MESSENGER Mission Design and Navigation

Nearly three decades after the Mariner 10 spacecraft’s third and final targeted Mercury flyby, the 3 August 2004 launch of the MESSENGER (MErcury Surface, Space ENvironment, GEochemistry, and Ranging) spacecraft began a new phase of exploration of the closest planet to our Sun. In order to ensure that the spacecraft had sufficient time for pre-launch testing, the NASA Discovery Program mission to orbit Mercury experienced launch delays that required utilization of the most complex of three possible mission profiles in 2004. During the 7.6-year mission, the spacecraft’s trajectory will include six planetary flybys (including three of Mercury between January 2008 and September 2009), dozens of trajectory-correction maneuvers (TCMs), and a year in orbit around Mercury. Members of the mission design and navigation teams optimize the spacecraft’s trajectory, specify TCM requirements, and predict and reconstruct the spacecraft’s orbit. These primary mission design and navigation responsibilities are closely coordinated with spacecraft design limitations, operational constraints, availability of ground-based tracking stations, and science objectives. A few days after the spacecraft enters Mercury orbit in mid-March 2011, the orbit will have an 80° inclination relative to Mercury’s equator, a 200-km minimum altitude over 60°N latitude, and a 12-hour period. In order to accommodate science goals that require long durations during Mercury orbit without trajectory adjustments, pairs of orbit-correction maneuvers are scheduled every 88 days (once per Mercury year).     

Entropy based inverse design of aircraft mission success space in system-of-systems confrontation

This paper presents a practical and efficient design method for aircraft Mission Success Space (MSS) based on the entropy measurement (EM). First, fundamentals regarding MSS, Inverse Design (ID) and entropy are discussed. Then, two EM schemes of entropy-based ID and the whole MSS ID procedure are given to demonstrate alternative ways of entropy quantification and MSS design. After that, Genetic Algorithm (GA) is utilized as a search algorithm to find the optimal MSS design with the minimum objective, entropy, in each EM scheme. A simulation case of aircraft penetration mission is given for the method validation where the best aircraft MSS design is obtained by GA according to the minimum entropy. Results from two schemes are compared at the end.     

共面圆轨道航天器在轨服务任务规划

为了降低"一对多"在轨服务的成本,以共面圆轨道卫星群为研究对象,开展了在轨服务任务规划问题的研究。首先,对"一对多"在轨服务任务场景进行了分析,建立了任务规划数学模型,将其简化为包含内层Lambert问题、外层最优时间分配问题的双层优化模型。然后,给出了任务规划求解方法及流程,提出采用工程图解法的思想求解内层多圈Lambert问题,采用遗传算法求解外层最优时间分配问题。最后,以三个目标航天器为例,针对限制和不限制在轨服务任务完成总时间这两种情况,采用上述方法进行求解,计算结果验证了方法的有效性。     

Flight trajectory optimization of sun-tracking solar aircraft under the constraint of mission region

The optimal yawing angle of sun-tracking solar aircraft is tightly related to the solar azimuth angle, which results in a large arc flight path to dynamically track the sun position. However, the limited detection range of payload usually requires solar aircraft to loiter over areas of interest for persistent surveillance missions. The large arc sun-tracking flight may cause the target area on the ground to be outside the maximum coverage area of payload. The present study therefore develops an optimal flight control approach for planning the flight path of sun-tracking solar aircraft within a mission region. The proposed method enables sun-tracking solar aircraft to maintain the optimal yawing angle most of the time during daylight flight, except when the aircraft reverses its direction by turning flight. For a circular region with a mission radius of 50 km, the optimal flight trajectory and controls of an example Λ-shaped sun-tracking solar aircraft are investigated theoretically. Results demonstrate the effectiveness of the proposed approach to optimize the flight path of the sun-tracking aircraft under the given circular region while maximizing the battery input power. Furthermore, the effects of varying the mission radius on energy performance are explored numerically. It has been proved that both net energy and energy balance remain nearly constant as the radius constraint varies, which enables the solar aircraft to achieve perpetual flight at almost the same latitude as the large arc flight. The method and results presented in this paper can provide reference for the persistent operation of sun-tracking solar aircraft within specific mission areas.     

卫星导航地面试验验证的平行系统方法

应用平行系统理论,研究全球卫星导航系统（GNSS）人工建模、计算实验和平行执行的方法。首先构建GNSS平行系统框架,分析GNSS平行系统人工建模的关键技术,提出基于代理（Agent）的导航系统实体建模方法;然后根据计算实验需求,设计GNSS平行系统在人工建模、试验支持与运行维护等方面的计算实验方法及流程。在此基础上,给出GNSS平行系统的运行模式及其平行执行过程。最后,以GNSS平行系统在人员培训方面的应用为例,说明GNSS平行系统在实际GNSS运行维护方面的应用。研究结果表明,建立GNSS平行系统是提高GNSS建设和运行维护效率的有效方法。     

