机载SAR反投影图像自聚焦处理方法

反投影算法(BPA)是一种经典的时间域合成孔径雷达(SAR)成像处理方法。BPA对回波数据插值累加得到图像,运动误差导致的目标散焦沿不同的倾斜角度存在,无法直接应用现有的自聚焦算法。为此,提出了一种新颖的BPA图像运动补偿方案。基于反投影数据运动相位误差和距离徙动分析,研究了修正投影栅格成像,从而去除重建图像中目标散焦方向的空变特性。在中低分辨率配置下,重建SAR图像能够直接应用相位梯度自聚焦(PGA)等进行运动补偿。点目标仿真实验和实测数据结果验证了该算法的有效性。     

A memetic algorithm for path planning of curvature-constrained UAVs performing surveillance of multiple ground targets

The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles （UAVs） performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs＇ minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood （DTSPN）. Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants （multi-UAV scenario and multiple groups of targets scenario）. The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.     

Novel orbit-attitude combination mode for solar power satellites to reduce mass and fuel

Solar power satellite receives great attention because it can release the energy crisis and environmental problems in the future. However, the launch and maintenance costs are tremendous due to the large system mass and large fuel consumption to counteract space perturbations. To reduce mass and fuel, a novel quasi-Sun-pointing attitude in Sun-frozen orbit is proposed. The Sun-frozen orbit has a nonzero eccentricity vector that always points towards the Sun. The quasi-Sun-pointing attitude is a periodic solution of the Sun-pointing attitude angle. Although about 3 % electricity must be given up because of the variation of Sun-pointing attitude angle, little control action is required to deal with the solar radiation pressure and gravity-gradient torque. The algorithm to obtain initial conditions is proposed. The influences of system parameters and structural flexibilities are studied. Simulation results reveal that the quasi-Sun-pointing attitude in Sun-frozen orbit dramatically reduce fuel consumption, the dry mass, and complexity of the control system. In addition, structural vibration is hardly induced by the gravity-gradient torque. Thus, the bending stiffness as well as the mass of the supporting structure can be reduced.     

Autonomous navigation for lunar final approach based on gravity gradient measurements

Lunar final approach navigation is critical for pin-point lunar landing in future missions. This study investigates the use of lunar gravity gradient measurements for autonomous navigation of a lunar probe during the final approach phase. As the spacecraft approaches the Moon, the strength of gravity gradient signals improves. A spaceborne gravity gradiometer can precisely measure local gravity gradients, and the latest lunar gravity model GL1500E is used to provide reference values. The employed truncation degree and order of the gravity model are increased stepwise considering the decreasing altitude of the spacecraft in order to reach a compromise between computational costs and model accuracy. An iterative Kalman filter is developed for coupled orbit and attitude estimation using gravity gradient measurements and attitude quaternions obtained from star sensors. A simulated spacecraft with a gradiometer noise level of 0.01 E is considered. Simulation results show that the spacecraft’s position converges rapidly and achieves an accuracy of less than 100 m at the last epoch.