Blind velocities mitigation for MIMO GMTI radar with Doppler division multiple access waveforms

Multiple-input multiple-output (MIMO) radar with multiple transmitters and multiple receivers can achieve a larger virtual antenna array and more system degrees of freedom; thus applying it to ground moving target indication (GMTI) radar can improve the performance of GMTI. Doppler division multiple access (DDMA) waveforms are approximately orthogonal providing good minimum detectable velocity (MDV) performance. However, in such DDMA systems, a sufficient pulse repetition frequency (PRF) design freedom is required. Furthermore, these waveforms suffer from blind velocities which are serious problems, especially in radar systems with high carrier frequency or low PRF. This paper analyses the blind velocities problem and show that blind velocities are relative to variation of the PRF and/or the carrier frequency. Variable PRF techniques are widely used in conventional GMTI radar including multiple PRFs and variable pulse repetition intervals (PRI). Combined with the characteristics of the DDMA MIMO GMTI radar, this paper proposed two methods to mitigate blind velocities: “multi-PRF DDMA” which employs multiple PRFs over successive coherent processing intervals, and “PRI-dithered DDMA” which employs nonuniform sampling by dithered PRI in slow time. Simulation results demonstrate that both the methods are effective ways to mitigate blind velocities in DDMA MIMO GMTI radar systems.     

A 3D indoor positioning system based on low-cost MEMS sensors

A positioning system in the absence of GPS is important in establishing indoor directional guidance and localization. Inertial Measuring Units (IMUs) can be used to detect the movement of a pedestrian. In this paper, we present a three-dimensional (3D) indoor positioning system using foot mounted low cost Micro-Electro-Mechanical System (MEMS) sensors to locate the position and attitude of a person in 3D view, and to plot the path travelled by the person. The sensors include accelerometers, gyroscopes, and a barometer. The pedestrians motion information is collected by accelerometers and gyroscopes to achieve Pedestrian Dead-Reckoning (PDR) which is used to estimate the pedestrian’s rough position. A zero velocity update (ZUPT) algorithm is developed to detect the standing still moment. A Kalman filter is combined with the ZUPT to eliminate non-linear errors in order to obtain accurate positioning information of a pedestrian. The information collected by the barometer is integrated with the accelerometer data to detect the altitude changes and to obtain accurate height information. The main contribution of this research is that the approach proposed fuses barometer and accelerometer in Kalman filter to obtain accurate height information, which has improved the accuracy at x axis and y axis. The proposed system has been tested in several simulated scenarios and real environments. The distance errors are around 1%, and the positioning errors are less than 1% of the total travelled distance. Results indicate that the proposed system performs better than other similar systems using the same low-cost IMUs.     

A mobile crowd sensing ecosystem enabled by CUPUS: Cloud-based publish/subscribe middleware for the Internet of Things

Mobile crowd sensing (MCS) is a novel class of mobile Internet of Things (IoT) applications for community sensing where sensors and mobile devices jointly collect and share data of interest to observe phenomena over a large geographic area. The inherent device mobility and high sensing frequency has the capacity to produce dense and rich spatiotemporal information about our environment, but also creates new challenges due to device dynamicity and energy constraints, as well as large volumes of generated raw sensor data which need to be processed and analyzed to extract useful information for end users. The paper presents an ecosystem for mobile crowd sensing which relies on the CloUd-based PUblish/Subscribe middleware (CUPUS) to acquire sensor data from mobile devices in a flexible and energy-efficient manner and to perform near real-time processing of Big Data streams. CUPUS has unique features compared to other MCS platforms: It enables management of mobile sensor resources within the cloud, supports filtering and aggregation of sensor data on mobile devices prior to its transmission into the cloud based on global data requirements, and can push information of interest from the cloud to user devices in near real-time. We present our experience with implementation and deployment of an MCS application for air quality monitoring built on top of the CUPUS middleware. Our experimental evaluation shows that CUPUS offers scalable processing performance, both on mobile devices and within the cloud, while its data propagation delay is mainly affected by transmission delay on wireless links.     

中国互联网发展的历史阶段划分

首先根据互联网重点应用方向的变迁，简单地把中国互联网的发展历程分为3个阶段．然后详细分析每个阶段的时间跨度、划分依据、阶段特点，最后对互联网未来发展趋势进行预测.     

