A jamming satellite avoidance method changes an orbital altitude for each of orbital planes with different normal vectors in a mega-constellation satellite group composed of 100 or more satellites, so as to avoid a jamming satellite controlled by a ground device that is different from a device that controls the mega-constellation satellite group. The jamming satellite is an artificial satellite that includes a propulsion device and adopts a nominal orbital altitude and a nominal orbital inclination at which the mega-constellation satellite group flies, and maintains an average orbital altitude and an average orbital inclination while operating the propulsion device irregularly, and is controlled by the ground device that is different from the device that controls the mega-constellation satellite group.

A disclosed spacecraft is provided with: an attitude control actuator configured to control an attitude of the spacecraft; an imaging device configured to receive an optical communication signal from another spacecraft; and an attitude controller configured to control the attitude control actuator, based on a position of the optical communication signal in an image obtained by the imaging device.

To achieve an objective to enable a plurality of management business operators managing space objects flying in space, to share and carry out danger analysis efficiently. In a space traffic management system (500), a plurality of space traffic management devices (100) are connected to each other via a communication line. Each of the plurality of space traffic management devices includes a space information recorder (101), a danger alarm device (102), a danger analysis device (103), a danger avoidance action assist device (104), and a security device (105). The space information recorder includes a space object ID, orbital information, and public condition information; and a business device ID and public condition information. The plurality of space traffic management devices (100) have data format compatibility and share the space object ID and the business device ID, and share orbital information corresponding to the space object ID among business devices that comply with the public condition information.

To achieve an objective to enable a plurality of management business operators managing space objects flying in space, to share and carry out danger analysis efficiently. In a space traffic management system (500), a plurality of space traffic management devices (100) are connected to each other via a communication line. Each of the plurality of space traffic management devices includes a space information recorder (101), a danger alarm device (102), a danger analysis device (103), a danger avoidance action assist device (104), and a security device (105). The space information recorder includes a space object ID, orbital information, and public condition information; and a business device ID and public condition information. The plurality of space traffic management devices (100) have data format compatibility and share the space object ID and the business device ID, and share orbital information corresponding to the space object ID among business devices that comply with the public condition information.

Orbital debt is removal (ODR) systems under the present approach may use a ground- or surface-based FEL and mirror system with sufficient power and both spatial and temporal resolution to both locate Category II OD (1 cm to 10 cm diameter) in low Earth orbit (LEO, 160 to 2000 km altitude) and remove these objects from orbit. Locating the Category II OD is performed by having, the light beam from an FEL and its beam director scan a volume of space of interest and then observing the light reflected from the OD. Removing the OD may include heating the OD to a sufficiently high temperature to evaporate the OD, changing the orbit of the OD such as to lower the perigee, or both. Megawatt-class MOPA FELs for, inter alia, removing OD, are described.

Systems that enable observing celestial bodies during daylight or in under cloudy conditions.

Systems that enable observing celestial bodies during daylight or in under cloudy conditions.

In a distance control method of relative motion between satellites, by reducing the distance between a companion satellite and a reference satellite through the first position relation, and increasing the distance between a companion satellite and a reference satellite according to the second position relation, the distance between satellites can be kept between the set maximum distance and the minimum distance. In this way, on the one hand, the inter-satellite distance cannot be too large to ensure that the two satellites are within the maximum distance range required by communication or other cooperative relations. At the same time, the inter-satellite distance cannot be too small, and further avoid the collision between the two satellites. The method is capable of tolerating the effect of satellite orbit perturbation, allowing the inter-satellite distance to vary naturally between maximum and minimum distances, and thus saving control fuel consumption.

In a distance control method of relative motion between satellites, by reducing the distance between a companion satellite and a reference satellite through the first position relation, and increasing the distance between a companion satellite and a reference satellite according to the second position relation, the distance between satellites can be kept between the set maximum distance and the minimum distance. In this way, on the one hand, the inter-satellite distance cannot be too large to ensure that the two satellites are within the maximum distance range required by communication or other cooperative relations. At the same time, the inter-satellite distance cannot be too small, and further avoid the collision between the two satellites. The method is capable of tolerating the effect of satellite orbit perturbation, allowing the inter-satellite distance to vary naturally between maximum and minimum distances, and thus saving control fuel consumption.

A method for preprocessing data for device operations can include preprocessing measurement data using a machine learning technique, determining, by a Kalman filter and based on (1) the preprocessed measurement data or the measurement data and (2) prediction data from a prediction model predicting a measurement associated with the measurement data, corrected measurement data, and providing the corrected measurement data based on the predicted measurement and the preprocessed measurement data.