Improvement of the GRACE star camera data based on the revision of the combination method

The new release of the sensor and instrument data (Level-1B release 02) of the Gravity Recovery and Climate Experiment (GRACE) had a substantial impact on the improvement of the overall accuracy of the gravity field models. This has implied that improvements on the sensor data level can still significantly contribute to arriving closer to the GRACE baseline accuracy. The recent analysis of the GRACE star camera data (SCA1B RL02) revealed their unexpectedly higher noise. As the star camera (SCA) data are essential for the processing of the K-band ranging data and the accelerometer data, thorough investigation of the data set was needed. We fully reexamined the SCA data processing from Level-1A to Level-1B with focus on the combination method of the data delivered by the two SCA heads. In the first step, we produced and compared our own combined attitude solution by applying two different combination methods on the SCA Level-1A data. The first method introduces the information about the anisotropic accuracy of the star camera measurement in terms of a weighing matrix. This method was applied in the official processing as well. The alternative method merges only the well determined SCA boresight directions. This method was implemented on the GRACE SCA data for the first time. Both methods were expected to provide optimal solution characteristic by the full accuracy about all three axes, which was confirmed. In the second step, we analyzed the differences between the official SCA1B RL02 data generated by the Jet Propulsion Laboratory (JPL) and our solution. SCA1B RL02 contains systematically higher noise of about a factor 3–4. The data analysis revealed that the reason is the incorrect implementation of algorithms in the JPL processing routines. After correct implementation of the combination method, significant improvement within the whole spectrum was achieved. Based on these results, the official reprocessing of the SCA data is suggested, as the SCA attitude data are one of the key observations needed for the gravity field recovery.     

计算机辅助功能危险评估方法研究

功能和安全一直是高风险复杂系统的关键问题。传统的功能危险评估由安全工程师手工进行分析，面对高度复杂系统时，就会变得难以完成且容易出错。解决这种问题的一个途径就是利用计算机进行辅助。为此提出一种计算机辅助的功能危险评估方法，采用状态图语言搭建系统状态模型，将功能失效影响直观地从系统状态转移图上表达出来。并且在系统状态模型的基础上，采用计算机编程快速计算出导致系统故障的失效组合以及最小割集。最后以飞机为对象证明了方法的可行性。     

星载二次电源的电磁兼容预设计

针对星载二次电源电磁兼容试验中辐射发射的超标问题,提出了电磁兼容预设计方法.分析二次电源电磁干扰产生的机理,利用SPICE仿真器建立传导干扰的电路等效模型,优化电路设计得到传导干扰源;应用修正的单线模型近似计算辐射干扰,根据计算结果,利用遗传算法优化等效偶极子的数目和分布位置建立场等效模型;基于场路结合的方法,以传导干...     

几种有限可重组合的公式型解法

对于有限可重组合问题 ,通常用母函数方法[1] 作解答 ,但当数据比较大时 ,母函数方法就不太方便。更重要的是 ,母函数方法很难在计算机中实现。本文对几种有限可重组合问题给出了公式型解法     

最优投资组合模型

本模型意在寻求净收益Ｒ尽可能大而风险ε尽可能小的一种投资组合，先介绍了在期望风险为一定值时单纯形法求解净收益最大的投资组合的全过程。     

基于MAP的装备保障资源需求预测研究

针对装备保障资源需求预测难的问题,本文利用EM算法将单装备的保障资源需求点过程拟合为马尔可夫到达过程(MAP).通过仿真获取整个装备的备件更换时间序列,并举例说明了该方法的有效性.     

A novel approximation of basic probability assignment based on rank-level fusion

Belief functions theory is an important tool in the field of information fusion. However, when the cardinality of the frame of discernment becomes large, the high computational cost of evidence combination will become the bottleneck of belief functions theory in real applications. The basic probability assignment (BPA) approximations, which can reduce the complexity of the BPAs, are always used to reduce the computational cost of evidence combination. In this paper, both the cardinalities and the mass assignment values of focal elements are used as the criteria of reduction. The two criteria are jointly used by using rank-level fusion. Some experiments and related analyses are provided to illustrate and justify the proposed new BPA approximation approach.     

科技论文副标题英译的常见问题

运用调查和对比分析的手段，指出当前国内期刊在处理带有副标题的科技论文标题时常用的方法及一些常见错误，并提出一些建议。     

浅谈舰载直升机的海上试飞

针对舰载直升机的特殊使用环境，分析了舰船运动情况对舰载直升机实施起飞、着舰和舰上机动飞行的影响，最后，探讨了MIL－F－83300等直升机规范对舰载直升机的各种使用规定及特殊的飞行品质要求。     

超声速翼—身组合体Euler方程数值解

本文采用MacCormack二步显式差分格式,用空向推进法给出了超声速翼-身组合体Euler方程的数值解。应用薄翼假设生成简易的多区网格。采用Kentzer方案处理边界。计算中通过对横流速度型的修正改善了背风面压力分布特性,解决了推进中断问题,同时模拟出背风涡。