Evaluation of a Geiger-mode imaging flash lidar in the approach phase for autonomous safe landing on the Moon

The imaging flash lidar has been considered as a promising sensor for the future space missions such as autonomous safe landing, spacecraft rendezvous and docking due to its ability to provide a full 3D scene with a single or multiple laser pulses. The linear-mode flash lidar has been developed and demonstrated for an autonomous safe landing on the Moon in order to provide an accurate distance measurement to the landing site and its 3D image. Yet, the Geiger-mode flash lidar has also been recognized as an emerging technology for the space missions because it is highly sensitive even to a single photon and provides the very accurate timing of photon arrival. In this study, the performance of the Geiger-mode flash lidar is simulated in the approach phase and evaluated for the autonomous landing on the Moon. Furthermore, a new statistical signal processing algorithm is proposed to remove the noise counts in order to obtain the 3D image from a sequence of laser pulses in the situation of the fast moving spacecraft. The algorithm is shown to be effective for the autonomous landing due to its ability to remove noise events under the condition of low signal-to-noise ratio and improve ranging accuracy.     

Investigating γ- and X-ray properties of GRBs using multivariate statistics

We propose to study the interrelation between the γ- (Fluence, 1sec Peakflux, duration) and X-ray (early X flux, 24 h X flux, X decay index, X spectral index, X HI column density) properties using the canonical correlation method. Computing the canonical correlations and variables we show that there is a significant interrelation between the γ- and X-ray data. Using the canonical variables from the analysis, we computed their correlations (canonical loadings) with the original ones. The canonical loadings revealed that the γ-ray fluence and the early X-ray flux give the strongest contribution to the correlation in contrast to the X-ray decay index and spectral index. An interesting new result appears to be the strong contribution of the HI column density to the correlation. Accepting the collapsar model of long GRBs this effect may be interpreted as an indication for the ejection of an HI envelope by the progenitor in the course of producing the GRB.     

一种遥测缓变参数自动判读的新方法

针对遥测参数中缓变参数的自动判读问题，提出一种基于历史数据统计特性的遥测缓变参数自动判读新方法。首先，设计了一种以参数目标数据时标为基准的时间间隔递推算法和线性插值方法，使历史数据与目标数据的时标得到有效统一。其次，基于方向和距离函数构造了双因子等价权函数，并利用抗差最小二乘估计算法得到了参数的估值和标准差。最后，根据参数的估值和标准差对目标数据进行统计分析，依据目标数据的概率分布判断参数是否存在异常，进而实现参数的自动判读。仿真校验结果表明，该方法能有效辨识缓变参数中的异常参数，且具有较强的抑制随机噪声和抗差自适应能力。与传统以人工为主的判读方式相比，该方法能有效提高遥测参数判读的效率和准确性。     

Uncertainty propagation for statistical impact prediction of space debris

Predictions of the impact time and location of space debris in a decaying trajectory are highly influenced by uncertainties. The traditional Monte Carlo (MC) method can be used to perform accurate statistical impact predictions, but requires a large computational effort. A method is investigated that directly propagates a Probability Density Function (PDF) in time, which has the potential to obtain more accurate results with less computational effort. The decaying trajectory of Delta-K rocket stages was used to test the methods using a six degrees-of-freedom state model. The PDF of the state of the body was propagated in time to obtain impact-time distributions. This Direct PDF Propagation (DPP) method results in a multi-dimensional scattered dataset of the PDF of the state, which is highly challenging to process. No accurate results could be obtained, because of the structure of the DPP data and the high dimensionality. Therefore, the DPP method is less suitable for practical uncontrolled entry problems and the traditional MC method remains superior. Additionally, the MC method was used with two improved uncertainty models to obtain impact-time distributions, which were validated using observations of true impacts. For one of the two uncertainty models, statistically more valid impact-time distributions were obtained than in previous research.     

Evolution and History in a new “Mathematical SETI” model

In a recent paper (Maccone, 2011 [15]) and in a recent book (Maccone, 2012 [17]), this author proposed a new mathematical model capable of merging SETI and Darwinian Evolution into a single mathematical scheme. This model is based on exponentials and lognormal probability distributions, called “b-lognormals” if they start at any positive time b (“birth”) larger than zero. Indeed:

