The entropy in groups – a clue to galaxy formation

The entropy in the hot X-ray gas in groups of galaxies is a fossil of the process of galaxy formation The amount of entropy in these low mass systems considerably exceeds that predicted from structure formation models. To explain these results requires “extra” energy which is a relic of the process of star formation and active galaxy heating. We present new XMM results on the entropy and entropy profiles. These results are inconsistent with pre-heating scenarios which have been developed to explain the entropy floor in groups but are broadly consistent with models of structure formation which include the effects of heating and/or the cooling of the gas. The total entropy in these systems provides a strong constraint on all models of galaxy and group formation, and on the poorly defined feedback process which controls the transformation of gas into stars and thus the formation of structure in the universe.     

基于BP神经网络的软件项目成本估测方法

为进一步提高软件项目成本估测的准确度,减少在使用传统估测方法时产生的较大误差,提出了一种基于BP神经网络算法的软件项目成本估测模型。利用BP神经网络对软件项目成本进行估计,采用梯度下降自适应Ir的BP算法训练,仿真结果表明,基于算法的软件项目成本估测值与实际成本的偏差较小。     

航空发动机研制费估算工作的现状与展望

针对在立项论证阶段对航空发动机项目经费进行快速并有效的估算的问题,基于中国航空发动机的研制现状和型号数据的积累情况,分析了发动机研制经费估算工作的重点与难点以及相应的解决途径,并采用偏最小二乘法建立了航空发动机研制经费估算模型。计算结果表明:该发动机模型精度较高,已经应用于国产某型涡扇发动机的经费测算工作中,并可用于中国未来航空发动机型号的研制经费估算。     

非圆实信号MIMO雷达中基于实值ESPRIT的角度估计

研究单基地多输入多输出(MIMO)雷达中的波达角(DOA)估计问题,提出了一种基于非圆(NC)实信号的实值旋转不变性信号参数估计(ESPRIT)算法.首先对接收信号进行降维变换,降低运算复杂度;之后根据非圆实信号特性构造中心Hermitian对称矩阵,通过酉(Unitary)变换将复数运算转为实数,进一步降低复杂度;最后根据ESPRIT得到角度估计.该算法无需谱峰搜索,运算复杂度较NC ESPRIT和Unitary ESPRIT大大降低,且该算法的角度估计性能优于后两种算法.论文分析了所提算法的复杂度,并推导了克拉美-罗界(CRB).仿真结果验证了该算法的有效性.     

基于约束最小冗余线阵与干扰对消的测向方法

针对有源干扰背景下信号源和干扰源的个数超过线阵的自由度而产生线阵饱和现象,提出一种将约束最小冗余线阵与干扰对消技术相结合的测向方法。通过将无源状态和有源状态下线阵输出数据的协方差矩阵进行对消运算去除有源干扰和噪声分量,并对约束最小冗余线阵的波达方向(DOA)估计算法进行改进,构造了新的协方差Toeplitz矩阵,有效抑制了由阵列非均匀性导致的伪峰,提高了阵列的DOA估计性能。仿真结果表明:该算法在低信噪比背景下具有抗有源干扰能力,扩展了阵列孔径,并具有较高的测向精度和鲁棒性。     

基于距离代价函数和信息熵的发动机性能参数估计研究

研究发动机部件性能参数变化规律,对于减少维修次数和推动视情维修具有重要意义。针对测量参数个数少于待估性能参数的情况,给出了一种通过构建代价函数和优化算法的参数估计方法。原代价函数只考虑当前点参数,缺少与前面点参数的联系,因此结合自组织神经网络,构造了包含以前与当前点参数的距离代价函数。并提出了一种快速的参数估计方法。由于准确的部件性能参数很难获取,并且参数趋势估计不同于单纯的点估计问题,以对应的测量参数为基础,利用信息熵方法评定部件性能参数估计效果。进一步得到距离代价函数对应的参数信息熵为0.6805,优于原代价函数的估计结果。最后通过实例验证了参数估计方法的有效性。      

Reliability analysis based on a novel density estimation method for structures with correlations

Estimating the Probability Density Function (PDF) of the performance function is a direct way for structural reliability analysis,and the failure probability can be easily obtained by integration in the failure domain.However,efficiently estimating the PDF is still an urgent problem to be solved.The existing fractional moment based maximum entropy has provided a very advanced method for the PDF estimation,whereas the main shortcoming is that it limits the application of the reliability analysis method only to structures with independent inputs.While in fact,structures with correlated inputs always exist in engineering,thus this paper improves the maximum entropy method,and applies the Unscented Transformation (UT) technique to compute the frac tional moments of the performance function for structures with correlations,which is a very efficient moment estimation method for models with any inputs.The proposed method can precisely estimate the probability distributions of performance functions for structures with correlations.Besides,the number of function evaluations of the proposed method in reliability analysis,which is determined by UT,is really small.Several examples are employed to illustrate the accuracy and advantages of the proposed method.     

高超声速飞行器气动伺服弹性的自适应抑制

针对弹性高超声速飞行器的气动伺服弹性问题，提出一种结合线性自抗扰和自适应陷波器的综合控制方案。针对强耦合和强不确定性问题，采用线性自抗扰控制对总扰动进行快速估计和补偿。为了在最小化对刚体控制性能影响的同时实现对频率未知且时变的弹性模态的抑制，采用能够在线估计弹性频率的自适应陷波器。根据气动伺服弹性抑制问题的特点提炼出对自适应陷波器的性能需求。针对这些需求设计了两种基于递推最大似然法的多频率直接辨识方案——参数单独自适应和同时自适应方案。为了提高辨识算法在各种随机扰动下的鲁棒性，在此基础上提出一种在线有效性监督机制，并通过大量的数字仿真对两种方案进行了性能对比。最后，在弹性高超声速飞行器模型上进行仿真，仿真结果验证了所提控制方案的有效性。     

基于时空显著性建模的空中飞行器跟踪方法

以复杂背景下空中飞行器的鲁棒视觉跟踪问题为研究背景，为解决现有跟踪方法目标表征模型不够精确，算法鲁棒性严重受到目标形变、宽高比变化、复杂背景等因素干扰的问题，提出了建模跟踪场景中独立物体的显著性特性，用于构建精确的目标模型。提出的显著性估计方法有别于传统的单帧检测方法，利用跟踪算法提供的背景先验知识以及多帧图像观测数据，使用时空联合的方式进行建模估计，其结果用来指导目标跟踪算法选取有效视觉特征，建立精确目标表征模型，减小背景区域对算法模型的干扰。实验表明，提出的方法为上述难点问题提供了有效的解决方案，对空中飞行器的跟踪精度与鲁棒性优于大多数最先进的主流方法，在其他类型的目标跟踪任务中也有十分优越的性能表现。     

Influence of optical parameters on a solar sail motion

Detailed dynamic modeling of a solar sail requires recording of solar radiation pressure influence. A photon-solar sail is determined by the thrust value and the direction. We define the solar sail’s reflectivity depending on the film materials, the sail design and temperature, the thickness of multiple layers, and degradation factor, with a reasonable degree of accuracy. Thus, this work is devoted to the identification of optical characteristics of thin multilayer films in space flight conditions, i.e. to finding its reflectance, absorbance, and transmittance. In particular, the paper asks whether the solar sail simulates by a mathematical model of the optical characteristics of a multilayer epitaxial thin film. The temperature change effect and optical properties of solar sail degradation are considered as well. Solar sail flight from Earth to Mercury is designed as a simulation of the flight change in optical parameters.