航空学报 > 2010, Vol. 31 Issue (9): 1841-1848

有限姿控能力的低RCS微小卫星姿态实时规划

苏抗, 周建江   

  1. 南京航空航天大学 信息科学与技术学院
  • 收稿日期:2009-09-28 修回日期:2010-03-12 出版日期:2010-09-25 发布日期:2010-09-25
  • 通讯作者: 周建江

Real-time Attitude Planning for Low RCS Micro-satellites with Limited Attitude Control Ability

Su Kang, Zhou Jianjiang   

  1. College of Information Science and Technology, Nanjing University of Aeronautics and Astronautics
  • Received:2009-09-28 Revised:2010-03-12 Online:2010-09-25 Published:2010-09-25
  • Contact: Zhou Jianjiang

摘要: 为提高在轨微小卫星使用效能及生存能力,提出一种受姿控能源消耗及驱动能力约束的低雷达散射截面(RCS)微小卫星姿态实时规划算法。算法应用曲面像素法、时域有限差分法及假设检验,在三维空间内对微小卫星的RCS及雷达探测水平进行建模,并结合雷达分布模型构建了相应的威胁评估函数及规划代价评估函数。同时,为提高算法的实时性能,采用了粒子群优化(PSO)算法以降低计算复杂度。仿真结果表明,在有限计算量的基础上,算法能够以较小规划代价有效降低卫星威胁方向的RCS及雷达探测概率,满足对微小卫星飞行姿态实时规划的需要。

关键词: 姿态规划, 微小卫星, 雷达散射截面, 粒子群优化, 计算复杂度

Abstract: A real-time satellite attitude planning algorithm (RSAPA) is developed for low radar cross section (RCS) micro-satellites with limited attitude control energy and abilities to enhance their on-orbit operational effectiveness and survivability. Based on the curved surface pixel method (CSPM), finite difference time domain (FDTD) and hypothesis testing, novel micro-satellite RCS and radar detection probability mathematical models are established in a three-dimensional (3D) space, and the relative radar threat evaluation function and planning cost evaluation function are defined according to a novel radar distribution model. Particle swarm optimization (PSO) algorithm is applied to the planning to decrease the algorithm computational complexity and improve its real-time performance. In the simulation, within limited computational complexity and planning cost, the algorithm reduces effectively the micro-satellite’s RCS and radar detection probability in threat directions, and meets the needs of real-time micro-satellite attitude planning.

Key words: attitude planning, micro-satellite, radar cross section, particle swarm optimization, computational complexity

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