A method for detecting and modeling objects in space using LIDAR is disclosed. The method includes transmitting a laser beam to detect at least one object in space. Further, the method includes detecting one or more data related to at least one object. The detection is based upon the principle of reflection of the object in a vacuum. Further, said one or more data related to at least one object obtained from the detection unit is processed. Further, one or more information is determined from the processed data related to at least one object. The one or more information is mapped corresponding to the related at least one object. The method further comprises measuring one or more parameters associated with at least one of the mapped objects and modeling the measurement data related to at least one of the mapped objects.

A method for detecting and modeling objects in space using LIDAR is disclosed. The method includes transmitting a laser beam to detect at least one object in space. Further, the method includes detecting one or more data related to at least one object. The detection is based upon the principle of reflection of the object in a vacuum. Further, said one or more data related to at least one object obtained from the detection unit is processed. Further, one or more information is determined from the processed data related to at least one object. The one or more information is mapped corresponding to the related at least one object. The method further comprises measuring one or more parameters associated with at least one of the mapped objects and modeling the measurement data related to at least one of the mapped objects.

A satellite system includes a satellite in an orbit that is configured to reduce a number of exclusion regions and improve the observation coverage of resident space objects (RSOs) positioned in near Earth orbits. The satellite system includes at least one satellite positioned in a sun synchronous orbit (SSO) with a noon/midnight nodal crossing. The altitude of the SSO is between 1000 and 2000 kilometers and the satellite includes at least one sensor arranged on the satellite that is configured for detection, tracking, and/or identification. Using the noon/midnight nodal crossing is advantageous in that three main exclusion regions, the sun, eclipse, and Earth exclusion regions, are combined into only two exclusion regions for improved performance of the satellite system in observing RSOs.

A method for initializing a tracking algorithm for target objects, includes generating a 3D point cloud of the target object and iteratively determining a spatial position and orientation of the target object using a 3D model. A spatial position and orientation of the target object is first determined using an artificial neural network, thereafter the tracking algorithm is initialized with a result of this determination. A method for training an artificial neural network for initializing a tracking algorithm for target objects includes generating a 3D point cloud of the target object by a scanning method, and iteratively determining a spatial position and orientation of the using a 3D model of the target object. The artificial neural network is trained using training data to initially determine a spatial position and orientation of the target object and thereafter initialize the tracking algorithm with a result of this initial determination.

A method for initializing a tracking algorithm for target objects, includes generating a 3D point cloud of the target object and iteratively determining a spatial position and orientation of the target object using a 3D model. A spatial position and orientation of the target object is first determined using an artificial neural network, thereafter the tracking algorithm is initialized with a result of this determination. A method for training an artificial neural network for initializing a tracking algorithm for target objects includes generating a 3D point cloud of the target object by a scanning method, and iteratively determining a spatial position and orientation of the using a 3D model of the target object. The artificial neural network is trained using training data to initially determine a spatial position and orientation of the target object and thereafter initialize the tracking algorithm with a result of this initial determination.

A method for accurately and efficiently calculating a dense ephemeris of a high-eccentricity orbit is provided. With respect to the ephemeris calculation of the high-eccentricity orbit, the method constructs uneven interpolation nodes through time transformation and interpolates by an interpolation polynomial based on uneven interpolation nodes to obtain a dense ephemeris, which significantly improves the calculation efficiency and accuracy. Based on a large-scale numerical experiment, the method derives an optimal universal value (that is, 0.3) of a transformation parameter for all orbital eccentricities and various interpolation polynomials. In the case of using the optimal universal value of the transformation parameter δ, the method further verifies the Hermite interpolation polynomial as the preferable one among various interpolation polynomials.

A method for accurately and efficiently calculating a dense ephemeris of a high-eccentricity orbit is provided. With respect to the ephemeris calculation of the high-eccentricity orbit, the method constructs uneven interpolation nodes through time transformation and interpolates by an interpolation polynomial based on uneven interpolation nodes to obtain a dense ephemeris, which significantly improves the calculation efficiency and accuracy. Based on a large-scale numerical experiment, the method derives an optimal universal value (that is, 0.3) of a transformation parameter for all orbital eccentricities and various interpolation polynomials. In the case of using the optimal universal value of the transformation parameter δ, the method further verifies the Hermite interpolation polynomial as the preferable one among various interpolation polynomials.

A spacecraft for changing an orbit or an attitude of a target in outer space by irradiating the target with a laser, the spacecraft includes: a laser apparatus configured to generate the laser; a focusing unit configured to converge the laser; a detecting unit configured to acquire detection information including a distance between the spacecraft and the target; and an irradiation control unit configured to control the focusing unit on the basis of the distance so that the laser converges on the target.

A tracking system for a target flight vehicle includes at least two sensor nodes that are positioned at geographically diverse locations relative to a launch site from which the target flight vehicle is launched. The sensor nodes have a lens and a visible camera that captures images of an anticipated launch trajectory for the target flight vehicle. The sensor nodes determine position data for the target flight vehicle including timing, azimuth, and elevation based on the captured images. A fusion processing engine is communicatively coupled to the at least two sensor nodes for receiving and integrating the position data. The data is integrated to determine real-time state vectors including a velocity and a three-dimensional position for the target flight vehicle. The state vectors are sent to a range network that is configured to implement a flight termination system for the target flight vehicle based on the state vectors.

Small, low-cost satellite systems, like CubeSats or other microsatellites, can exhibit reduced reliability relative to higher-cost satellite systems. This can result in difficulty identifying, communicating with, and tracking such satellite systems when they fail. Provided herein are reliable, low-cost, low-energy, turn-key systems for identification and tracking of small satellites that can be readily added to a microsatellite with minimal integration costs and while occupying a minimal amount of volume, mass, and external area of the host satellite. These systems are electrically isolated from the satellite bus, being powered by internal batteries or other separate energy sources and providing reliable identification and tracking even when the other systems of the satellite have failed. These improved identification and tracking systems include space environment sensors to maintain the system in a very-low-power state while the system is in vehicle processing and transit on Earth, extending device lifetime and reducing cost and weight.