimension (number of pixels, number of speeds), which can quickly lead to very high memory usage. Furthermore, as outlined in [Fig. 4], several speeds (indicated by the arrows) on the search grid, different from the actual speed but close on the quantization grid, will detect a strong presence signal corresponding to the same object.

[0192] To overcome these two problems, and as detailed above, it suffices during the loop on the speeds (n), to store, in only two arrays indexed in (a, b), only the value of the maximum of RSBn(a, b) and the value of the associated n to determine in the end the probability of presence of a satellite and its speed (un, vn).

[0193] Improbably, two objects such as RSOs could intersect on the same reference pixel. The less luminous one would then go undetected. If necessary, a second pair of arrays storing the secondary maximum, combined with a "speed proximity threshold," would solve this problem, and other pairs would handle even less probable cases if needed.

[0194] Advantageously, the method according to the invention also includes a phase of fine determination of the coordinates of a moving spatial object detected in the previous step.

[0195] When using a ground-based monitoring system, the atmospheric effects experienced by the light beam passing through the atmosphere must be taken into account when determining the coordinates of a space object. Indeed, the main limitation of angular position measurements of stars or SORs by ground-based means stems from the atmosphere. Atmospheric refraction introduces a bias exceeding one arcminute for elevations below 45°. This correction is achieved by measuring the coordinates of the detected SORs and converting them into celestial coordinates using the established coordinate relation. The effects of turbulence, i.e., high-frequency random motion, average over the estimated position over a long period. A long-exposure image of any quasi-point-like celestial object is approximately a Gaussian with an angular width on the order of one arcsecond at the zenith in a good observing site..

[0196] For measuring the position of an image spot, the accuracy o is on the order of o = L / RSB, where L is the full width at half maximum of the spot and RSB is the signal-to-noise ratio.

[0197] Thus, from spots limited by atmospheric turbulence in long exposure (width of the order of L = 2" for observations at 45° elevation in an average site), one can obtain a precision of the order of 0.05" with an RSB of 40.

[0198] With short-exposure images, a large part of the turbulence is eliminated. It is known that 90% of the effect of turbulence is contained in the fluctuation of the beam's angle of arrival. Moreover, most of this directional perturbation is at low frequencies, with a cutoff frequency of approximately 0.3v / D, where v is the wind speed and D is the telescope diameter, or about 10 Hz for typical conditions (v = 10 m / s and D = 0.3 m). It is therefore known that, on a small telescope, once this fluctuation in the angle of arrival within each short-exposure image is eliminated, the effect of turbulence is reduced to the random movement of a smaller spot. An exposure time of 0.1 s thus makes it possible to reduce the extent L of each short-exposure image, and therefore the noise in the measurement of its position.Summation over several seconds, on the RSOs but also on the stars in the field, allows the position fluctuations between the frames to be averaged and makes the average tend towards the same position as that obtained on the equivalent long-exposure image.

[0199] The precise determination of the coordinates can be carried out by one or more of the following steps or actions to take into account atmospheric effects.

[0200] The effects of variation in the field of atmospheric refraction, diurnal aberration or tube distortion can be modeled by using a polynomial of at least third order to establish the coordinate relation.

[0201] Chromatic effects (due to atmospheric refraction or aberrations of a tube or lens comprising dioptric elements) can be modeled by taking into account a correction term based on the spectral characteristics of the space object, known from a catalogue, approximated or measured by spectroscopy.

[0202] The parallax effect induced by atmospheric refraction, which depends on the distance of the moving space object to the optical tube, can also be modeled.

[0203] For terrestrial or space-based surveillance systems, the precise determination of coordinates can still be achieved by one or more of the following steps or actions.

[0204] Can be modeled: - the movement of the moving space object, such as a satellite, and of the observer during the time it takes for light to travel between the satellite and the camera, - the effect of annual aberration, experienced by stars but not by moving space objects, and / or - in the case of using a scanning sensor, or rolling shutter sensor, the effects of variation in the field of the actual moment of measurement.

[0205] The steps or actions for the fine determination of coordinates can be applied to both stars and moving orbital objects. Some steps are reserved for RS O.

[0206] Figure 5 illustrates parasitic effects induced during the passage of light through the atmosphere. The density of the atmosphere, continuously varying between the ground 51 and space, is represented by two homogeneous layers 52, 53.

[0207] In [Fig. 5], the atmospheric effects considered below are drawn in an exaggerated manner for better visibility. The description first focuses on the main ray 54, shown in a thick solid line, and then on the ray 54' of another color, shown in a thick dashed line.

[0208] For a star 55 (very distant, appearing to come from a direction 0) observed by a T-shaped telescope, the pressure gradient, and therefore the refractive index, of the air bends the light rays, causing the star to appear after passing through the atmosphere as coming from the direction 1. This atmospheric refraction is characterized by an angle R which is greater the greater the distance to the zenith, in the direction Z and characterized by the zenith angle z.