• 1.Darwinian evolution theory may be regarded as a part of SETI theory in that the factor f_l in the Drake equation represents the fraction of planets suitable for life on which life actually arose, as it happened on Earth.
• 2.In 2008 (Maccone, 2008 [9]) this author firstly provided a statistical generalization of the Drake equation where the number N of communicating ET civilizations in the Galaxy was shown to follow the lognormal probability distribution. This fact is a consequence of the Central Limit Theorem (CLT) of Statistics, stating that the product of a number of independent random variables whose probability densities are unknown and independent of each other approached the lognormal distribution if the number of factors is increased at will, i.e. it approaches infinity.
• 3.Also, in Maccone (2011 [15]), it was shown that the exponential growth of the number of species typical of Darwinian Evolution may be regarded as the geometric locus of the peaks of a one-parameter family of b-lognormal distributions constrained between the time axis and the exponential growth curve. This was a brand-new result. And one more new and far-reaching idea was to define Darwinian Evolution as a particular realization of a stochastic process called Geometric Brownian Motion (GBM) having the above exponential as its own mean value curve.
• 4.The b-lognormals may be also be interpreted as the lifespan of any living being, let it be a cell, or an animal, a plant, a human, or even the historic lifetime of any civilization. In Maccone, (2012 [17, Chapters 6, 7, 8 and 11]), as well as in the present paper, we give important exact equations yielding the b-lognormal when its birth time, senility-time (descending inflexion point) and death time (where the tangent at senility intercepts the time axis) are known. These also are brand-new results. In particular, the σ=1 b-lognormals are shown to be related to the golden ratio, so famous in the arts and in architecture, and these special b-lognormals we call “golden b-lognormals”.
• 5.Applying this new mathematical apparatus to Human History leads to the discovery of the exponential trend of progress between Ancient Greece and the current USA Empire as the envelope of the b-lognormals of all Western Civilizations over a period of 2500 years.
• 6.We then invoke Shannon's Information Theory. The entropy of the obtained b-lognormals turns out to be the index of “development level” reached by each historic civilization. As a consequence, we get a numerical estimate of the entropy difference (i.e. the difference in the evolution levels) between any two civilizations. In particular, this was the case when Spaniards first met with Aztecs in 1519, and we find the relevant entropy difference between Spaniards an Aztecs to be 3.84 bits/individual over a period of about 50 centuries of technological difference. In a similar calculation, the entropy difference between the first living organism on Earth (RNA?) and Humans turns out to equal 25.57 bits/individual over a period of 3.5 billion years of Darwinian Evolution.
• 7.Finally, we extrapolate our exponentials into the future, which is of course arbitrary, but is the best Humans can do before they get in touch with any alien civilization. The results are appalling: the entropy difference between aliens 1 million years more advanced than Humans is of the order of 1000 bits/individual, while 10,000 bits/individual would be requested to any Civilization wishing to colonize the whole Galaxy (Fermi Paradox).
• 8.In conclusion, we have derived a mathematical model capable of estimating how much more advanced than humans an alien civilization will be when SETI succeeds.

     

基于统计特征的航空发动机风扇外物撞击检测

为了检测识别航空发动机工作过程中的风扇外物撞击事件,采用非接触叶尖振动测量系统对风扇叶片叶尖振动位移进行实时采集与检测。通过风扇叶片非接触叶尖振动位移数据统计分析,发现叶尖振动位移服从正态分布,并采用Epps-Pulley假设检验证明。设计了基于统计特征的风扇叶片外物撞击叶尖振动位移检测算法,采用该方法获取了风扇转子不同转速下外物撞击叶尖振动位移检测阈值。对风扇转子转速为3000r/min状态下,直径16mm、质量为2.9g的外物弹体撞击风扇叶片的振动位移数据进行分析,并采用高速摄像系统对该方法识别结果的可靠性进行验证。结果表明:基于统计特征的发动机风扇外物撞击检测方法,能够准确识别外物撞击风扇叶片事件及发生撞击的叶片编号。     

测试设备统计过程控制方法及其实现

针对测试设备计量保证的具体情况,采用计量确认与统计过程控制组合方法,实现测试设备校准间隔的确定和不确定度的评价。设计了校准间隔确定和统计过程控制计算软件,使得整个控制过程在局域网上操作方便简单。     

疲劳寿命分布模型的统一描述

在大量仿真试验的基础上，发现：①正态分布和3参数Weibull分布之间存在解析关系；②在工程中常见的情况下，3参数Weibull分布可有效地拟合正态和对数正态数据；③当一组数据可同时用2参数Weibull分布（B_1），正态分布（B_2），对数正态分布（B_3）和3参数Weibull分布（B4）描述时，则其B基值间存在以下关系B_1＜B_2＜B_3＜B_4；④在工程中常见的情况下，以3参数Weibull分布拟合正态和对数正态数据，其B基值的相对误差｜ε｜＜5％。     

陨星和月球土壤的光谱识别

文章研究了使用符号检验法和秩和检验法等数理统计方法在短波红外-长波红外光谱范围(2.0795~14.011μm)内选择识别陨星和月球土壤光谱波段的问题,并对所选出的波段进行了相关性分析,最终选择了5个多光谱遥感波段,它们是:2.23~2.66μm,3.52~3.74μm,6.97~7.12μm,8.63~9.09μm和12.84~13.64μm。该项研究对中国探月计划具有参考价值。     

统计能量分析中几种非共振传输与声场间传输系数研究

简述统计能量分析（SEA）中几种非共振传输（近场、直接场、强迫运动）及共振（混响场）传输特性与处理方法,并用简单方法导出声场间一种强迫运动-非共振传输系数表达式,可以满足工程要求。