Purpose: The purpose of this paper is to present a method to achieve small satellite formation keeping operations by using the differential lift and drag to control the drift caused by J2 perturbation in circular or near-circular low earth orbits (LEOs). Design/methodology/approach: Each spacecraft is equipped with five large flat plates, which can be controlled to generate differential accelerations. The aerodynamic lift and drag acting on a flat plate is calculated by the kinetic theory. To maintain the formation within tracking error bounds in the presence of J2 perturbation, a nonlinear Lyapunov-based feedback control law is designed. Findings: Simulation results demonstrate that the proposed method is efficient for the satellite formation keeping and better accuracy advantage in comparison with classical approaches via the fixed maximum differential aerodynamic acceleration. Research limitations/implications: Because the aerodynamic force will reduce drastically as the orbital altitude increases, the formation keeping control strategy for small satellites presented in this paper should be limited to the scenarios when satellites are in LEO. Practical implications: The formation keeping control method in this paper can be applied to solve satellite formation keeping problem for small satellites in LEO. Originality/value: This paper proposes a Lyapunov control strategy for satellite formation keeping considering both lift and drag forces, and simulation results show better performance with high accuracy under J2 perturbation.

In this study, we present a novel system for crowd surveillance and quantified analysis based on laser range scanners. By mounting a laser scanner at a swinging platform, the spatial information of passengers inside the area of interest can be reconstructed in a form of 3D points. Multiple laser scanners are integrated together by semi-auto calibration procedures. Background map is generated through histogram analysis of scan maps, and is further applied for 3D moving object detection. An improved version of mean-shift clustering algorithm is proposed to extract individual passengers efficiently. In addition, quantified crowdness analysis is conducted from different aspects to indicate the situation inside the surveillance area according to the extraction results of passengers. The proposed system was tested in a central subway station in Tokyo and experimental results demonstrate the effectiveness of our proposed system.

NSGA-II-Based Multi-objective Mission Planning Method for Satellite Formation System

For continuous-discrete filtering with unpredictable approximation errors, by proposing the novel stochastic feedback scheme, this note elaborates a closed-loop adaptive Kalman filter for nonlinear continuous-discrete systems. In conventional filters, unknown approximation errors might arise due to the integration/discretization and linearization of continuous model, and ruin the optimality of Kalman theory. As the main contribution of this note, the stochastic feedback based covariance adaption scheme does not require the approximation steps; instead, the posteriori sequence is mined as a feedback to adapt the priori error covariance, so that the unpredictable errors and costly calculations can be reduced or controlled in the novel closed-loop filtering structure. The new approach's advantages in computational cost, adaptability, and accuracy have been demonstrated by the numerical simulations.