There is a severe lag between the pitch attitude and flight path angle of hypersonic vehicles, imposing extraordinary difficulty in achieving high-precision trajectory control. A comprehensive flight path regulation scheme is proposed to resolve this problem. The inherent relationship between the pitch attitude and flight path angle is sufficiently used to establish a feed-forward control framework where the flight path reference is directly fed into the attitude loop in order to quickly obtain the major control component. To achieve efficient tracking, an attitude control method based on active disturbance rejection control (ADRC) is proposed. The new attitude control method utilizes an extended state observer (ESO) to estimate the unknown model dynamics and external disturbances. The remaining part of control is generated by ADRC acting on the flight path angle, which plays a complementary role. The stability margin tester is used to tune the attitude controller explicitly. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed method.

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This paper suggests a methodology for the selection of an inertial sensor for cycle slip detection. The satellite-difference and time-difference residual between the predicted and measured carrier phases is defined as the monitoring value for cycle slip detection. The inertial navigation system (INS) position is used to calculate the predicted observation, and its error mainly contributes to the residual. For one cycle slip detection, the monitoring value residual should be smaller than the threshold. Based on this approach, we derive the maximum permissible position estimation error of the INS to detect one cycle slip. An Earth-centered, Earth-fixed (ECEF) frame-based INS is used for the derivations. Then, we formulate the position estimation error as a function of the inertial sensor specifications using suitable assumptions. Using resulting equation, the optimal inertial sensor can be selected based on the required cycle slip detection performance. To verify the process of optimal IMU selection, simulation data is used. The derived position estimation error of the INS is analyzed carefully, and the monitoring value elicited by the INS error is also investigated. As a result, the selected IMU satisfies the designed cycle slip detection performance within the microelectromechanical systems (MEMS) grade.

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Orbital debris poses a constant threat to satellites. Some larger debris can be tracked and avoided, but smaller objects cannot be tracked. In addition, there exists a data gap in orbital debris dispersion models for particles less than 5 mm in diameter. The Debris Resistive/Acoustic Grid Orbital Navy Sensor (DRAGONS) fills this critical gap in debris monitoring capability. DRAGONS is a sensor system developed by the U.S. Naval Academy and NASA. Consisting of multiple sensor layers, the sensor is capable of providing size, velocity, angle of incidence, and density information of the impacting micrometeoroid and orbital debris. DRAGONS will provide real-time monitoring of orbital debris of small sizes, and will be deployed on the outside of the International Space Station in 2016 for in-situ characterization of debris flux, resulting in improved risk assessment and situation awareness. DRAGONS has been developed and tested for functionality. However, some concerns were raised in regards to its sensitivity to the possible damage that may occur due to environmental loading. The paper provides an overview of the design of the sensor grid, and discusses test results for thermal and vibration loading, as well as potential secondary damage from the force of particle impact.

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This paper investigates how a priori localization information on a stationary ground target affects the optimal trajectories of cooperative unmanned aerial vehicles (UAVs) for estimating the target location. Each UAV is assumed to be equipped with a bearing-only sensor which always directs to the target. In order to formally incorporate the effect of a priori information into the estimation process, a Bayesian framework is employed: The optimal flying directions and paths of the multiple UAVs are determined by minimizing the Bayesian Cramér-Rao Lower Bound (BCRLB) with prior information on the ground target location represented via a bivariate Gaussian Probability Density Function (PDF). The effect of the prior information is examined with varying parameters that handle the size and shape of the prior PDF. It turns out that the more elliptical the prior PDF support, the more orthogonal the flying directions to the major principal axis of the ellipse in order to reduce the information imbalance in the direction of the major principal axis. In order to reduce the computational load for the calculation of the BCRLB, we employ the Bayesian Monte-Carlo integration method, which is shown to be fast enough to compute the BCRLB online in small UAVs.

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For a better original state and scientific value of lunar soil samples, research on the impact of drill bits on the perturbation rate based on DEM was carried out. A simulated model of lunar soil was established based on the linear adhesion contact model. The parameters of the model were determined by matching between the mechanics and discrete elements. The evaluation criteria of the original states of the lunar soil samples were built on the basis of actual project needs. Based on this, some simulations for the drilling and sampling of lunar soil with different drill bits were carried out. The impact of drill bit parameters, such as internal diameter, cutting angle and height of bottom-out blade on the perturbation rate, was studied. It is shown by the results that the perturbation rate decreases with both the internal diameter and the height of the bottom-out blade, and there is a minimum value with cutting angle. For the best perturbation rate of lunar soil samples under the constraint conditions of the project, the internal diameter should be 18 mm, cutting angle should be 90°, and height of bottom-out blade should be 5 mm.

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On February 15th, 2013, a meteor with size of about 20 m in diameter entered the Earth's atmosphere over Chelyabinsk, Russia, and exploded at an altitude of about 20 km, damaging about 4,500 buildings and injuring about 1,500 residents. This incident widely invoked an interest in hazard mitigation caused by a NEO. Motivated by such interests, this study focuses on a new concept of NEO detection and impact warning system. In this concept, a space telescope is placed at the L1 point of the Sun-Earth system to intensively observe the NEOs in-coming from the noon-side, which ground-based observatories hardly detect because of the sunlight. Throughout some cases of simulations, this paper reveals the distributions of NEO directions at detection, V-infinity vectors at the Earth impact, and the NEO orbit determination precision are evaluated.

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A highly precise connection method for two sets of three-dimensional surface shape data measured by the grating projection method is proposed with the aim of capturing the full-field surface shape of a large space structures with high accuracy and spatial resolution. The coordinate transformation matrix that serves as an interface between the two sets of surface shape data is precisely calculated by feature-point matching of the virtual targets using the singular value decomposition algorithm, and the two sets of the surface shape data are connected by the coordinate transformation. In the verification experiment, the virtual targets are created from preliminary surface shape measurement of dedicated concave models using the grating projection method. The results show that the two sets of surface shape data can be connected with 40.2 × 10⁻⁶ mRMS accuracy. This connection accuracy is roughly the same as that achieved with photogrammetry using the grating projection method, thus confirming the effectiveness of the connection method proposed.

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