车载GPS/DR组合导航系统的信息融合新方案

总结了适用于车载 GPS/ DR组合导航系统的几种信息融合方法 ,提出一种可容错的新型联合卡尔曼滤波结构方案。针对系统重构和自适应调整的依据 ,提出一种新的分系统状态评估方法 ,定义了滤波器估计结果可信度的概念并给出对其进行模糊综合评判的方法。在此基础上进一步确定联合滤波模型的自适应信息分配准则 ,实时跑车数据处理结果表明 ,该方案大大提高了系统的导航精度和可靠性     

基于快速终端滑模的模糊逼近系统及其应用

为改善模糊系统逼近的收敛速率,提出了一种基于快速终端滑模的反向传播(BP)学习算法。将快速终端滑模引入模糊逻系统的学习算法,综合终端吸引子有限时间收敛和线性系统指数收敛的性质,提高了对非线性连续函数的逼近能力。仿真结果表明:该算法能以较快速率逼近未知函数,且逼近过程稳定,较普通学习算法更为精确和有效。     

基于SPWD多载波频率估计算法的改进

针对目前提出的多载波估计算法存在的速度与精度的问题,基于模糊控制理论,改进和完善了多载波信号载频估计算法.通过对多载波时隙ALOHA网络真实卫星信号的载频频点提取,验证了该改进算法的时效性.     

应用模糊变权的启发式搜索进行飞行轨迹优化

回顾了军机轨迹优化问题的提出及研究历史，介绍了几种主要方法的特点，特别是启发式搜索算法应用于飞行轨迹优化问题时存在的主要问题。提出为了得到较好的近优路径而采取的模糊变权处理方法。通过计算不同加权下解的情况，说明模糊变权方法是使加权随具体情况作相应调整的有效手段，为提高飞行路径规划系统的有效性开辟了一个新思路。     

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.     

Training effectiveness evaluation of helicopter emergency relief based on virtual simulation

Helicopters are playing an increasingly important part in emergency relief, such as earthquake rescue, firefighting and medical transport. With the development of virtual simulation technology, virtual simulation-based training is widely used in the training of the helicopter crew especially for the dangerous and costly missions mentioned above. A complete training effectiveness evaluation method is proposed to evaluate the trainees’ training effect based on virtual simulation in this paper. A key to this method is regarding the complicated process as a discrete event-activity flow system and establishing the evaluation indicator system. Then expert group and Analytical Network Process (ANP) are applied to determine the weight of indicators. When the training data are processed, there is a novel attempt to apply Fuzzy Comprehensive Evaluation (FCE) model to calculate the two categories of indicators. Eventually, an experiment and the analysis were carried out to validate the evaluation method.     

一种快速的飞行器布局方案优选方法

本文引用系统模糊优选理论与基于数理统计正交表的设计法相结合来处理飞行器布局方案优选问题，并举例说明具体用法，文中方法对整个飞行器方案选择有一定参考价值。     

航天航空中急性缺氧条件下功效改变的研究

受试者为84名男性青年和实验工作人员,在低压舱1500、2500、3000、4000、5000和6000米高度上停留60分钟。每次实验一个高度,总共133人次。实验中,记录了数字记忆、听觉警觉和跟踪操作等多项功效指标。应用统计和模型方法对结果进行了分析,并试用模糊集理论对五种基本功效进行综合评定,得到了急性缺氧下功效改变有意义的结果。这些结果可为飞行员执行飞行任务,航天员在船舱内或穿着航天服在舱外执行任务及制订医学保证方案提供了科学依据。     

涡轮泵转子工作转速的模糊可靠性确定方法及其应用

针对涡轮泵转子共振失效的特点,分析了转子工作状态超界的隶属函数,详细讨论了隶属函数中有关参数的确定方法,建立了转子工作转速模糊可靠性计算模型,推导出工作转速的计算公式,并与常规的工作转速确定法进行了比较。     

模糊传感器与区间型多属性决策的信息融合方法

对于日益复杂的信息环境和变化的目标特性,现有的多传感器信息融合方法大多为"静态的",较少考虑传感器可信度变化以及测量过程中的多维特征指标权重的时效性给融合结果带来的影响.为了解决此问题,提出了一种基于模糊理论与区间型多属性决策的信息融合方法.该方法从各传感器对模糊命题支持度的一致性来定义其信息质最优化度,用区间数与多属性决策理论来定义特征识别综合置信度,并从这两方面客观确定了传感器的融合权重,较好地解决了对传感器信息与目标特征权重为模糊与不确定时的合理评价,以此构建了一个智能优化决策层融合识别模型.最后以弹道目标识别实验证明了此方法有较好的时效性和准确性.