机载PD雷达速度波门拖引干扰建模与评估

通过对速度波门拖引干扰机理及其拖引过程的分析，建立了以跟踪误差、压制系数、拖引时间和干扰成功率等作为拖引干扰评估指标的评估模型，并对它们之间的关系，结合Matlab仿真对速度波门拖引干扰效能评估给予了分析论证。     

基于改进的PRI方法对植被冠层叶绿素含量的反演

叶绿素是植被光合作用的重要色素，对植被的健康状况有直接的指示作用。利用遥感技术准确、快速地获取植被叶绿素含量对精准农业具有重要意义。文章在对各种光化学植被指数（Photochemical Reflectance Index，PRI）与叶绿素含量进行敏感性分析的基础上，提取出对叶绿素变化较为敏感的组合形式，并考虑土壤背景的影响，提出了一种改进的PRI模型，同时利用在小汤山试验田获取的地面采样数据和实用模块化成像光谱仪（Operative Modular Imaging Spectrometer，OMIS）数据进行验证。结果表明，基于OMIS高光谱数据，模型能够很好地对植被冠层的叶绿素含量进行反演，反演的叶绿素含量与实测值具有较好的相关性。     

倾转旋翼机动态倾转过渡过程的操纵策略优化

利用最优控制方法研究倾转旋翼机的最优动态倾转过渡过程,并得到最优操纵策略,使得由时间、姿态角变化以及驾驶员工作负荷等组成的性能指标达到最小。首先,在基本纵向刚体飞行动力学模型的基础上引入混合操纵方程,并使用杆量位移的一阶导数作为控制量,形成适用于计算倾转旋翼机动态倾转过渡过程的飞行动力学模型,从而能在动态倾转操纵策略优化过程中考虑到操纵系统特性对操纵量变化速度的限制,以及避免操纵量在优化过程中出现跳跃不连续。然后,将倾转旋翼机的最优动态倾转过渡过程转化为非线性动态最优控制问题,建立合理的性能指标,并采用直接转换法和序列二次规划算法进行求解。最后,以XV-15倾转旋翼机为样机,分别计算正向和逆向最优动态倾转过渡过程,并与驾驶员飞行仿真数据进行对比。结果表明:飞行状态量的时间历程与文献吻合地较好,且俯仰姿态角和杆量位移变化更加柔和。最优控制方法可以用于研究倾转旋翼机的最优动态倾转过渡过程。     

航天项目风险管理——预先识别与控制风险到可接受程度

风险是对成功实现项目目标的威胁。航天项目风险管理是预先对风险进行系统地识别、评估、跟踪和降低的活动,是一个在整个项目生命周期内连续、反复进行的过程。风险管理的目的是将风险降低到一个可接受的水平。根据风险对成功威胁的程度排序,可以使管理的关注点集中到风险程度较大的问题上。技术风险管理关注影响技术性能的风险,是项目风险管理的组成部分。     

NASA Human Health and Performance Center: Open innovation successes and collaborative projects

In May 2007, what was then the Space Life Sciences Directorate published the 2007 Space Life Sciences Strategy for Human Space Exploration, setting the course for development and implementation of new business models and significant advances in external collaboration over the next five years. The strategy was updated on the basis of these accomplishments and reissued as the NASA Human Health and Performance Strategy in 2012, and continues to drive new approaches to innovation for the directorate. This short paper describes the successful execution of the strategy, driving organizational change through open innovation efforts and collaborative projects, including efforts of the NASA Human Health and Performance Center (NHHPC).     

Planetary protection on international waters: An onboard protocol for capsule retrieval and biosafety control in sample return mission

Planetary protection has been recognized as one of the most important issues in sample return missions that may host certain living forms and biotic signatures in a returned sample. This paper proposes an initiative of sample capsule retrieval and onboard biosafety protocol in international waters for future biological and organic constituent missions to bring samples from possible habitable bodies in the solar system. We suggest the advantages of international waters being outside of national jurisdiction and active regions of human and traffic affairs on the condition that we accept the Outer Space Treaty. The scheme of onboard biological quarantine definitely reduces the potential risk of back-contamination of extraterrestrial materials to the Earth.     

