舰载机智能复飞决策技术研究

为了进一步改进复飞技术,针对复飞环境,提出了一种在原军用推力操纵的基础上,加入具有保持迎角恒定的升降舵模糊控制的复飞系统,从而有效地增强了低动压状态下飞机的机动能力。给出了复飞决策准则,设计了基于模糊控制的复飞决策系统,并对具有该复飞决策系统的舰载机自动着舰导引系统进行了仿真验证。结果表明,该复飞决策系统明显地缩小了复飞边界区,大大提高了着舰和复飞的安全性,可实现自动复飞,减轻了飞行员的负担。     

基于PIC＋FPGA飞机直流供电系统设备故障预测研究

针对飞机直流供电系统中直流设备工作情况，本文利用FPGA双进程有限状态机方法控制A／D转换器，快速准确采样多路信号。用模糊理论的建议语言规则，结合PIC单片机的控制优势，从而解决飞机直流供电系统设备故障预测报警。     

基于伪随机序列调制的混合域自适应盲水印算法

在多小波变换和DCT变换混合变换域中，提出了一种基于伪随机序列调制的彩色图像盲水印算法。该算法先将原始彩色图像由RGB空间转换到YIQ空间．选取Y分量多小波变换后的中频区域作为水印的嵌入区域。水印嵌入前先对待嵌入水印区域8×8分块，然后对所有子块按照纹理和能量特征进行模糊分类，最后将置乱后的二值水印信息用两个互不相关的伪随机序列进行扩频调制．嵌入到8×8子块DCT变换后的交流系数上。提取水印时，通过比较两个伪随机数列和待检测系数相关性的大小来提取水印，不需要原始图像参与。实验表明，该算法对噪声、JPEG压缩和几何剪切等常见的攻击操作具有很强的鲁棒性。     

Geomagnetic activity associated with magnetic clouds,magnetic cloud-like structures and interplanetary shocks for the period 1995–2003

Using nine years (1995–2003) of solar wind plasma and magnetic field data, solar sunspot number, and geomagnetic activity data, we investigated the geomagnetic activity associated with magnetic clouds (MCs), magnetic cloud-like structures (MCLs), and interplanetary shock waves. Eighty-two MCs and one hundred and twenty-two MCLs were identified by using solar wind and magnetic field data from the WIND mission, and two hundred and sixty-one interplanetary shocks were identified over the period of 1995–2003 in the vicinity of Earth. It is found that MCs are typically more geoeffective than MCLs or interplanetary shocks. The occurrence frequency of MCs is not well correlated with sunspot number. By contrast, both occurrence frequency of MCLs and sudden storm commencements (SSCs) are well correlated with sunspot number.     

风扇进口噪声预测模型的改进

针对Heidmann模型对风扇进口低频噪声(1k Hz)预测结果偏低的情况,通过引入风扇叶尖弦长雷诺数和相关几何参数改进了Heidmann模型中风扇进口宽频噪声的频谱修正函数,确定了其中频谱修正系数为0.085。对比改进模型和Heidmann模型的风扇进口噪声预测结果发现:在亚声速工况下,改进的模型很好地改善了风扇进口低频噪声的预测结果,改进幅值可以达到约45d B;而在超声速工况下,由于风扇进口产生的组合单音噪声成为风扇进口噪声的主要组成部分,除了在小于100Hz的频域内,改进的模型与Heidmann模型的预测结果差别不大。     

基于模糊机会约束规划的机会阵雷达方向图综合

针对机会阵雷达方向图综合的不确定问题,提出了一种基于模糊机会约束规划的方向图综合规划模型。该模型基于可信性理论,综合考虑天线单元分布的随机性以及激励状态的不确定性,将参与方向图综合时激励打开的天线数目看做一个梯形模糊变量,用以描述综合时的复杂不确定环境。随后,将规划模型转化为清晰等价形式,再结合遗传算法和灰关联综合评价法则设计了一种混合智能优化算法,用于求解该模型。以一维任意非均匀线阵为例,对主瓣宽度和最大副瓣电平进行了优化。仿真表明:优化后结果的可信性高于置信水平,验证了该算法的有效性。     

基于一致关联数最大化的航迹关联算法

航迹关联(TTTA)是多传感器数据融合系统的核心模块之一,是系统误差估计和航迹融合的前提和基础。传感器存在的固有系统误差使得目标位置状态估计与真值发生偏离,容易诱发TTTA错误。传统的基于全局最小距离准则的TTTA算法,需要获得较高精度的系统误差估计,来对航迹数据进行误差补偿。针对传感器具有系统误差环境下的TTTA问题,在对TTTA进行间接评估的基础上,定义了一致关联数的概念,提出了一致关联数最大化的TTTA准则,并在稳健交替迭代的框架下完成算法设计。与距离函数不同,一致关联数是一个离散量,放松了对系统误差估计精度的要求。最后,仿真实验验证了所提算法的有效性。     

A salient edges detection algorithm of multi-sensor images and its rapid calculation based on PFCM kernel clustering

Multi-sensor image matching based on salient edges has broad prospect in applications, but it is difficult to extract salient edges of real multi-sensor images with noises fast and accurately by using common algorithms. According to the analysis of the features of salient edges, a novel salient edges detection algorithm and its rapid calculation are proposed based on possibility fuzzy C-means （PFCM） kernel clustering using two-dimensional vectors composed of the values of gray and texture. PFCM clustering can overcome the shortcomings that fuzzy C-means （FCM） cluster- ing is sensitive to noises and possibility C-means （PCM） clustering tends to find identical clusters. On this basis, a method is proposed to improve real-time performance by compressing data sets based on the idea of data reduction in the field of mathematical analysis. In addition, the idea that kernel-space is linearly separable is used to enhance robustness further. Experimental results show that this method extracts salient edges for real multi-sensor images with noises more accurately than the algorithm based on force fields and the FCM algorithm; and the proposed method is on average about 56 times faster than the PFCM algorithm in real time and has better robustness.     

大面积航班延误的实时航班延误程度评估研究

为对大面积航班的延误程度进行实时评估,根据航班延误的时空分布特点,从延误时间和延误范围两个角度给出评估指标,建立了航班延误程度实时评估指标体系。采用层次分析法得到各个指标的权重,并在此基础上给出了基于模糊综合评价的航班延误程度实时评估模型。实例的计算结果表明建立的评估模型是可行的。