A genetic algorithm for Initial Orbit Determination from a too short arc optical observation

Optical observations constitute a source of angular measurements of a satellite pass. Commonly, these observations have short durations with respect to the satellite orbit period. As a consequence, the use of classical orbit determination algorithms, as Laplace, Gauss or Escobal methods, give very poor results. The present work faces with the problem of estimating the orbital parameters of an orbiting object using its optical streak acquired by a telescope or a high accuracy camera. In the paper a new technique is developed for the Initial Orbit Determination from optical data by exploiting the genetic algorithms. The algorithm works without restrictions on the observer location. A recent challenging problem is the Initial Orbit Determination with space-based observations. This work focuses on the problem of determinating the orbital parameters of a satellite from an orbiting observer in LEO, using short time observations. We present the results based on a simulation with the observer on a sun-synchronous orbit with a single observation of just 60 s. Monte Carlo simulations are presented with different levels of sensor accuracy to show the reliability of the algorithm. The algorithm is able to yield a candidate solution for each observation. The coplanar case is analyzed and discussed as well.     

OLS算法在无人机传感器故障诊断中的应用

在故障诊断领域,神经网络故障诊断方法以其优良的特性正得到越来越广泛的应用。本文针对无人机的特点提出一种基于RBF神经网络故障诊断方法,通过建立神经网络预测器来实现无人机机载传感器的故障诊断,其中网络学习算法的选取将直接影响神经网络故障诊断的性能。正交最小二乘算法(OLS)以其在设定网络参数方面的优点常用来作为RBF神经网络学习算法。本文将介绍OLS算法的原理和实现步骤,通过VC 6.0编程实现OLS算法,并利用无人机机载传感器数据来验证OLS算法的有效性。     

区域覆盖低轨卫星移动通信系统星座优化设计

针对区域覆盖低轨卫星移动通信系统星座,提出了一种改进遗传算法(GA)的优化设计。根据改进的区域覆盖星座模型,采用可变维数优化的整数与实数混合的染色体编码。给出了算法步骤。某区域覆盖低轨卫星移动通信系统星座优化设计算例结果显示了该算法的有效性。     

航空图像矩形建筑物自动提取方法研究

对航空城区图像自动提取矩形建筑物方法进行了研究。该方法基于从航空城区图像中提取的边缘，通过轮廓跟踪、直线提取得出其相应的直线几何图形。本文引入知识定义了几种构成矩形的基本矩形结构元。先提取直线图形中所有可能构成矩形的基本结构元，进而采用几何结构元分析的方法，根据结构元合并的准则，将各种基本结构元通过一定的合并算法合并成矩形结构。试验结果表明，本文方法提取矩形房屋具有较高的准确率，鲁棒性好，运算速度快，具有较强的实际应用价值。     

带作用力约束的二维装填布局问题--航天器中复杂插座板上插孔的布局优化设计

研究航天器中一种复杂插座板上插孔的布局设计问题 ,简化为在圆形插板上 ,根据给定的 n个插头 ,考虑插座板的非凸的可布空间和插头的拔脱力、插座板的紧固螺栓力、边缘弹簧的弹簧力等约束情况下 ,布置其插孔位置。它属于带作用力约束的二维装填 ( Packing)问题。给出该问题的数学模型 ,并提出一种改进编码的遗传算法进行求解。文后附以航天器复杂插座上插孔布局设计实际工程问题为背景的算例     

基于退火遗传算法的小推力轨道优化问题研究

利用退火遗传算法解决小推力轨道优化问题。首先利用传统混合法将轨道优化问题归结为受非线性方程约束的参数优化问题。通过结合退火和随机惩罚函数对约束条件进行处理后，用遗传算法求解这个参数优化问题。最后再采用局部优化算法提高解的精度。这种算法既保持了传统混合法精度高、解轨线光滑的优点，又克服了传统轨道优化方法收敛性差、初始猜测困难、容易陷入局部极小解的缺点。在本文的最后，利用文中提出的轨道优化算法求解“喷-停-喷”型定常推力幅值地球-木星轨道转移问题。算例证明此算法可以有效地求解小推力轨道转移问题，尤其适用于传统轨道优化方法难以求解的复杂轨道优化问题。     

IMM滤波算法在目标跟踪中的建模和仿真

IMM(Interacting Multiple Model)滤波算法以混合状态系统的观点为基础，利用一个连续状态的微分方程来描述目标的运动，利用一个离散差分方程来描述目标的机动出现，从而建立了更为准确的目标运动模型。本文对该滤波算法进行了进一步的研究，总结了该算法的特点，指出了影响该算法性能的因素，并进行了细致的分析。     

遗传算法在DH106动力箱可靠性优化设计中的应用

本文考虑随机因素的影响，建立了DH106动力箱可靠性优化设计的模型。采用惩罚函数法将约束优化转化为无约束优化。将遗传算法用于DH106动力箱可靠性优化设计的求解，利用交叉和变异来搜索，在较大程度上避免了优化搜索停止在局部优化解上，优化效果十分明显。     

Multi-UAV reconnaissance task allocation for heterogeneous targets using an opposition-based genetic algorithm with double-chromosome encoding

This paper presents a novel multiple Unmanned Aerial Vehicles (UAVs) reconnaissance task allocation model for heterogeneous targets and an effective genetic algorithm to optimize UAVs’ task sequence. Heterogeneous targets are classified into point targets, line targets and area targets according to features of target geometry and sensor’s field of view. Each UAV is regarded as a Dubins vehicle to consider the kinematic constraints. And the objective of task allocation is to minimize the task execution time and UAVs’ total consumptions. Then, multi-UAV reconnaissance task allocation is formulated as an extended Multiple Dubins Travelling Salesmen Problem (MDTSP), where visit paths to the heterogeneous targets must meet specific constraints due to the targets’ feature. As a complex combinatorial optimization problem, the dimensions of MDTSP are further increased due to the heterogeneity of targets. To efficiently solve this computationally expensive problem, the Opposition-based Genetic Algorithm using Double-chromosomes Encoding and Multiple Mutation Operators (OGA-DEMMO) is developed to improve the population variety for enhancing the global exploration capability. The simulation results demonstrate that OGA-DEMMO outperforms the ordinary genetic algorithm, ant colony optimization and random search in terms of optimality of the allocation results, especially for large scale reconnaissance task allocation problems.     

导弹弹道有理Bezier曲线造型与优化方法

为有效克服传统弹道优化方法解的收敛性和全局最优性受搜索算法和初始猜测等影响大的问题,提出了基于有理Bezier曲线的弹道造型与优化计算方法。根据边界条件用光滑且只含少量自由参数的有理Bezier曲线形成参数化弹道,采用逆动力学方法计算导弹攻角、速度等变量及参数化弹道性能指标,通过对自由参数寻优得到最优弹道。这种方法将连续的弹道优化问题转换为对很少自由参数的参数优化问题。与传统方法相比,该方法无需求解2点边值问题,不对导弹运动方程组进行离散化,因而鲁棒性强且解的全局最优性和光滑性好。仿真结果及与自适应伪谱法的比较验证了该方法的实用性和有效性。