Contingency and recovery options for the European Student Moon Orbiter

This paper presents an overview of the analysis performed on the lunar orbit and some of the possible contingencies for the European Student Moon Orbiter (ESMO). Originally scheduled for launch in 2014 –2015 as a piggyback payload, it was the only ESA planned mission to the Moon. By way of a weak stability boundary transfer, ESMO is inserted into an orbit around the Moon. Propellant use is at a premium, so the operational orbit is selected to be highly eccentric. In addition, an optimization is presented to achieve an orbit that is stable for 6 months without requiring orbit maintenance. A parameter study is undertaken to study the sensitivity of the lunar orbit insertion. A database of transfer solutions across 2014 and 2015 is used to study the relation between the robustness of weak capture and the planetary geometry at lunar arrival. A number of example recovery scenarios, where the orbit insertion maneuver partially or completely fails, are also considered.     

Differential code bias estimation based on uncombined PPP with LEO onboard GPS observations

Differential Code Bias (DCB) is an essential correction that must be provided to the Global Navigation Satellite System (GNSS) users for precise position determination. With the continuous deployment of Low Earth Orbit (LEO) satellites, DCB estimation using observations from GNSS receivers onboard the LEO satellites is drawing increasing interests in order to meet the growing demands on high-quality DCB products from LEO-based applications, such as LEO-based GNSS signal augmentation and space weather research. Previous studies on LEO-based DCB estimation are usually using the geometry-free combination of GNSS observations, and it may suffer from significant leveling errors due to non-zero mean of multipath errors and short-term variations of receiver code and phase biases. In this study, we utilize the uncombined Precise Point Positioning (PPP) model for LEO DCB estimation. The models for uncombined PPP-based LEO DCB estimation are presented and GPS observations acquired from receivers onboard three identical Swarm satellites from February 1 to 28, 2019 are used for the validation. The results show that the average Root Mean Square errors (RMS) of the GPS satellite DCBs estimated with onboard data from each of the three Swarm satellites using the uncombined PPP model are less than 0.18 ns when compared to the GPS satellite DCBs obtained from IGS final daily Global Ionospheric Map (GIM) products. Meanwhile, the corresponding average RMS of GPS satellite DCBs estimated with the conventional geometry-free model are 0.290, 0.210, 0.281 ns, respectively, which are significantly larger than those obtained with the uncombined PPP model. It is also noted that the estimated GPS satellite DCBs by Swarm A and C satellites are highly correlated, likely attributed to their similar orbit type and space environment. On the other hand, the Swarm receiver DCBs estimated with uncombined PPP model, with Standard Deviation (STD) of 0.065, 0.037 and 0.071 ns, are more stable than those obtained from the official Swarm Level 2 products with corresponding STD values of 0.115, 0.101, and 0.109 ns, respectively. The above indicates that high-quality DCB products can be estimated based on uncombined PPP with LEO onboard observations.     

Design and operation of an anaerobic digester for waste management and fuel generation during long term lunar mission

Waste treatment and management for manned long term exploratory missions to moon will be a challenge due to longer mission duration. The present study investigated appropriate digester technologies that could be used on the base. The effect of stirring, operation temperature, organic loading rate and reactor design on the methane production rate and methane yield was studied. For the same duration of digestion, the unmixed digester produced 20–50% more methane than mixed system. Two-stage design which separated the soluble components from the solids and treated them separately had more rapid kinetics than one stage system, producing the target methane potential in one-half the retention time than the one stage system. The two stage system degraded 6% more solids than the single stage system. The two stage design formed the basis of a prototype digester sized for a four-person crew during one year exploratory lunar mission.     

Automated design architectures for co-orbiting spacecraft swarms for planetary moon mapping

This work describes the design and optimization of spacecraft swarm missions to meet spatial and temporal visual mapping requirements of missions to planetary moons, using resonant co-orbits. The algorithms described here are a part of Integrated Design Engineering and Automation of Swarms (IDEAS), a spacecraft swarm mission design software that automates the design trajectories, swarm, and spacecraft behaviors in the mission. In the current work, we focus on the swarm design and optimization features of IDEAS, while showing the interaction between the different design modules. In the design segment, we consider the coverage requirements of two general planetary moon mapping missions: global surface mapping and region of interest observation. The configuration of the swarm co-orbits for the two missions is described, where the participating spacecraft have resonant encounters with the moon on their orbital apoapsis. We relate the swarm design to trajectory design through the orbit insertion maneuver performed on the interplanetary trajectory using aero-braking. We then present algorithms to model visual coverage, and collision avoidance in the swarm. To demonstrate the interaction between different design modules, we relate the trajectory and swarm to spacecraft design through fuel mass, and mission cost estimations using preliminary models. In the optimization segment, we formulate the trajectory and swarm design optimizations for the two missions as Mixed Integer Nonlinear Programming (MINLP) problems. In the current work, we use Genetic Algorithm as the primary optimization solver. However, we also use the Particle Swarm Optimizer to compare the optimizer performance. Finally, the algorithms described here are demonstrated through numerical case studies, where the two visual mapping missions are designed to explore the Martian moon Deimos.     

