利用局部评估的分布式图模式匹配算法

为了在分布式存储的大规模数据图上进行快速图模式匹配,提出利用局部评估的分布式图模式匹配算法。各计算节点并行地执行本地匹配;协调器节点收集局部匹配结果、计算边界点的匹配状态并发送给相应的计算节点;计算节点根据边界点的匹配状态确定与边界点相连的节点的匹配情况;协调器节点组合得出最大匹配集。实验结果表明:与已有的分布式图模式匹配算法相比,dis GPM-PE算法都能够在不显著增加通信量的前提下避免数据片段间的依赖关系对执行时间的影响,从而减少图模式匹配的时间。     

基于高精度景象匹配的SAR平台定位方法

提出一种利用SAR图像与光学基准图高精度匹配实现SAR平台定位的方法。利用成像中间时刻SAR平台与SAR图像中心线上物点在水平面的投影共线的特性,在图像中心线上均匀选取若干点作为匹配点,并与光学基准图进行高精度景象匹配获取它们的物点坐标;根据这些物点坐标估计出图像中心线在当地水平面投影的直线方程;利用直线信息和斜距高度信息计算SAR平台在水平面上的投影点位置,进而计算得到成像中间时刻SAR平台的空间位置。为了进一步提高匹配精度,分别提出对正侧视和斜视SAR图像匹配区域进行几何粗校正的方法。还分析了不同误差因素对平台定位精度的影响,并给出精度估计公式。仿真和实际图像实验结果表明,方法正确可行,具有较高的定位精度,具备工程实用价值。     

钢球侵彻不同靶标的相似性分析

为研究相同弹丸侵彻不同靶标所造成损伤之间的相似性,以钢球侵彻明胶造成的瞬时空腔的最大直径为研究对象,基于相似理论推导出瞬时空腔最大直径的相似准则方程,利用钢球侵彻明胶的实验数据求解出准则方程的系数和指数,最后通过钢球侵彻猪后腿实验验证了所得到的准则方程可用于不同靶标之间的相似性分析,并具有准确性和合理性。     

效力准则的电子战干扰效果度量的研究

探讨了舰载电子战系统干扰效果的度量准则,分析了压制干扰对反舰导弹的单发命中概率的影响,从研究系统射击效力指标的角度出发,提出一种新的评定舰载电子战干扰效果的准则——效力准则。并通过算例得出典型情况下系统施放压制性干扰时机与反舰导弹单发命中概率之间的关系。     

雷达定时脉冲近距离传输的分析与电路设计

通过分析比较多种时间同步技术,对与雷达距离上百米的系统,采用有线传输雷达定时脉冲信号的方式来实现快速的时间同步。针对雷达脉冲信号边沿跳变迅速,在传输过程中存在延时、反射和畸变等问题,借助Cadence仿真软件对信号传输过程进行了仿真分析,设计了合理的传输电路。实验证明本方案结构简单,抗干扰能力强,同步时间可以达到亚微秒级,在雷达信号检测模拟器、雷达诱饵和雷达组网中都有着重要应用。     

多喷嘴超声速引射器压力匹配性能试验研究

建立了多喷嘴超声速引射器试验台,采用燃气作为一、二次流驱动工质对多喷嘴超声速引射器进行了试验研究,重点考察了引射器的压力匹配问题。试验结果表明:一次流总压越低,引射喷嘴出口压力越低,与二次流压力匹配越容易;二次流总压越低,保持压力匹配对引射器的要求越高;二次流总温对压力匹配基本无影响。     

A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise,minimum mean square variance criterion and least mean square adaptive filter

Underwater acoustic signal processing is one of the research hotspots in underwater acoustics. Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing. Owing to the complexity of marine environment and the particularity of underwater acoustic channel, noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing. In order to solve the dilemma, we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), minimum mean square variance criterion (MMSVC) and least mean square adaptive filter (LMSAF). This noise reduction technique, named CEEMDAN-MMSVC-LMSAF, has three main advantages: (i) as an improved algorithm of empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN can better suppress mode mixing, and can avoid selecting the number of decomposition in variational mode decomposition (VMD); (ii) MMSVC can identify noisy intrinsic mode function (IMF), and can avoid selecting thresholds of different permutation entropies; (iii) for noise reduction of noisy IMFs, LMSAF overcomes the selection of decomposition number and basis function for wavelet noise reduction. Firstly, CEEMDAN decomposes the original signal into IMFs, which can be divided into noisy IMFs and real IMFs. Then, MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs. Finally, both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained. Compared with other noise reduction techniques, the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals, which has the better noise reduction effect and has practical application value. CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection, feature extraction, classification and recognition of underwater acoustic signals.     

Dynamic pricing and matching in ride-hailing platforms

Ride-hailing platforms such as Uber, Lyft, and DiDi have achieved explosive growth and reshaped urban transportation. The theory and technologies behind these platforms have become one of the most active research topics in the fields of economics, operations research, computer science, and transportation engineering. In particular, advanced matching and dynamic pricing (DP) algorithms—the two key levers in ride-hailing—have received tremendous attention from the research community and are continuously being designed and implemented at industrial scales by ride-hailing platforms. We provide a review of matching and DP techniques in ride-hailing, and show that they are critical for providing an experience with low waiting time for both riders and drivers. Then we link the two levers together by studying a pool-matching mechanism called dynamic waiting (DW) that varies rider waiting and walking before dispatch, which is inspired by a recent carpooling product Express Pool from Uber. We show using data from Uber that by jointly optimizing DP and DW, price variability can be mitigated, while increasing capacity utilization, trip throughput, and welfare. We also highlight several key practical challenges and directions of future research from a practitioner's perspective.     

无人飞行器异源图像匹配辅助惯性导航定位技术综述

无全球定位系统下高精度定位与导航是飞行器实现自主侦查、巡航与打击的关键。视觉导航具有被动、低成本、能避免累积误差等优点。视觉导航与惯性导航融合更能够发挥出各自的优势,达到高精度定位的目的。总结了异源图像匹配辅助惯性导航的飞行器定位技术的发展历程; 从相机-惯导标定技术、异源图像匹配、姿态解算、数据融合和后端优化五个方面详细阐述了异源图像匹配辅助惯性导航的飞行器定位的关键技术; 指出了基于深度学习的异源图像匹配与惯性导航两种无源定位组合导航系统融合技术等四个未来可能的发展方向,可为实现异源图像匹配辅助惯性导航飞行器定位技术提供参考。     

军用履带车辆电传动匹配计算

为给军用履带车辆电传动部件选型提供理论依据,对某车型的双侧电机传动方案中驱动用永磁同步电动机及主要部件的性能参数进行了匹配计算,并根据车辆对驱动系统大转矩和宽调速范围的要求,提出了驱动电机必须具备的过载能力和弱磁能力,最后利用仿真手段验证了计算方法的有效性。