A fast satellite selection algorithm with floating high cut-off elevation angle based on ADOP for instantaneous multi-GNSS single-frequency relative positioning

With the Global Navigation Satellite System (GNSS) developing, the single-frequency single-epoch multiple GNSSs (multi-GNSS) relative positioning has become feasible. Since a larger number of the observed satellites make the instantaneous (single-epoch) positioning time-consuming, a proper satellite selection is necessary. Among the present methods, the satellite selection with a fixed high cut-off elevation angle (CEA) is least time-consuming. However, there is no criterion how large a fixed high CEA should be to achieve a high success rate and less time consumption. Besides, a fixed high CEA makes the number of visible satellites largely variable, which affects the success rate. Hence, a satellite selection strategy based on ambiguity dilution of precision (ADOP) is proposed. Firstly, the theoretical proof that the ADOP increases the least when removing satellites are all low-elevation-angle satellites is given, which is important to achieve the fast positioning with a high success rate. Then, the threshold $\beta$ is calculated for a different number of satellites and a given ADOP. The satellites are selected based on their elevation angles from high to low until $\beta$ of the selected satellites becomes smaller than the corresponding threshold; this method is called the extended floating CEA multi-GNSS (EF-multi-GNSS). The comparison of the single-frequency single-epoch positioning performance of the EF-multi-GNSS with the satellite selections based on a fixed low CEA (L-multi-GNSS) and a fixed high CEA (H-multi-GNSS) via the relative positioning experiments shows that: (1) the EF-multi-GNSS with a minimal number of satellites can achieve the fast positioning and a high success rate close to 100%. It can greatly reduce the time consumption of the L-multi-GNSS, by about 64.0%, by selecting 12.6 satellites of 23.4 satellites; (2) the floating CEA of EF-multi-GNSS eliminates the consideration how large a fixed high CEA should be, and a CEA larger than the fixed high CEA of the H-multi-GNSS makes it more suitable for different conditions.     

基于主题模型的结构化Web服务发现机制

提出了基于主题模型(topic model)的结构化Web服务发现机制.利用LDA(Latent Dirichlet Allocation)生成概率模型,将Web服务(Web service)建模为结构化文本文档.一个文档视作主题的概率分布,主题又由关键词的概率分布组成,从而提供基于主题的Web服务检索.同时,利用Web服务的结构化特性,将Web服务描述文档表示为有向无环图,利用n阶谱核测量Web服务文档的相似度,实现Web服务结构化信息的发现.通过实验分析对比,基于主题模型的结构化Web服务发现机制有效提高了Web服务发现的效率和精确率.      

开源软件定制改造过程中的原型选择

在定制改造开发过程中选择合适的原型系统,可以达到提高定制改造过程效率、减少开发成本、缩短开发周期的目的.在定制改造过程的原型分析和评估中依托构造成本模型COCOMO(COstructive COst MOdel) II,提出一种新的软件成本评估方法,综合分析了影响定制改造过程的功能差异、性能、规模、稳定性等关键因素,量化了这些关键因素对定制改造过程中成本计算公式中的关键变量——等价代码——的影响.实际的项目显示,该方法对预期工作量的估计误差约为17%,远小于COCOMO II模型40%的可接受阈值.      

飞机总体设计优化中的多目标方案优选方法

飞机概念设计多目标优化的结果基本决定了飞机的总体外形。为提高多目标优化结果解集的优选效率,在多目标方案对比评价方法和可视化辅助评价支持两方面对飞机多目标方案优选方法进行了研究。首先在研究了线性加权和法及欧氏加权距离法的基础上,提出了体现具体目标对比的基于等效多边形的等效面积评价法,并进行了改进。其次,采用量化指标初选与可视化目标对比及方案模型可视化精选相结合的方式,在概念设计平台上实现了多目标方案优选方法。最后在轻型战斗机概念方案多目标优化实例中利用提出的优选方法对优化非劣解集进行了优选,结果验证了可视化辅助评价支持的优选方法方便快速获取满意方案的有效性。     