Enhancing QoS of Mobile Devices by a New Handover Process in PMIPv6 Networks

The handover processes in present IP mobility management protocols incur significant latency, thus aggravating QoS of consumer devices. In this paper, we introduce an enhanced handover process for the Proxy Mobile IPv6 (PMIPv6) protocol, which is a recently developed IP mobility management protocol aiming at providing network-based mobility support. The proposed handover process further improves handover performance of PMIPv6 by allowing a new access network obtains handover context before a consumer??s mobile node (MN) moves to the new access network. Data packets destined for the MN are buffered to prevent packet loss and immediately delivered to the MN as the MN moves to the new access network. We evaluate the handover latency and data packet loss of the proposed handover process compared to the basic one of PMIPv6. The conducted analysis results confirm that the proposed handover process yields the reduced handover latency compared to that of the basic PMIPv6 and also prevents data packet loss. We moreover evaluate the buffering cost of the proposed handover process.     

一体化标识网络映射缓存DoS攻击防范方法研究

为了抵御一体化标识网络中接入路由器可能遭受的映射缓存DoS攻击,本文提出了一种基于双门限机制的映射缓存DoS攻击防范方法.该方法设计了一种基于迭代思想的谜题机制降低映射缓存中映射信息条目的增加速率,并采用了映射信息可信度算法识别和过滤映射缓存中恶意的映射信息条目.仿真实验与性能分析表明,该方法能够有效地抵御映射缓存DoS攻击,防止映射缓存溢出.     

一种新闻网页关键信息的提取算法

针对网页正文提取算法缺乏通用性,以及对新闻网页的提取缺乏标题、时间、来源信息的问题,提出一种新闻关键信息的提取算法newsExtractor。该算法首先通过预处理将网页转换成行号和文本的集合,然后根据字数最长的一句话出现在新闻正文的概率极高的特点,从正文中间开始向两端寻找正文的起点和终点提取新闻正文,根据最长公共子串算法提取标题,构造正则表达式并以行号辅助判断提取时间,根据来源的格式特点并辅以行号提取来源;最后构造了数据集与国外开源软件newsPaper进行提取准确率的对比实验。实验结果表明,newsExtractor在正文、标题、时间、来源的平均提取准确率上均优于newsPaper,具有通用性和鲁棒性。     

一种改进的TCP over OBS网络拥塞控制策略

首先深入分析了TCP over OBS网络中造成TCP性能下降的各种原因.在此基础上,考虑将近年来提出的GAIMD算法与OBS网络的特点相结合,提出了一种改进的拥塞控制策略.该策略能在一定程度上改善OBS网络由于随机竞争丢包给TCP性能带来的负面影响.     

基于加密的BitTorrent系统间接激励机制

针对BitTorrent系统中的节点剥削行为,提出一种流模型论证剥削行为对系统性能的影响,通过该模型得到“剥削容忍阈值”,当系统中剥削节点的比例超过该阈值时,系统可能“死亡”。为避免系统“死亡”,提出一种基于加密的间接激励机制。在该机制中,节点必须经过一段时间的供种才能够获取密钥,还原下载的文件,同时该机制还能够根据节点的供种贡献对其下载行为进行奖励。实验结果证明:BitTorrent系统中节点不会因其供种行为获得任何奖励,无法达到抑制剥削行为的效果;引入所提出的机制后,供种节点的下载效率是原BitTorrent系统的2~3倍。     

二氧化铪材料中Cu的最佳迁移路径

The movement of Cu in a HfO2-based resistive random access memory （RRAM） device is investigated in depth by first-principle calculations. Thermodynamics analysis shows that the dominant motion of Cu tends to be along the [001] orientation with a faster speed. The migration barriers along different routes are compared and reveal that the [001] orientation is the optimal migration route of Cu in HfO2, which is more favorable for Cu transportation. Furthermore, the preferable HfOz growth orientation along [100], corresponding to Cu migration along [001], is also observed. Therefore, it is proposed that the HfO2 material should grow along [100] and the operating voltage should be applied along [001], which will contribute to the improvement of the response speed and the reduction of power consumption of RRAM.