A device for determining an attitude of a satellite is disclosed, the satellite having an attitude control system comprising a gyroscopic actuator including a flywheel mounted so as to be rotatable around an axis of rotation and carried by a gimbal articulated to rotate around an axis of rotation. The device includes an attitude sensor configured to measure the attitude of the satellite, a position sensor configured to measure the angular position of the gimbal around its axis of rotation, a speed sensor configured to measure the rotational speed of the flywheel, and a processing circuit configured to determine the attitude of the satellite by using the measurement of the angular position of the gimbal, the measurement of the rotational speed of the flywheel, and the measurement of the attitude of the satellite.

A satellite attitude estimation system 20 includes a determination unit 21 which determines the maximum pixel, which is a pixel with the largest luminance, and the minimum pixel, which is a pixel with the smallest luminance, respectively, in an infrared image, which is an image taken by an infrared sensor of a target satellite that is a satellite whose attitude is to be estimated, an association unit 22 which associates the determined maximum and minimum pixels with coordinates on the 3D structure of the target satellite, respectively, a computation unit 23 which computes normal vectors for a surface including the coordinates associated with the pixel, respectively, over the coordinates associated with each pixel, and a sun direction estimation unit 24 which estimates the direction of the sun relative to the target satellite before the infrared image is taken using the computed normal vectors.

A satellite attitude estimation system 20 includes a determination unit 21 which determines the maximum pixel, which is a pixel with the largest luminance, and the minimum pixel, which is a pixel with the smallest luminance, respectively, in an infrared image, which is an image taken by an infrared sensor of a target satellite that is a satellite whose attitude is to be estimated, an association unit 22 which associates the determined maximum and minimum pixels with coordinates on the 3D structure of the target satellite, respectively, a computation unit 23 which computes normal vectors for a surface including the coordinates associated with the pixel, respectively, over the coordinates associated with each pixel, and a sun direction estimation unit 24 which estimates the direction of the sun relative to the target satellite before the infrared image is taken using the computed normal vectors.

Disclosed in the present disclosure is a representation learning-based star identification method, which utilizes an end-to-end and representation learning based neural network model RPNet, for fast, efficient, and robust full-sky star identification tasks. The RPNet learns a unique star pattern for each star from a huge amount of random simulated star image samples, then a classification is made on these star patterns learned before. The RPNet comprises two parts: (1) a star pattern generator (SPG) based on a star pattern generation network to generate unique star patterns for the star image samples; (2) a star pattern classifier (SPC) to classify the unique star patterns generated on the front end. And a weight search verification algorithm is also proposed in the invention for filtering and verification of main stars of the GRSs identified by the RPNet, which further improves tremendously the identification ability for a single star image.

An autonomous system for geographic locating may include a camera unit capable of capturing a present time image of a night sky, a processor operable to execute instructions accessible in memory, the processor capable of implementing a machine learning positioning algorithm comprising a finite sequence of instructions, the machine learning positioning algorithm comprising a training module operable in a training mode with a training dataset to train same, the machine learning positioning algorithm including a prediction module operable in a prediction mode with a live dataset to provide a prediction of an inferred geographic location of capturing the present time image.

An autonomous system for geographic locating may include a camera unit capable of capturing a present time image of a night sky, a processor operable to execute instructions accessible in memory, the processor capable of implementing a machine learning positioning algorithm comprising a finite sequence of instructions, the machine learning positioning algorithm comprising a training module operable in a training mode with a training dataset to train same, the machine learning positioning algorithm including a prediction module operable in a prediction mode with a live dataset to provide a prediction of an inferred geographic location of capturing the present time image.

A detector for image recording, in particular for an optoelectronic image recording system for a spacecraft, includes a carrier substrate and an optoelectronic element arranged on the carrier substrate. At least in one end region, the carrier substrate has at least one side surface running obliquely to the longitudinal direction of the carrier substrate. An optoelectronic image recording system for a spacecraft includes a carrier plate and such a detector. A spacecraft includes such a detector and/or such an optoelectronic image recording system.

A system and method of tracking a hypersonic object over a flightpath includes at least one observer having at least one sensor. The sensor is configured to provide measurements of the hypersonic object that are geometrically diverse such that each observer may independently measure any combination of range, angles, Doppler, and angle rates. The observers transmit measurements to a processing unit as the hypersonic object undergoes three phases including a boost phase, a ballistic phase, and a hypersonic glide phase. The hypersonic object is tracked over many time steps by first selecting a dynamics model representative of expected object kinematics during said phase. Then, an unscented Kalman filter is used to predict a future state and a covariance using the dynamics model that was selected. Finally, the unscented Kalman filter updates the future state and covariance that were predicted based on the geometrically diverse measurements of the sensors.

A method for directly planning a reentry trajectory in a height-velocity profile includes the following steps: S1, extracting an actual working parameter of an aircraft, setting the maximum value {dot over (Q)}.sub.max of a stagnation point heat flux, the maximum value q.sub.max of dynamic pressure, and the maximum value n.sub.max of overload according to the mission requirement, and solving the height-velocity boundary of the reentry trajectory, that is, a lower boundary of the reentry trajectory in the height-velocity profile; S2, solving a reentry trajectory of an initial descent stage according to differential equations of reentry motion, and determining a starting point of a trajectory of a gliding stage according to the trajectory of the initial descent stage; and S3, planning a trajectory in the height-velocity profile satisfying terminal constraints based on the lower boundary in the height-velocity profile, and calculating a corresponding bank angle, to obtain the reentry trajectory.

An atom interferometer system includes a sensor cell comprising alkali metal atoms. An optical system generates first and second interrogation beams having respective first and second frequencies and a circular polarization. The optical system includes optics that provide the first and second interrogation beams through the sensor cell in a first direction and reflect the first and second interrogation beams back through the sensor cell in a second direction opposite the first direction and in a same circular polarization to drive the alkali metal atoms from a first energy state to a greater energy state during an interrogation stage of sequential measurement cycles. A detection system detects a state distribution of a population of the alkali metal atoms between the first energy state and the second energy state during the interrogation stage based on an optical response.