Sensor Optimization Selection Model Based on Testability Constraint

Sensor selection and optimization is one of the important parts in design for testability. To address the problems that the traditional sensor optimization selection model does not take the requirements of prognostics and health management especially fault prognostics for testability into account and does not consider the impacts of sensor actual attributes on fault detectability, a novel sensor optimization selection model is proposed. Firstly, a universal architecture for sensor selection and optimization is provided. Secondly, a new testability index named fault predictable rate is defined to describe fault prognostics requirements for testability. Thirdly, a sensor selection and optimization model for prognostics and health management is constructed, which takes sensor cost as objective function and the defined testability indexes as constraint conditions. Due to NP-hard property of the model, a generic algorithm is designed to obtain the optimal solution. At last, a case study is presented to demonstrate the sensor selection approach for a stable tracking servo platform. The application results and comparison analysis show the proposed model and algorithm are effective and feasible. This approach can be used to select sensors for prognostics and health management of any system.     

基于Hausdorff距离的反舰导弹目标选择方法

如何从舰艇编队中选择预定目标,是超视距反舰导弹亟待解决的一个问题。文章基于Hausdorff距离的部分匹配理论研究了这一问题。火控雷达探测到的编队信息和末制导雷达探测到的编队信息都用点集来描述,通过点集形状匹配获取这两个点集的对应点,从而实现对预定目标的选择。重点提出了一种新的部分匹配途径,能够自适应地逐个剔除引起形状不相似的外部点而同时保留两个形状的相似部分。仿真试验表明,相比以往基于编队相互位置关系的方法,论文所研究的预定目标选择方法具有更好的抗干扰能力。     

基于图像的着陆点评估及探测器运动估计方法

针对深空探测任务特点给出了一种基于导航图像的探测器着陆点选择与探测器运 动估计技术。考虑到在着陆初始阶段(探测器高度＞2 km)导航相机所拍摄到的天体表面 近似为平面。这里通过跟踪至少4个平面内的特征点在导航图像序列 中的位置, 利用最小二乘法计算单应矩阵,由该矩阵得到探测器部分相对运动参数。结合激光测距仪给 出的探测器与天体表面之间的距离信息,可以得到全部6自由度参数。安全着陆点的选择与 评估首先利用图像灰度预选出平整的着陆点,再由着陆点对应的单应矩阵和之前获得的帧间 相对运动验证着陆点坡度。蒙特卡洛仿真结果表明,着陆点评估算法能够有效地选取满足平 整和坡度要求的着陆点,运动估计算法实时地对探测器参数进行估计,平移估计相对误 差小于10％,旋转估计误差小于0.23°。
     

基于混合优化算法的固液发动机装药优化设计

为了减小固液发动机工作过程中氧燃比的变化导致的比冲等性能损失,提出基于差分进化和克隆选择的混合优化算法,建立装药优化问题的优化模型和优化流程,采用惩罚函数处理约束条件,对某型固液发动机进行了装药优化和分析.结果表明该优化算法和流程性能良好,优化后发动机的性能得到了明显提高,减小了余药质量分数和工作压强,改善了燃烧室和喷管的工作环境,且平均比冲提高了1.2%.      

反舰导弹对目标选择的一种新方法

超视距反舰导弹(ASM)在搜索阶段选择预定目标时,目前采用的瞄准点选择方法受自控终点的散布误差和目标机动影响较大。为此提出一种利用舰艇编队相互位置关系(MPR)选择预定目标的方法。编队相互位置关系即其余目标相对参考目标的位置,对于一个编队,选择不同的参考目标得到不同的编队相互位置关系。对发射前装订的编队,以预定目标为参考目标获得其编队相互位置关系,在末制导雷达探测到的编队目标中,若以某目标为参考目标时的编队相互位置关系与之最相似,则该目标即为所要选择的预定目标。该方法不受自控终点散布误差和编队目标整体机动的影响。仿真实验表明该方法正确选择预定目标的概率高于瞄准点选择方法。     

基于单因素SVM的航空兵空运转场飞行架次需求预测研究

航空兵部队成建制空运转场飞行架次需求预测,对机关、航空兵部队拟定空运计划、进行空运准备等都具有重要的意义。运用序列后向选择方法(SBS)对影响飞行架次的特征因素进行逐层淘汰,利用支持向量机(SVM)理论建立单因素非线性回归模型,进而对飞行架次进行预测。预测结果表明:同多因素SVM预测模型相比,单因素SVM预测模型虽在预测精度上没有显著提高,但其减少了预测的前期工作量,方便了机关和部队的使用,实现了飞行架次预测的实时性要求。