Aircraft air conditioning system health state estimation and prediction for predictive maintenance

The vast potential of system health monitoring and condition based maintenance on modern commercial aircraft is being realized through the innovative use of Airplane Condition Monitoring System (ACMS) data. However there are few methods addressing the issues of failure prognostics and predictive maintenance for commercial aircraft Air Conditioning System (ACS). This study developed a Bayesian failure prognostics approach using ACMS data for predictive maintenance of ACS. First, a health index characterizing the ACS health state is inferred from a multiple sensor signals using a data driven method. Then a dynamic linear model is proposed to describe the degradation process for failure prognostics. Bayesian inference formulas are carried out for degradation estimation and prediction. The developed approach is applied on a passenger aircraft fleet with ACMS data recorded for one year. The analysis of the case study shows that the developed method can produce satisfactory prognostics results, where all the ACS failure precursors are identified in advance, and the relative errors for the failure time prediction made when just entering the degradation warning stage are less than 8%. This would allow operators to proactively plan future maintenance.     

Physical implications of discrepancy between summer and winter PC indices observed in the course of magnetospheric substorms

The PC index based on a statistically justified relationship between the polar cap magnetic activity and the interplanetary electric field E_KL has been derived as a value standardized for the E_KL intensity regardless of season, UT and hemisphere. As a result, the summer and winter PC indices are consistent with one another under ordinary conditions. Discrepancies between the summer and winter PC indices arising in the course of magnetospheric substorms are analyzed in this paper. It is argued that the channel of enhanced conductivity, formed in the auroral oval owing to intense auroral particle precipitation, strongly improves the conditions for closure of the Region 1 field-aligned currents in the winter dark polar region but only trivially affects the conditions of the Region 1 FAC closure in the summer sunlit ionosphere. Since the coefficients describing the relationship between E_KL and the polar cap magnetic activity were derived for statistically justified (i.e., mean) conditions, their application to such abnormal situation, as intense field-aligned currents in the winter dark polar region, leads to overestimation of the winter PC index. The summer and winter PC indices level off as soon as the intense auroral particle precipitation terminates and the auroral ionosphere in the winter and summer polar caps returns to the ordinary (statistically justified) state.     

Using vegetation indices and texture measures to estimate vegetation fractional coverage (VFC) of planted and natural forests in Nanjing city,China

Vegetation fractional coverage (VFC) is an important vegetation parameter affecting exchanges of carbon, water, energy between the atmosphere and surface. In this study, the applicability of tonal and texture measures calculated using an IKONOS_2 image in retrieving VFC of forests was investigated in the urban area of Nanjing city, China. Four spectral vegetation indices (VI) and six texture measures (TEX) were related to VFCs acquired from in situ measurements. Models for estimating VFC based on VIs or/and TEXs were established and validated for planted low broad-leaf forest plots (PLB), planted mature forest plots (PMF), natural broad-leaf forest plots (NBF), and all forest plots (ALLv), respectively. The results show that high spatial resolution remote sensing data is applicable to estimate VFC in urban areas, and TEXs may act as effective supplements of vegetation indices (VIs) for the retrieval of VFC. VIs are suitable for VFC estimation of mature forests (such as NBF and PMF) with high vegetation density, and TEXs can yield a more accurate estimate for planted forests (such as PLB and PMF) with regular spatial distribution if they are calculated with proper parameters, such as window size. The combination of VIs and TEXs improve the estimation of VFC if forest types are not previously differentiated. The results can be used as a reference for determining effective spectral or texture parameters in VFC estimation under similar environmental conditions according to vegetation maturity and regularity.     

A data-driven health indicator extraction method for aircraft air conditioning system health monitoring

Prognostics and Health Management (PHM) has become a very important tool in modern commercial aircraft. Considering limited built-in sensing devices on the legacy aircraft model, one of the challenges for airborne system health monitoring is to find an appropriate health indicator that is highly related to the actual degradation state of the system. This paper proposed a novel health indicator extraction method based on the available sensor parameters for the health monitoring of Air Conditioning System (ACS) of a legacy commercial aircraft model. Firstly, a specific Airplane Condition Monitoring System (ACMS) report for ACS health monitoring is defined. Then a non-parametric modeling technique is adopted to calculate the health indicator based on the raw ACMS report data. The proposed method is validated on a single-aisle commercial aircraft widely used for short and medium-haul routes, using more than 6000 ACMS reports collected from a fleet of aircraft during one year. The case study result shows that the proposed health indicator can effectively characterize the degradation state of the ACS, which can provide valuable information for proactive maintenance plan in advance.