Application of a PCA-DBN-based surrogate model to robust aerodynamic design optimization

An efficient method employing a Principal Component Analysis (PCA)-Deep Belief Network (DBN)-based surrogate model is developed for robust aerodynamic design optimization in this study. In order to reduce the number of design variables for aerodynamic optimizations, the PCA technique is implemented to the geometric parameters obtained by parameterization method. For the purpose of predicting aerodynamic parameters, the DBN model is established with the reduced design variables as input and the aerodynamic parameters as output, and it is trained using the k-step contrastive divergence algorithm. The established PCA-DBN-based surrogate model is validated through predicting lift-to-drag ratios of a set of airfoils, and the results indicate that the PCA-DBN-based surrogate model is reliable and obtains more accurate predictions than three other surrogate models. Then the efficient optimization method is established by embedding the PCA-DBN-based surrogate model into an improved Particle Swarm Optimization (PSO) framework, and applied to the robust aerodynamic design optimizations of Natural Laminar Flow (NLF) airfoil and transonic wing. The optimization results indicate that the PCA-DBN-based surrogate model works very well as a prediction model in the robust optimization processes of both NLF airfoil and transonic wing. By employing the PCA-DBN-based surrogate model, the developed efficient method improves the optimization efficiency obviously.     

Passive localization by a single moving observer using TOA only with unknown SRI: Observability analysis and algorithm

Passive localization by a single moving observer using Time of Arrival (TOA) only with an unknown Signal Repetition Interval (SRI) is investigated in this paper. Observability analysis is performed first. The observability condition for uniquely determining the emitter position and SRI is derived. The conditional Cramer-Rao Lower Bound (CRLB) is also analyzed. It is found that the ambiguity of the SRI integer of the first TOA does not affect the theoretical estimation precision of the emitter position and SRI. A Reference-Fixed Differential TOA (RFDTOA)-based Iterative Maximum Likelihood Estimator (IMLE) is proposed, which only needs O(M) computational operations. Theoretical analysis and simulation results show that the Mean Square Error (MSE) of the proposed algorithm could attain the CRLB with moderate Gaussian measurement noise.     

利用GPS进行姿态估计的一种算法

首先建立了全球定位系统（ＧＰＳ）姿态确定的观测方程;然后给出了利用ＧＰＳ进行飞行器姿态估计的模型,并对该模型进行了线性处理;最后利用攻推广卡尔曼滤波技术,针对某飞行器进行了仿真计算。计算结果表明,对于不同的测量噪声和系统噪声,滤波器都有较好的估计,姿态估计的精度明显高于单纯ＧＰＳ姿态确定的精度,可以满足大多数飞行器对姿态确定的要求,证实了模型和算法可用性。     

半个太阳活动周期内我国中纬地区上空电离层等效板厚的变化特征

本文用新乡(电离层400km对下点是:32.4°N,115.6°E)、重庆(电离层400km对下点是:27.2°N,108.7°E)接收日本同步卫星ETS-Ⅱ的信标资料,研究了我国中纬地区上空半个太阳活动周期内(1981—1985)电离层等效板厚的变化特征,得到了等效板厚日变化、季变化的二维和三维等值图。由付里叶分析和回归方法得出等效板厚日变化各谐波分量与太阳黑子数12个月滑动平均值之间存在弱的线性关系。同时指出在等效板厚日变化中,于当地时0400—0700LT存在一明显的黎明峰。并对出现这种峰的原因作了讨论。      

某发动机涡轮故障叶片共振相干分析与可靠性评估

分析了某发动机二级涡轮叶片的振动特性、振型应力,共振特性;并结合内外场大量的频率统计数据进行了共振相干分析,分析了叶片故障原因,并提出采用限频、调频等排故措施。      

Levy 方法的改进

由于Levy方法简化了指标函数,并采用经典的最小二乘法,用于估计系统传递函数的参数,受实验数据误差影响大。基于Levy方法但保持原来的指标函数,提出一种改进的增量迭代算法和正交最小二乘法,仿真结果表明,该算法具有良好的收敛性,并使系统参数估计精度较Levy方法有明显的提高。     

基于神经网络的自适应状态观测器

利用ＢＰ神经网络动态系统对一类非线性时变系统的状态进行了估计。利用神经网络的“学习－遗忘”特性,提出了非线性时变系统的自适应状态观测器,对其结构及特性进行了讨论。仿真结果表明这种自适应状态观测器能跟踪系统参数及状态的变化。     

实数域中的投影法及其在单次快摄阵处理中的应用

阵列处理中计算简单的投影法避免了矩阵特征分解(ＥＶＤ)的庞大计算量,然而仍需进行复数计算。为了进一步减小计算量,提出一种实数域中的投影法,它将投影矩阵及空间谱的计算均简化为实数的计算,从而。使阵处理的计算量大大减少,而且使估计性能保持不变。计算机模拟与实际外场实验数据的计算结果表明了算法的有效性。     

一种基于贝叶斯估计的高分辨目标定向新方法

提出一种高分辨方位估计新方法。它是建立在阵列输出信号和噪声参数联合后验概率密度基础上的空间谱估计。仿真结果表明,该方法具有以下几个显著的优点：①极高的空间分辨率和估计精度;②可解相干源;③低信噪比、少快拍数的情况下很有潜力;④可以估计不同方向目标源的能量;⑤具有较好的工程应用前景。该方法和ＭＵＳＩＣ方法的性能进行了比较并给出计算机仿真结果。     

一种手持设备的条形码技术

主要讨论条形码（BARCODE）技术中的解码技术,文中详细地讲述了条形码解码过程中可能出现的问题以及解决的方法、解码系统的识别性能问题,最后列出了一个条形码解码的具体算法。