Systems and methods of the present disclosure enable machine learning-based refinement of trajectory predictions using a processor to determine a future trajectory associated with an object state using an iterative physics algorithm. The processor utilizes a trajectory error prediction machine learning model to predict a trajectory error for the future trajectory determined for the object state. The processor determines a pseudo-measurement representative of the trajectory error based at least in part on the trajectory error for the future trajectory and determines a pseudo-measurement noise based at least in part on the pseudo-measurement. The processor determines an updated future trajectory for the future trajectory based on the pseudo-measurement and the pseudo-measurement noise of the trajectory error for the future trajectory, and causes to display a trajectory notification associated with future trajectory on a screen of a user computing device associated with a user.

Systems and methods of the present disclosure enable machine learning-based refinement of trajectory predictions using a processor to determine a future trajectory associated with an object state using an iterative physics algorithm. The processor utilizes a trajectory error prediction machine learning model to predict a trajectory error for the future trajectory determined for the object state. The processor determines a pseudo-measurement representative of the trajectory error based at least in part on the trajectory error for the future trajectory and determines a pseudo-measurement noise based at least in part on the pseudo-measurement. The processor determines an updated future trajectory for the future trajectory based on the pseudo-measurement and the pseudo-measurement noise of the trajectory error for the future trajectory, and causes to display a trajectory notification associated with future trajectory on a screen of a user computing device associated with a user.

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 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.

The present disclosure provides a jump detection system for inertial measurement unit (IMU) integrated with a barometric altimeter in the same device (IMU-baro). The processor is configured to record time-series data of both a vertical component of the measured IMU-baro acceleration and the estimated vertical velocity of the IMU-baro, detect a potential jump by comparing the vertical component of the measured IMU-baro acceleration to one or more acceleration thresholds, and, validate the potential jump by comparing a difference between a maximum velocity and a minimum velocity within a vicinity of the potential jump in the time-series data of the estimated vertical velocity of the IMU-baro to a velocity threshold.

Improved methods and systems for position acquisition and/or monitoring are disclosed. The position acquisition and/or monitoring can be performed with improved intelligence so that data acquisition, transmission and/or processing is reduced. As a result, the position acquisition and/or monitoring is able to be performed in a power efficient manner.

The present invention provides a method for imparting unique identifiers that do not overlap each other to individual position spaces in the case of latitude and longitude information or even in the case of height information also included in addition thereto. A longitude line passing through the coordinate origin is divided by the length of one side of a unit grid, and a latitude value inside unit grids is calculated. An accumulated error is calculated in a case where latitude values inside the unit grids are accumulated for one round in a longitude line direction of a celestial body, and an error per unit grid is calculated based on the calculated accumulated error. The number of unit grids included in one block in the longitude line direction is specified so that a reference error per block is equal to or smaller than one thousandth of the accumulated error, and thus a reference latitude is set. A reference longitude is set by the same calculation process for each latitude line that is determined based on the set reference latitude, reference points are specified sequentially from the coordinate origin based on the set reference latitude and reference longitude, and a unique identifier is imparted to each unit grid located in a block with the reference points set as its vertices.

The present invention provides a method for imparting unique identifiers that do not overlap each other to individual position spaces in the case of latitude and longitude information or even in the case of height information also included in addition thereto. A longitude line passing through the coordinate origin is divided by the length of one side of a unit grid, and a latitude value inside unit grids is calculated. An accumulated error is calculated in a case where latitude values inside the unit grids are accumulated for one round in a longitude line direction of a celestial body, and an error per unit grid is calculated based on the calculated accumulated error. The number of unit grids included in one block in the longitude line direction is specified so that a reference error per block is equal to or smaller than one thousandth of the accumulated error, and thus a reference latitude is set. A reference longitude is set by the same calculation process for each latitude line that is determined based on the set reference latitude, reference points are specified sequentially from the coordinate origin based on the set reference latitude and reference longitude, and a unique identifier is imparted to each unit grid located in a block with the reference points set as its vertices.

Provided is a distance measuring device and a method of measuring a distance. The distance measuring device detects light reflected by an object, generates an electrical signal based on the detected light, detects whether the electrical signal is saturated or not by comparing the electrical signal with a reference value, controls a magnitude of the electrical signal based on whether the signal is saturated, and calculates a distance to the object using the electrical signal.

A method of determining a precise orbit of a satellite through estimation of a parallactic refraction scale factor is proposed, the method including inputting an initial estimate including initial orbit information of a satellite with respect to an observation epoch and the parallactic refraction scale factor; performing orbit propagation using a high-precision orbit propagator by applying a dynamics model; performing observer-centered satellite optical observation modeling including the parallactic refraction scale factor; calculating an observation residual between actual optical observation data and observation data calculated via the observation modeling reflecting the parallactic refraction; and precisely determining the orbit of the satellite by estimating the parallactic refraction scale factor and a satellite state vector using a batch least square estimation algorithm.