An operation of a spacecraft is controlled using an inner-loop control determining first control inputs for momentum exchange devices to control an orientation of the spacecraft and an outer-loop control determining second control inputs for thrusters of the spacecraft to concurrently control a pose of the spacecraft and a momentum stored by the momentum exchange devices of the spacecraft. The outer-loop control determines the second control inputs using a model of dynamics of the spacecraft including dynamics of the inner-loop control, such that the outer-loop control accounts for effects of actuation of the momentum exchange devices according to the first control inputs determined by the inner-loop control. The thrusters and the momentum exchange devices are controlled according to at least a portion of the first and the second control inputs.

Described herein are systems and methods for attitude determination using infrared Earth horizon sensors (EHSs) with Gaussian response characteristics. Attitude information is acquired by detecting Earth's infrared electromagnetic radiation and, subsequently, determining the region obscured by Earth in the sensors' fields of view to compute a nadir vector estimation in the spacecraft's body frame. The method can be applied when two sensors, each with known and distinct pointing directions, detect the horizon, which is defined as having their fields of view partially obscured by Earth. The method can be implemented compactly to provide high-accuracy attitude within small spacecraft, such as CubeSat-based satellites.

A control system includes a target spacecraft and a swarm of chaser spacecraft. Each chaser spacecraft is controlled to follow a corresponding computed trajectory. The system also includes at least one computing device that executes a nested genetic algorithm. The nested genetic algorithm includes multiple guidance genetic algorithms and an outer genetic algorithm. Characteristically, each chaser spacecraft has an associated guidance genetic algorithm that determines a computed trajectory for the chaser spacecraft associated therewith. Advantageously, the outer genetic algorithm checks for collisions and is configured to alter one or more computed trajectories to avoid collisions.

Disclosed are an attitude estimation method, a terminal, a system and a computer-readable storage medium. For the problem of attitude and sensor bias estimation, a cascade solution method is provided. The first part of the cascade is a Kalman filter applied to an LTV system, and the second part of the cascade is a nonlinear attitude observer built in SO(3). In the estimation process, only one constant inertial reference vector needs to be measured explicitly in body-fixed coordinates, and the complexity of the attitude estimation algorithm is greatly simplified by exploiting the geometric relationship between the inertial reference vector and the Earth angular velocity vector. At the same time, the time-varying characteristics of the implemented Kalman filter help to avoid the tedious empirical gain adjustment process that often relies on sets of piecewise constant gains, to improve the convergence speed of the algorithm.

A control system configured to execute a safing mode sequence for a spacecraft is disclosed. The control system includes one or more star trackers that each include a field of view to capture light from a plurality of space objects surrounding the celestial body. The control system also includes one or more actuators, one or more processors in electronic communication with the one or more actuators, and a memory coupled to the one or more processors. The memory stores data into a database and program code that, when executed by the one or more processors, causes the control system to determine a current attitude of the spacecraft, and re-orient the spacecraft from a current attitude into a momentum neutral attitude.

A process to design an attitude control system (ACS) controller in each of a plurality of joined entities includes identifying a worst case configuration as a design-to configuration as one or more configurations in a given set S of configurations required for a spacecraft. For the design-to configuration, the process includes deriving one or more system equations in a functional form of equations to determine intermediate design parameters that represent effective proportional and derivative gains of the combined controller, Kp and Kd, respectively. The process also includes determining the design parameters of the ACS controller, namely, gains Kq and Kω and stiffness and damping coefficients, Ks and Cd respectively of all the interfaces between each of the plurality of joined entities, from the intermediate design parameters Kp and Kd. The process further includes programming the ACS controller with selected values of the design parameters for matrices Kq and Kω and selecting springs with stiffness Ks and dampers with damping coefficient Cd for all interfaces between each of the plurality of joined entities. The process includes iterating the computer-implemented process after incrementing a convergence requirement parameter σthreshold when the control performance is not acceptable and until the system achieves acceptable performance, and programming the ACS controller for each of the plurality of joined entities.

An attitude control system includes one or more control moment gyro pairs, with gyros of individual of the pairs being counter-rotated to rotate the rotation axes of flywheels of the gyros of a gyro pair in opposite direction. The flywheels of a gyro pair may be in paddle configuration, with the rotation axes of the flywheels rotating in the counter-rotation through separate planes as the gyros are rotated. The rotation of the gyros of a gyro pair may be accomplished by coupling both of the gyros to a servo motor with suitable coupling gears, or by using independent servos for each gyro. The counter-rotation of gyros of an individual pair produces a resultant torque about a fixed global axis, such as the axis of a flight vehicle of which the attitude control system is a part. Further control may be accomplished for example by varying rotation speeds of the flywheels.

When calculating a gimbal angle trajectory that satisfies boundary conditions set by an attitude boundary condition setter 2131 of the ground station 21, a gimbal angle trajectory calculator 2132 calculates the gimbal angle trajectory that minimizes a period of an acceleration interval within a range that satisfies driving restrictions of a gimbal, based on a gimbal angle θ.sub.0i of a start time and a gimbal angle θ.sub.ci of a fixed interval of an attitude change. Also, the gimbal angle trajectory is calculated that minimizes a period of a deceleration interval within a range that satisfies the driving restrictions of the gimbal, based on the gimbal angle θ.sub.ci of the fixed interval and a gimbal angle θ.sub.fi of a completion time of the attitude change. The obtained θ.sub.0i, θ.sub.ci, θ.sub.fi and an attitude change period τ are transmitted to the artificial satellite as gimbal angle trajectory parameters, and the control moment gyros are controlled based on the gimbal angle trajectory parameters.

An attitude control apparatus (20) includes an ideal thrust direction calculator (22), an ideal attitude calculator (24), a target attitude calculator (26), and a torque calculator (28). The ideal thrust direction calculator (22) calculates an ideal thrust direction of a thruster. The target attitude calculator (26) calculates a target attitude that is the attitude of a satellite in which a deviation from an ideal attitude is minimized within a movement limitation of an attitude control actuator (14) while a panel surface faces the sun. The torque calculator (28) calculates a torque for turning the satellite from an actual attitude to the target attitude and transmits a torque instruction to the attitude control actuator (14).

Aspects presented herein may enable a positioning device or entity to perform PR measurement error detection and classification based on SV geometry via ML. In one aspect, a UE or a location server determines for each SV of a set of SVs at least a geometric orientation with respect to the UE. The UE or the location server determines, based on an ML classifier and the determined geometric orientation with respect to the UE for each SV of at least a subset of the set of SVs, a relative PR weight for each SV of the set of SVs. The UE or the location server estimates a position of the UE based on PR measurements of each SV of the set of SVs and the relative PR weight for each SV of the set of SVs.