启发式深空探测器任务规划方法

针对深空探测器的任务规划过程特点,考虑约束的数值特性,提出一种基于规划活动相关度的领域无关启发式规划方法。定义了活动的相关度,结合规划过程,给出自学习式的相关度动态更新过程。设计基于相关度的活动选择机制,形成启发式规划算法。数值计算结果表明,文中提出的方法有效地减少了规划过程中规划步数和回溯步数,提高了深空探测器规划的效率。     

多级备件供需状态下装备使用可用度的优化

装备通常采用三级保障体制,具有多种备件供需状态,采用马尔可夫过程建立装备使用可用度(AO)模型是一个三维具有不等式约束的非线性方程。依此模型难于直观地选定AO的设计参数。本文采用优化设计方法之一的复形法较好地解决了这个问题,在λ,μ,б确定的可行域中,获得了AO的优化解及相应的λ,μ,б数值。并用实例说明优化方法可方便的解决装备论证中参数的选取问题。     

Encounter trajectories for deep space mission ASTER to the triple near Earth asteroid 2001-SN263. The laser altimeter (ALR) point of view

In cooperation with Russia, the Brazilian deep space mission ASTER plans to send a small spacecraft to investigate the triple asteroid 2001-SN263. The nearest launch opportunities for this project include June 2022 and June 2025. One main exploration campaign is being planned with focus on the largest asteroid (Alpha). Among the instruments under development, a laser altimeter (named ALR) was preliminarily designed and presented in 2010–2011. Many studies to define mission and instruments requirements were performed aiming at the characterization of important issues for the successful realization of the mission. Among them, the identification of a suitable trajectory that could be followed by the ASTER spacecraft in the encounter phase, when the main campaign will take place. This paper describes the effort undertaken with focus on the laser altimeter operation. Possible encounter trajectories were modelled and simulated to identify suitable approach parameters and conditions allowing the accomplishment of the intended investigation. The simulation also involves the instrument operation, considering approach geometry, attitude, relative motion, time/date, and the dynamics of the main asteroid. From the laser altimeter point of view, keeping in mind the desired coverage results (50% minimum surface coverage of asteroid Alpha, complying with horizontal and vertical resolution requirements), results point out crucial features for the encounter trajectory, like the need for a small inclination (10^-6 degrees; with respect to the asteroid's orbit), the most favourable spacecraft positioning (between the Sun and the asteroid) and pointing condition (back to the Sun), the minimum amount of achievable surface coverage (58%, focused on central areas), and the most proper time to conduct the main campaign (January 2025). Concerning the instrument, results offer refined values for divergence angle (500 to 650 μrad, half-cone), pulse repetition frequencies (from 1/20 to 1 Hz), and consequent data generation rates. A simulation tool that can use any 3D generated trajectories as input data was created for the analyses presented here. Although created for the ALR in this mission, this simple analysis tool can be adapted to other instruments in this or other missions.     

Modeling satellite battery aging for an operational satellite simulator

During the satellite’s operations, simulation tools perform an important role in ensuring the space mission success. In this sense, the models implemented in the context of an operational satellite simulator that enables analysis of health status and maintenance during operations shall reflect the current satellite behavior with high fidelity. Moreover, it is complicated to obtain all analytical models of a satellite’s disciplines, considering its aging. This paper proposes an Artificial Neural Network (ANN) to reproduce the battery voltage behavior of a large sun-synchronous remote sensing satellite, the CBERS-4, currently in operation. Using the genetic algorithm to find the best network architecture of ANN, the neural model for this application presented an error of less than 1%, demonstrating its feasibility to obtain a high fidelity model for an operational simulator enabling extend analyses. The paper addresses advanced techniques aligned with the space industry’s future, increasing the ability to analyze a large amount of data and improve the space system’s operation.     

Unmanned aerial vehicle swarm mission reliability modeling and evaluation method oriented to systematic and networked mission

With the development of Unmanned Aerial Vehicle (UAV) system autonomy, network communication technology and group intelligence theory, mission execution in the form of a UAV swarm will be an important realization of future applications. Traditional single-UAV mission reliability modeling methods have been unable to meet the requirements of UAV swarm mission reliability modeling. Therefore, the UAV swarm mission reliability modeling and evaluation method is proposed. First, aimed at the interdependence among the multiple layers, a multi-layer network model of a UAV swarm is established. At the same time, based on the system having the following characteristics—using a mission chain to complete the mission and applying the connectivity of the mission network—the mission network model of a UAV swarm is established. Second, vulnerability and connectivity are selected as two indicators to reflect the reliability of the mission, and aimed at random attack and deliberate attack, vulnerability and connectivity evaluation methods are proposed. Finally, the validity and accuracy of the constructed model are verified through simulations, and the model and selected indicators can meet the reliability requirements of the UAV swarm mission. In this way, this study provides quantitative reference for UAV-swarm-related decision-making work and supports the development of UAV-swarm-related work.