Optimal mission planning of the reconfiguration process of satellite constellations through orbital maneuvers: A novel technical framework

In this paper, a general new methodology is presented for the orbital reconfiguration of satellite constellations on the basis of Lambert targeting theorem. In view of the cost and risk reduction, it is very important to consider the problem of satellite constellation reconfiguration with the two constraints of overall mission cost minimization and the desired final configuration. Hence, the dependent non-simultaneous deployment approach is proposed to minimize overall fuel cost. Despite the fact that the satellites deploy in a non-simultaneous manner, supplementary phasing maneuvers on the target orbital pattern to achieve the desired orbital configuration are avoided. Moreover, a novel idea is presented to optimize the flight of satellites, which plays an important role in complying with the constraint of overall fuel cost minimization as much as possible. In order to achieve the global optimal solution of the satellite constellation reconfiguration problem, the efficient hybrid Particle Swarm Optimization/Genetic Algorithm (PSO/GA) technique, is implemented. Finally, to indicate the superiority of the presented method, a comparison to the simultaneous maneuver viewpoint is made on a number of representative cases. The obtained results imply significant reduction of reconfiguration costs by employing the proposed method.     

H-reversal trajectory: A new mission application for high-performance solar sails

The aim of this paper is to quantify the performance of a flat solar sail to perform a double angular momentum reversal maneuver and produce a new class of two-dimensional, non-Keplerian orbits in the ecliptic plane. For a given pair of orbital parameters, the orbital period and the perihelion distance, it is possible to find the minimum solar sail characteristic acceleration required to fulfil a double angular momentum reversal trajectory. This problem is addressed using an optimal formulation and is solved through an indirect approach. The new trajectories are symmetrical with respect to the sun-perihelion line and exhibit a bean-like shape. Two main difficulties must be properly taken into account. On one side the sail is required to perform a rapid reorientation maneuver when it approaches the perihelion. Suitable simulations have shown that such a maneuver is feasible. In the second place the new trajectories require the use of high performance solar sails. For example, assuming an orbital period equal to 5 years, the required solar sail characteristic acceleration is greater than 3.4 mm/s². Such a value, although beyond the currently available sail performance, is comparable to what is required by the original concept of H-reversal maneuvers introduced by Vulpetti in 1996.     

Applying fuzzy bi-dimensional scenario-based model to the assessment of Mars mission architecture scenarios

Sending man to Mars has been a long-held dream of humankind. NASA plans human planetary explorations using approaches that are technically feasible, have reasonable risks and have relatively low costs. This study presents a novel Multi-Attribute Decision Making (MADM) model for evaluating a range of potential mission scenarios for the human exploration of Mars. The three alternatives identified by the Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) include split mission, combo lander and dual scenarios. The proposed framework subsumes the following key methods: first, the conjunction method is used to minimize the number of alternative mission scenarios; second, the Fuzzy Risk Failure Mode and Effects Analysis (RFMEA) is used to analyze the potential failure of the alternative scenarios; third, the fuzzy group Real Option Analysis (ROA) is used to estimate the expected costs and benefits of the alternative scenarios; and fourth, the fuzzy group permutation approach is used to select the optimal mission scenario. We present the results of a case study at NASA’s Johnson Space center to demonstrate: (1) the complexity of mission scenario selection involving subjective and objective judgments provided by multiple space exploration experts; and (2) a systematic and structured method for aggregating quantitative and qualitative data concerning a large number of competing and conflicting mission events.     

轻型通用飞机起飞总重估算方法研究

飞机的起飞总重是飞机的重要设计参数,概念设计阶段首先要做的重要工作之一就是确定飞机的起飞总重。以四人座低速活塞螺旋桨飞机为例,采用任务剖面法和商载航程法分别对起飞总重进行了估算,并对两种方法进行了修正,在此基础上,取两个计算结果的平均值作为最终的起飞总重估算值。通过与对比机型的比较,验证修正后的计算方法和结果是准确合理的,为通用飞机起飞总重的确定和选择提供了参考。     

LARES successfully launched in orbit: Satellite and mission description

On February 13th 2012, the LARES satellite of the Italian Space Agency (ASI) was launched into orbit with the qualification flight of the new VEGA launcher of the European Space Agency (ESA). The payload was released very accurately in the nominal orbit. The name LARES means LAser RElativity Satellite and summarises the objective of the mission and some characteristics of the satellite. It is, in fact, a mission designed to test Einstein's General Relativity Theory (specifically ‘frame-dragging' and Lense-Thirring effect). The satellite is passive and covered with optical retroreflectors that send back laser pulses to the emitting ground station. This allows accurate positioning of the satellite, which is important for measuring the very small deviations from Galilei–Newton's laws. In 2008, ASI selected the prime industrial contractor for the LARES system with a heavy involvement of the universities in all phases of the programme, from the design to the construction and testing of the satellite and separation system. The data exploitation phase started immediately after the launch under a new contract between ASI and those universities. Tracking of the satellite is provided by the International Laser Ranging Service. Due to its particular design, LARES is the orbiting object with the highest known mean density in the solar system. In this paper, it is shown that this peculiarity makes it the best proof particle ever manufactured. Design aspects, mission objectives and preliminary data analysis will be also presented.     

基于有向图模型的卫星任务指令生成算法

面向任务的卫星操控模式具有操作简便、星载资源使用效率高的优点,正在取代指令序列注入成为遥感卫星运控的新模式。文章提出一种基于有向图模型的遥感卫星任务指令序列生成算法,具有线性存储复杂度和计算复杂度,适合存储资源和计算资源受限的星载计算机应用。此算法已在某遥感卫星应用,测试试验表明,采用3个面向任务的高级指令即可生成52种指令序列,任务上行注入效率提升了5倍。本文方法根据有效载荷的使用约束条件,配置有向图模型参数,即可满足各种类型卫星使用。