[0209] Thus, the compensation of the effect of atmospheric refraction is achieved by the coordinate relation, allowing the moving space object to benefit from the very good knowledge of the position of the reference stars present in the field.

[0210] Since the refractive index of air is chromatic, that is, it depends on the frequency of the radiation considered, the deviation R is also chromatic. The image of a broad-spectrum source, such as a star or a solar radiation system (SRS), is in the form of a small segment of angular extent dR. The temperature of the star, which determines the energy distribution among the frequencies detected by the sensor, then modifies the position of the apparent center of the segment and therefore the effective value of R.

[0211] Fig. 5 shows that atmospheric deflection also induces a displacement Lateral displacement of amplitude b of the beam. This lateral displacement is not taken into account in astronomy because it has no impact for an object at infinity. If we consider a nearby object such as a 56 SAR (represented by a black disk), located at position 2 and therefore aligned with the star for an observer at position T, its apparent position will be perceived, depending on the color, at positions 1 and 1'. This deviation can reach several arcminutes. It is therefore important to apply to the SAR the angular correction R determined on the star. Applying this correction is equivalent to placing the SAR at position 0. This corresponds to making a parallax error relative to the actual position 2. The parallax, expressed as P = b / h, is greater the lower the altitude h of the SAR.

[0212] It is therefore advantageous to include in the processing the deterministic numerical correction (once the distance h is known) of these terms P and dR (typically less than one arcsecond) after having applied the necessary parallax correction R (typically one arcminute) determined on the stars.

[0213] For the fine determination of coordinates of a previously detected moving spatial object, the image stack is limited to a local sub-tube in the vicinity of the previously performed detection.

[0214] The parameters obtained by the fine determination include the position of the moving spatial objects and an estimate of the uncertainty on the estimated position.

[0215] The parameters returned by the fine determination allow in particular to adjust the shape of an image spot in a stack of images, this spot being assumed to be of Gaussian shape beforehand for the detection of moving spatial objects.

[0216] According to embodiments, the process according to the invention includes preliminary preparation or calibration steps.

[0217] In particular, the method according to the invention may include a preliminary step of determining the terrestrial coordinates of the telescope in the case of a terrestrial surveillance system.

[0218] This position can be refined by observing reference satellites and seeking the coordinates of the telescope which minimize the difference between the measured dated positions of these satellites and the dated positions tabulated elsewhere.

[0219] Reference satellite observation can also be repeated regularly to ensure the quality of the measurements.

[0220] Observing space in "short-exposure image stacks" mode has many technical advantages compared to observing from a single long-exposure image, depending on the operations performed.

[0221] It is possible to determine the direction of movement of objects.

[0222] The background level added to the signal of moving spatial objects is reduced, in This is particularly true in the infrared range, where the background level is very high. Indeed, as soon as a moving object leaves a pixel, continuing integration no longer provides a signal but only background noise, and its associated shot noise.

[0223] The average background level can be estimated locally on each pixel (for example, by a median filter applied according to k on the stack).

[0224] Parasitic events can be filtered. Indeed, the loss of a few pixels in a long stack of frames is less detrimental than in a single image.

[0225] This mode of observation also has the advantage of being able to accept a drift or a rotation (locally linear) around the line of sight, whether intentional (sliding acquisition) or suffered (poorly controlled pointing of a terrestrial or space telescope, field rotation induced by a non-equatorial mount).

[0226] The diameter of the image spots of the observed SSRs, as well as of reference stars, can be reduced, thereby increasing positioning accuracy. This is achieved in particular by filtering out a large part of the atmospheric turbulence, such as the low-frequency fluctuation of the angle of arrival.

[0227] Image sensor sampling by spot movement is refined. The estimation of the position of a spatial object is therefore also refined, whereas a single elongated image leads to a less accurate estimation. This refinement of sampling can make it possible to move beyond the classic "sidereal tracking" mode in order to benefit from the "sliding sensor" effect, even on stars. The "sliding sensor" effect, induced by the inherent movement of moving objects or, in the case of stars, by sliding acquisition along a pointing trajectory different from the sidereal motion, leads to a beneficial averaging of local sensor inhomogeneities. In particular, it is thus possible to use, without significant degradation, sensors with a few defective pixels, which are less expensive than higher-quality sensors, especially for large dimensions.

[0228] Of course, the invention is not limited to the examples just described and many modifications can be made to these examples without departing from the scope of the invention.

Claims

1. Demands Method for monitoring moving space objects, the method being implemented by a ground-based or space-based monitoring system (100) comprising at least one optical tube or lens, at least one camera, a computing unit (11, 13) and a control unit (19), the method comprising the following steps: - pointing the tube or optical lens along a known trajectory on the celestial sphere, - sliding acquisition, by the camera, of at least one stack (12, 12') of image frames of space according to a field of view produced by the optical tube, each stack (12, 12') of image frames comprising at least three image frames, each image frame being recorded with an exposure time of less than 1 second, - detection, in the field of view, of a plurality of stars (14, 55), preferably several dozen, in at least one stack (12, 12') of image frames, - estimation of the coordinates, in at least one frame and at a given time, of the stars detected in the field of view, - identification of detected stars using a list of reference stars, previously extracted from a stellar catalogue, the list comprising several thousand reference stars, - establishment of a relationship, called a coordinate relationship, linking the celestial coordinates to the coordinates in the image frames of the stars present in the reference star list, - detection of at least one moving spatial object (15, 56) in at least one image frame stack and estimation of their dated frame coordinates, - conversion of the dated frame coordinates of each detected moving spatial object into coordinates on the celestial sphere using the coordinate relation, and - transmission of coordinates on the celestial vault to the control unit (19) or to another computing unit.

