大行星、月球和小天体环绕型探测器的轨道问题

针对环绕型探测器的轨道,以具有不同物理特征的大天体(金星、火星和月球等)为例,根据它们的质量大小(决定其引力作用范围的大小)、密度分布和形状特征(决定其非球形引力场的特征),具体阐述了它们各自环绕型探测器轨道的可能形式和不同的变化特征,另外介绍了小天体探测时的两种伴飞形式。关于环绕型探测器的轨道特征,如月球无大气,对其低轨探测器而言没有能量耗散影响,却同样有轨道寿命问题,而且由于其质量分布不均匀,这种现象还与轨道倾角有密切关系;而对火星的环绕型探测器而言,尽管有类似现象,但与轨道倾角的关系却大不相同。这些重要的轨道变化特征,可为深空探测中目标轨道的选择和设计提供依据。     

基于改进启发式蚁群算法的无人机自主航迹规划

无人机自主航迹规划是未来无人机作战使用的关键技术难题。针对传统航迹规划方法存在的求解效率不高、实时性较差、容易陷入局部最优等缺点,提出一种基于改进启发式蚁群算法的无人机自主航迹规划算法。该算法前期使用Dijkstra算法进行初始化航迹,引入启发式信息,提高搜索效率;采用Logistic混沌映射初始化信息素,增加解的多样性,提高算法收敛速度;算法中、后期采用多航迹选择策略和模拟退火机制,提高全局搜索能力,避免因收敛速度过快而陷入局部最优解。对该算法进行仿真分析,结果表明:在存在威胁和障碍的复杂环境中,本文提出的改进启发式蚁群算法与标准蚁群算法相比,能够有效规划出一条从起点到终点的航迹,并且寻优精度更高,收敛速度更快,具有一定的应用价值。     

基于支持向量机和蚁群算法的空间目标分类

研究了基于支持向量机的空间目标分类中核参数和误差惩罚因子的选择问题.将蚁群算法与支持向量机相结合,提出了一种自动优选支持向量机模型参数的方法,克服了以往反复试验以确定其参数的缺点.采用所提出的方法,分类正确率迭90%左右,验证了该方法的有效性.     

Threshold Selection Method Based on Reciprocal Gray Entropy and Artificial Bee Colony Optimization

Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional（2-D）histogram region oblique division and artificial bee colony（ABC）optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional（1-D）method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization（NCPSO）,the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.     

蚁群算法的改进设计及在航迹规划中的应用

将蚁群算法与人工势场算法相结合，提出了一种新的寻优算法。在算法的设计过程中，首先引入人工势场法进行蚁群算法初始信息素的分配，避免了在迭代初始阶段，信息素太少与启发信息不成比例而使得蚂蚁集中在启发信息最强的路径上，从而陷入局部最优的问题。其次，通过引入势场引导函数改进蚁群算法的状态转移函数，避免了在三维空间中蚂蚁搜索容易忽视节点周围障碍物因素，从而陷入盲目选择导致搜索时间过长的问题。将优化算法应用于无人机三维航迹规划问题的求解，并通过仿真验证了有效性。     

Depth dependency of neutron density produced by cosmic rays in the lunar subsurface

Depth dependency of neutrons produced by cosmic rays (CRs) in the lunar subsurface was estimated using the three-dimensional Monte Carlo particle and heavy ion transport simulation code, PHITS, incorporating the latest high energy nuclear data, JENDL/HE-2007. The PHITS simulations of equilibrium neutron density profiles in the lunar subsurface were compared with the measurement by Apollo 17 Lunar Neutron Probe Experiment (LNPE). Our calculations reproduced the LNPE data except for the 350–400 mg/cm² region under the improved condition using the CR spectra model based on the latest observations, well-tested nuclear interaction models with systematic cross section data, and JENDL/HE-2007.     

数字化城市交通向导仿真的蚁群优化算法

以求解旅行商问题的蚁群算法为基础,充分考虑交通向导最佳路径的具体要求,对算法的选择机制、更新机制以及协调机制作进一步改进,引入自适应的转移策略,并融入节约法,以克服基本蚁群算法计算时间长、易出现停滞等缺陷。以湖北荆门地区车辆选择路径为研究对象,采用蚁群优化算法建立了车辆最佳路径的模型,并对其进行了仿真分析。仿真实验结果表明,优化算法比基本蚁群算法的路径更优,寻路时间更短。     

Coupling of earth’s magnetosphere,solar wind and lunar plasma environment

The Moon does not have significant atmosphere and magnetic field. So it was considered like a passive absorber of incoming plasma. The latest observation revealed that the significant deflected proton fluxes exist over magnetic anomalies at lunar surface. Such deflection implies that the magnetic anomalies may act as magnetosphere-like obstacles (mini-magnetospheres), modifying the upstream plasma.     

SNR periodical variation of Chang'E-3 spacecraft orbiting the Moon

Chang'E-3 spacecraft was orbiting the Moon from December 6–14, 2013, and very long baseline interferometry(VLBI) observations were performed to improve the accuracy of its orbit determination. In the process of recording VLBI raw data, 2 bits quantization was implemented.Interesting phenomenon was that signal-to-noise ratio(SNR) of each VLBI station experienced periodical change and had large variation on amplitude while in the Moon's orbit, whereas SNR kept in a stable level after Chang'E-3 landed on the Moon. Influence of varying elevation angle on SNR was analyzed and compensation of 2 bits quantization harmonics to SNR calculation was investigated. Most importantly, telescope system noise temperature increase caused by the Moon was computed along the time of Chang'E-3 orbiting the Moon, and well matched SNR changing trend in terms of correlation coefficients.     

Libration point orbit rendezvous using PWPF modulated terminal sliding mode control

The near-range rendezvous problem of two libration point orbit spacecraft in the Earth–Moon system is studied using the terminal sliding mode control which enables a time-fixed process with the flight time prescribed a priori. The underlying dynamics are the full nonlinear equations of motion for a complete Solar System model. For practical purposes, two means of pulse-width pulse-frequency (PWPF) modulation are employed to realize the theoretical continuous control with a series of thrust pulses. Extensive simulations with major errors taken into account show that the sliding mode controller can successfully guide the chaser to a given staging node with the final position and velocity errors, on average, lower than 20 m and 1 mm/s, respectively. Compared with the glideslope guidance previously studied, the proposed approach outperforms the former by saving approximately 50–60% of total delta-v.