Evaluation of Characteristics of Non-Metallic Inclusions in P/M Ni-Base Superalloy by Automatic Image Analysis

Non-metallic inclusions,especially the large ones,within P/M Ni-base superalloy have a major influence on fatigue characteristics,but are not directly measurable by routine inspection.In this paper,a method,automatic image analysis,is proposed for estimation of the content,size and amount of non-metallic inclusions in superalloy.The methodology for the practical application of this method is described and the factors affecting the precision of the estimation are discussed.In the experiment,the characteristics of the non-metallic inclusions in Ni-base P/M superalloy are analyzed.     

Navigation Accuracy Category-Position Models and Estimate Position Uncertainty Calculations for TIS-B System

Navigation accuracy category-position (NACp) is an important parameter for system accuracy of traffic information service-broadcast (TIS-B), which is determined by estimate position uncertainty (EPU). Centered about the problems that the existing EPU calculation based on noise measurement is low in accuracy and unfit for describing uncorrected biases in target reports, this article analyses the traditional NACp model, and uses the least square estimation (LSE) in EPU calculation. Furthermore, it proposes an extended NACp model, which considers both noise and biases and acquires EPU estimation with the help of approximate multiplex Taylor expression. Analysis and simulation show that the proposed method not only leads to significant improvement of the accuracy of EPU calculation, but is fit for EPU calculation with tracking biases in TIS-B system as well. As such it can find application in practice to depict different kinds of error models in TIS-B system.     

虹桥机场近距平行跑道仪表运行方式研究

针对虹桥机场近距平行跑道,以实现跑道系统最大容量为目标,综合考虑两个航站楼的布局情况,依据民航局有关运行规则,系统研究近距平行跑道的仪表运行方式,分析不同跑道运行方式下航站楼航班流量分布比例与近距平行跑道理论容量之间的函数关系,提出具有实际可操作性且适合虹桥机场近距平行跑道的最佳运行方式。     

地磁测量数据野值的辨识与剔除

针对地磁测量野值的辨识与剔除方法进行了深入研究。分析了野值辨识与剔除的基本原理,基于孤立型野值和斑点型野值模型分析比较了不同的野值剔除方法。利用地磁场实测信息,优化了野值剔除方法的参数,并从不同角度验证了方法的野值修复效果。仿真结果表明,在观测信息为总强度地磁信息条件下,优化的最小二乘B样条逼近法能够有效地辨识野值,具有较好的野值修复效果。     

机载设备外场数据的可靠性增长分析

对我国航空机载设备外场数据的性质进行分析后,提出该种数据是变动母体混合数据,不同于通常用于可靠性估计的不变母体数据。提出外场数据中含有可靠性增长信息。 为利用外场数据来分析和评估航空机载设备的可靠性增长和可靠性状态,提出一个数学模型。模型的基本原理是最小二乘法。为说明模型的使用提供了一个实例。     

Fast approximate maximum likelihood period estimation from incomplete timing data

 To estimate the period of a periodic point process from noisy and incomplete observations, the classical periodogram algorithm is modified. The original periodogram algorithm yields an estimate by performing grid search of the peak of a spectrum, which is equivalent to the periodogram of the periodic point process, thus its performance is found to be sensitive to the chosen grid spacing. This paper derives a novel grid spacing formula, after finding a lower bound of the width of the spectral mainlobe. By employing this formula, the proposed new estimator can determine an appropriate grid spacing adaptively, and is able to yield approximate maximum likelihood estimate (MLE) with a computational complexity of O(n²). Experimental results prove that the proposed estimator can achieve better trade-off between statistical accuracy and complexity, as compared to existing methods. Simulations also show that the derived grid spacing formula is also applicable to other estimators that operate similarly by grid search.     

Bayesian edge detector for SAR imagery using discontinuity-adaptive Markov random feld modeling

Synthetic aperture radar（SAR）image is severely affected by multiplicative speckle noise,which greatly complicates the edge detection.In this paper,by incorporating the discontinuityadaptive Markov random feld（DAMRF）and maximum a posteriori（MAP）estimation criterion into edge detection,a Bayesian edge detector for SAR imagery is accordingly developed.In the proposed detector,the DAMRF is used as the a priori distribution of the local mean reflectivity,and a maximum a posteriori estimation of it is thus obtained by maximizing the posteriori energy using gradient-descent method.Four normalized ratios constructed in different directions are computed,based on which two edge strength maps（ESMs）are formed.The fnal edge detection result is achieved by fusing the results of two thresholded ESMs.The experimental results with synthetic and real SAR images show that the proposed detector could effciently detect edges in SAR images,and achieve better performance than two popular detectors in terms of Pratt＇s fgure of merit and visual evaluation in most cases.     

基于GPR模型的自适应平方根容积卡尔曼滤波算法

与传统算法一样,动态系统的参数化模型(含噪声统计特性)未知或不够准确易导致容积卡尔曼滤波(CKF)效果严重下降,甚至滤波结果发散.为此,利用高斯过程回归(GPR)方法对训练数据进行学习,得到动态系统的状态转移GPR模型和量测GPR模型以及噪声统计特性,用以替代或增强原有动态系统模型,并将其融入到平方根容积卡尔曼滤波(SRCKF)中,分别提出了无模型高斯过程SRCKF (MFGP-SRCKF)和模型增强高斯过程SRCKF (MEGP-SRCKF)两种算法.仿真结果表明:这两种新的自适应滤波算法提高了动态系统模型精度,且实时自适应调整噪声的协方差,克服了传统算法滤波性能易受系统模型限制的问题;与MFGP-SRCKF相比,在给定一个不够准确的参数化模型,且有限的训练数据未能遍布估计状态空间的情况下,MEGP-SRCKF具备更高的滤波精度.     

FrFT-CSWSF:Estimating cross-range velocities of ground moving targets using multistatic synthetic aperture radar

Estimating cross-range velocity is a challenging task for space-borne synthetic aperture radar（SAR）, which is important for ground moving target indication（GMTI）. Because the velocity of a target is very small compared with that of the satellite, it is difficult to correctly estimate it using a conventional monostatic platform algorithm. To overcome this problem, a novel method employing multistatic SAR is presented in this letter. The proposed hybrid method, which is based on an extended space-time model（ESTIM） of the azimuth signal, has two steps： first, a set of finite impulse response（FIR） filter banks based on a fractional Fourier transform（FrFT） is used to separate multiple targets within a range gate; second, a cross-correlation spectrum weighted subspace fitting（CSWSF） algorithm is applied to each of the separated signals in order to estimate their respective parameters. As verified through computer simulation with the constellations of Cartwheel, Pendulum and Helix, this proposed time-frequency-subspace method effectively improves the estimation precision of the cross-range velocities of multiple targets.     

Model-based robust estimation and fault detection for MEMS-INS/GPS integrated navigation systems

In micro-electro-mechanical system based inertial navigation system（MEMS-INS）/global position system（GPS） integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust estimation（RE） and fault detection（FD）. A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing priori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range; with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of disturbances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.