The invention concerns a method for estimating the angular velocity (and, preferably, also the attitude) of a space platform (for example, a satellite, a space vehicle, or a space station) using only the information provided by one or more optical sensors, such as one or more star trackers, one or more colour and/or black and white cameras or video cameras, one of more infrared sensors, etc.

A wide field-of-view celestial sighting system and method are provided. The method includes orienting an imaging optic to collect light from at least one light source, such as at least one celestial body, the imaging optic being secured to a platform. The method further includes selectively collecting light from the at least one celestial body through a selective light collector secured to the platform and positioned in an imaging surface, such as an imaging plane, of the imaging optic. The method further includes combining forward scattered light from the at least one celestial body to provide a combined forward scattered light, and detecting a light intensity of the combined forward scattered light. Systems for performing the method are provided.

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.

Multiple telescopes of a telescope array are rigidly aligned at predetermined relative orientations to simultaneously image corresponding predesignated celestial objects. Detection of light from the celestial objects collected by the telescopes enables calculation or estimation of orientation of the telescope array with respect to the celestial sphere. That orientation, in combination with a planetary nadir direction, enables estimation or calculation of position of the telescope array relative to a planetary surface. The nadir can be measured by dropping a probe particle through an evacuated chamber onto or through a two-dimensional sensor.

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 compact celestial tracker includes a platform, a rotation stage that rotatably coupled to the platform to rotate a plane of the platform about a rotation axis and that supports the platform on a substrate, an off-axis parabolic mirror mounted to one side of the platform and having a focal plane directed at an acute angle that is between the rotation axis and the plane of the platform to reflect and focus the beam at a point above another side of the platform, and a detector coupled to the other side of the platform to receive and detect the reflected and focused beam.

Provided are an earth satellite attitude data fusion system and method, applicable to an earth satellite space environment to estimate attitude data of a satellite. When the earth satellite attitude data fusion system of the present invention is used to perform the earth satellite attitude data fusion method, the first step is to perform a body rates/quaternion attitude data processing operation. Then, the next step is to perform an attitude/rates data fusion processing operation, wherein an attitude data fusion algorithm module receives a first IAE result data from a first EKF, and a second IAE result data from a second EKF, and performs an attitude/rates data fusion algorithm in a subsystem level to evaluate an attitude estimation IAE performance based on the first IAE result data, and the second IAE result data.

A navigation system includes a monocentric lens and one or more curved image sensor arrays disposed parallel and spaced apart from the lens to capture respective portions, not all, of the field of view of the lens.

A navigation system includes a monocentric lens and one or more curved image sensor arrays disposed parallel and spaced apart from the lens to capture respective portions, not all, of the field of view of the lens.

One example includes a magnetic-inertial global positioning system mounted on a platform. The system includes an inertial system configured to determine an approximate latitude associated with an approximate global position of the global positioning system. The system also includes a magnetometer system configured to determine an ambient magnetic field at the approximate global position. The system further includes a location processor configured to compare the ambient magnetic field with a predetermined magnetic field profile to determine an approximate longitude along the determined approximate latitude to determine the approximate global position of the platform.