2. A method according to claim 1, further comprising the parameterized modeling of an image spot of a spatial object in the field of view, the image spot having a defined shape and movement, the spatial object comprising a star (14, 55) or a moving spatial object (15, 56).

3. A method according to any one of the preceding claims, characterized in that the step of detecting at least one space object comprises the following steps, the space object comprising a star or a moving space object: - selection of at least one exploration trajectory of the stack (12, 12') of image frames, the exploration trajectory being defined as a dx(k), dy(k) offset applied to each pixel (x, y) in the frame of index k, - calculation in the stack (12, 12') of frames, along each exploration trajectory, of a test statistic map for a plurality of pixels (x, y) and dx(k), dy(k) offsets of interest, and - possible extraction of space objects whose test statistic is greater than a threshold value.

4. A method according to the preceding claim, wherein the exploration trajectory corresponds to a uniform linear motion, resulting from the combination of the motion of the space objects and the pointing trajectory, the motion of the space objects and the pointing trajectory being substantially linear over the duration of the frame stack, the space objects comprising stars (14, 55) and / or moving space objects (15, 56).

5. A method according to any one of the preceding claims, characterized in that it further comprises a step of finely determining the coordinates of a detected space object, the space object comprising a star (14, 55) or a moving space object (15, 56), the finely determining comprising at least one of the following steps: - Modeling the displacement of the moving space object and the observer during the propagation time of light between the moving space object and the camera, - Modeling the effect of annual aberration, experienced by stars but not by moving space objects, - Modeling, for a scanning sensor, the effects of variation in the field at the effective time of measurement; - Modeling the effects of variation in the field of atmospheric refraction, diurnal aberration or distortion of the optical tube by using a polynomial of at least third order to establish the coordinate relation, - Modeling of chromatic effects by taking into account a correction term based on the spectral distribution of the space object, - Modeling of the parallax effect induced by atmospheric refraction.

6. A method according to any one of the preceding claims, wherein the detection of at least one moving space object (15, 56) includes determining its velocity in the observed plane, its average magnitude and / or its photometric variation.

7. A method according to the preceding claim, characterized in that the list of reference stars is determined from a stellar catalogue by: - ​​selecting stars based on at least one of the following characteristics: magnitude, temperature, multiplicity, variability, distance to neighboring stars, and / or - updating the coordinates of the stars in the list with the Earth's orbital parameters and the characteristics of the stars, at a date close to the observation.

8. A method according to any one of the preceding claims, characterized in that it further comprises a preprocessing step of each stack (12, 12') of image frames, prior to the step of detecting a plurality of stars (14, 55) in the field of view.

9. A method according to the preceding claim, characterized in that the preprocessing step comprises one or more of the following steps: - filtering the frames of the (12, 12') frame stack to eliminate a static background, - grouping pixels of the frames, - reducing the field of view, and / or - correcting the frames on the basis of the calibration database of the monitoring system.

10. A method according to any one of the preceding claims, characterized in that the pointing trajectory corresponds to - a stellar pursuit, - a zero pointing trajectory in which the optical tube is in fixed aiming, or - a pointing trajectory with average speed weighted between the apparent speeds of the stars and the expected moving objects.

11. A method according to any one of the preceding claims, characterized in that it further comprises fixing the camera integration time for each frame so that during the acquisition time, the movement of a spatial object covers less than 10 pixels of one frame of the (12, 12') stack of frames, and preferably less than one pixel.

12. A method according to any one of the preceding claims, further comprising precise timing, on the order of milliseconds, of a frame of the stack (12, 12') of frames, preferably at a central instant of the stack.

13. A method according to any one of the preceding claims, characterized in that it further comprises a preliminary step of determining the terrestrial coordinates of the surveillance system (100).

14. A method according to any one of the preceding claims, characterized in that it further comprises a preliminary or regular calibration step of the monitoring system (100) by observation of at least one reference satellite.

15. A system (100) for monitoring moving space objects, comprising: - at least one optical tube or lens, configured to be pointed along a known trajectory on the celestial sphere, - at least one camera, configured for the sliding or fixed acquisition of a stack of frames of space according to a field of view produced by the tube or optical lens, the frame stack comprising at least three frames, each frame being recorded with an exposure time of less than 1 second, - a calculation unit (11, 13), - a control unit (19), the system (100) being configured to implement a method for monitoring moving space objects according to any one of the preceding claims.

Images