一种用于分散化滤波的融合算法及其在组合导航系统中的应用

提出了一种局部估计相关时的最优融合算法，其特点是加权矩阵是对角阵，即全局估计中的各分量分别是局部估计中相应分量的线性组合，在此融合算法中局部估计是最优的，并且不存在由主滤波器向子滤波器的信息反馈，因此具有较好的客措性。给出了最优加权矩阵的存在性和唯一性的证明，并通过与现有类似融合算法的对比，表明该算法具有计算量小的优点。最后，以组合导航系统为例作了仿真计算，结果表明该融合算法是可行的。     

神经网络算法及其在GPS导航中的应用

GPS导航解算中常采用最小二乘算法。由于导航解算中存在观测异常（粗差），采用的模型精度很难满足用户需求，而高动态用户需求的精度却不断提高，为此文中提出一种利用神经网络的非线性逼近能力，在顾及观测信息权阵的条件下，利用Hopfieid神经网络进行GPS导航解算的新算法。该算法具有很好的抗差性和自适应性，能较好地抑制观测粗差对导航解的影响。计算结果证明了该算法的有效性。     

INS/ESGM组合导航系统的多模型自适应滤波技术研究

研究了一种随机系统多模型自适应估计的方法，并将此方法应用于INS／ESGM组合导航系统。通过数字仿真将单一模型的INS／ESGM组合导航系统与多模型的INS／ESGM组合导航系统的性能进行了详细比较，说明将多模型自适应估计理论应用于INS／ESGM组合导航系统，可增强系统对环境的适用性，大大提高组合导航系统的精度。     

计算机模拟升降法试验的研究

介绍了计算机模拟感度试验的原理，运用计算机模拟方法研究了升降法试验的初始参数选择对感度分布参数估计精度的影响，取得了对升降法有利的试验条件。     

用有限元自适网格控制结构应力分析的精度

本文涉及有限元结构应务分析精度控制的三个基本方面：１）自适应的有限元网格自动生成技术；２）有限元应力分析的误差估计：３）用单元尺寸场将误差分布用于形成新网格。     

Application of a kinematic hardening viscoplasticity model with thresholds to the residual stress relaxation

The life analysis of engine components needs to take into account the residual stress relaxation induced by cyclic service loads. The paper recalls a new class of constitutive equations for cyclic viscoplasticity, using a series of kinematic hardening models with thresholds. The equations are introduced within a recently enlarged thermodynamic framework. Some attention is focused to the relations with multisurface approaches and to a specific determination procedure of the model parameters. The new model is applied to the calculation of the near surface residual stress relaxation after shot peening, when the structure is submitted to cyclic service loads. The simulated stabilized residual stresses are in good accordance with experimental results obtained on an N18 disk alloy at 650°C. In comparison, the classical model without threshold predicts the complete vanishing of the residual stresses, which is not satisfactory.     

抗磨可靠性寿命的加速试验与预测

在工程实际中，对新机器零件的抗磨可靠性寿命进行评估或预测非常重要，但是，由于磨损是一种受多因素制约的随机过程，目前在实验室广泛采用的模拟磨损试验，不仅周期较长，而且预测误差也比较大。因此，提出了一种在保持磨损机相似的前提下合理选用高ＰＶ值的抗磨可靠性寿命加速试验的新方法。     

Selecting an Effective Entropy Estimator for Short Sequences of Bits and Bytes with Maximum Entropy

Entropy makes it possible to measure the uncertainty about an information source from the distribution of its output symbols. It is known that the maximum Shannon’s entropy of a discrete source of information is reached when its symbols follow a Uniform distribution. In cryptography, these sources have great applications since they allow for the highest security standards to be reached. In this work, the most effective estimator is selected to estimate entropy in short samples of bytes and bits with maximum entropy. For this, 18 estimators were compared. Results concerning the comparisons published in the literature between these estimators are discussed. The most suitable estimator is determined experimentally, based on its bias, the mean square error short samples of bytes and bits.     

Blind parameter estimation of pseudo-random binary code-linear frequency modulation signal based on Duffing oscillator at low SNR

Conventional parameter estimation methods for pseudo-random binary code-linear frequency modulation(PRBCLFM) signals require prior knowledge, are computationally complex, and exhibit poor performance at low signal-to-noise ratios(SNRs). To overcome these problems, a blind parameter estimation method based on a Duffing oscillator array is proposed. A new relationship formula among the state of the Duffing oscillator, the pseudo-random sequence of the PRBC-LFM signal, and the frequency difference between the PRBC-LFM signal and the periodic driving force signal of the Duffing oscillator is derived, providing the theoretical basis for blind parameter estimation. Methods based on amplitude method, short-time Fourier transform method, and power spectrum entropy method are used to binarize the output of the Duffing oscillator array, and their performance is compared. The pseudo-random sequence is estimated using Duffing oscillator array synchronization, and the carrier frequency parameters are obtained by the relational expressions and characteristics of the difference frequency. Simulation results show that this blind estimation method overcomes limitations in prior knowledge and maintains good parameter estimation performance up to an SNR of-35 d B.