An instrument (20) determines the attitude of a spacecraft (3) on which it is mounted, by interacting incident light (11) from the Sun with one or more light conditioning elements (12) and thereby forming a diffraction pattern at a photo-sensitive detector (13). The intensity distribution of light on the detector (13) is dependent on the angle of incidence of the light (11). An on-board computer (16) determines a direction vector to the Sun based on the light diffraction pattern detected by the detector (13).

A hand-held controller and a positional reference device for determining the position and orientation of the hand-held controller within a three-dimensional volume relative to the location of the positional reference device. An input/output subsystem in conjunction with processing and memory subsystems can receive a reference image data captured by a beacon sensing device combined with inertial measurement information from inertial measurement units within the hand-held controller. The position and orientation of the hand-held controller can be computed based on the linear distance between a pair of beacons on the positional reference device and the reference image data and the inertial measurement information.

A device implementing a system for estimating device location includes at least one processor configured to receive a first estimated position of the device at a first time. The at least one processor is further configured to capture, using an image sensor of the device, images during a time period defined by the first time and a second time, and determine, based on the images, a second estimated position of the device, the second estimated position being relative to the first estimated position. The at least one processor is further configured to receive a third estimated position of the device at the second time, and estimate a location of the device based on the second estimated position and the third estimated position.

The disclosed system may include a housing dimensioned to secure various components including at least one physical processor and various sensors. The system may also include a camera mounted to the housing, as well as physical memory with computer-executable instructions that, when executed by the physical processor, cause the physical processor to: acquire images of a surrounding environment using the camera mounted to the housing, identify features of the surrounding environment from the acquired images, generate a map using the features identified from the acquired images, access sensor data generated by the sensors, and determine a current pose of the system in the surrounding environment based on the features in the generated map and the accessed sensor data. Various other methods, apparatuses, and computer-readable media are also disclosed.

A device, system and method of use for the relative navigation in a fluid medium, the device having a receiver and a controller, the receiver capable of receiving signals through the fluid medium. The signals, produced by a source, are capable of undergoing Doppler shift, and the controller is capable of determining the Doppler shift of the signals and determining the bearing between the device and the source of the signals. The system further having a first vehicle capable of producing the signals and a second vehicle having the device and wherein the device determines the bearing of the second vehicle in relation to the first vehicle.

A system and a method of position and orientation determination use an image capturing device and position and orientation sensors in user equipment such as a head mounted device “HMD”. The method may comprise receiving position measurements from the position sensor and receiving a selection of one or more anchors based on said position measurements including the position of each anchor. The position and orientation measurements may be used to determine whether any selected anchor is visible to said image capturing device based on said position and orientation measurements. Then the image capturing device may be activated to capture an image including said one or more anchors when a selected anchor is visible. The image may be analyzed to determine the position and orientation of the image capturing device relative to the one or more anchors.

A distributed, cross reality system efficiently and accurately compares location information that includes image frames. Each of the frames may be represented as a numeric descriptor that enables identification of frames with similar content. The resolution of the descriptors may vary for different computing devices in the distributed system based on degree of ambiguity in image comparisons and/or computing resources for the device. A descriptor computed for a cloud-based component operating on maps of large areas that can result in ambiguous identification of multiple image frames may use high resolution descriptors. High resolution descriptors reduce computationally intensive disambiguation processing. A portable device, which is more likely to operate on smaller maps and less likely to have the computational resources to compute a high resolution descriptor, may use a lower resolution descriptor.

A distributed, cross reality system efficiently and accurately compares location information that includes image frames. Each of the frames may be represented as a numeric descriptor that enables identification of frames with similar content. The resolution of the descriptors may vary for different computing devices in the distributed system based on degree of ambiguity in image comparisons and/or computing resources for the device. A descriptor computed for a cloud-based component operating on maps of large areas that can result in ambiguous identification of multiple image frames may use high resolution descriptors. High resolution descriptors reduce computationally intensive disambiguation processing. A portable device, which is more likely to operate on smaller maps and less likely to have the computational resources to compute a high resolution descriptor, may use a lower resolution descriptor.

A system and method for high-confidence error overbounding of multiple optical pose solutions receives a set of candidate correspondences between 2D image features captured by an aircraft camera and 3D constellation features including at least one ambiguous correspondence. A candidate estimate of the optical pose of the camera is determined for each of a set of candidate correspondence maps (CMAP), each CMAP resolving the ambiguities differently. Each candidate pose estimate is evaluated for viability and any non-viable estimates eliminated. An individual error bound is determined for each viable candidate pose estimate and CMAP, and based on the set of individual error bounds a multiple-pose containment error bound is determined, bounding with high confidence the set of candidate CMAPs and multiple pose estimates where at least one is correct. The containment error bound may be evaluated for accuracy as required for flight operations performed by aircraft-based instruments and systems.

The subject matter disclosed herein is generally directed towards systems and methods for estimating vehicle attitude information using position data of stars and astronomical objects in the sky. Considerable advantages may be realized by equipping vehicles with low-cost star trackers adequate for filtering images based on statistical-based techniques, which could provide a robust and reliable attitude determination. The methods described herein provide algorithms to reduce the amount of processing capacity and memory for finding stars and astronomical objects. In some instances, the provided systems and methods allow the prediction of the next location of the stars and/or other astronomical objects to enhance the search by looking for them at the predicted location. The algorithms may be applied in real-time and are suitable for movable platforms with limited resources such as satellites and spacecraft.