基于智能天线的TD-SCDMA系统LCS平台研究

从无线定位业务的应用前景出发,结合TD-SCDMA系统采用智能天线的特点,提出了一种方位测量定位法(AOA)和圆周定位法(TOA)的混合定位法,并给出了基于该定位法的无线定位平台的体系结构,而且还对该系统的基本运作机制作了简要的阐述。     

TDMA数字移动通信系统无线干扰技术研究

采用TDMA技术体制的数字移动通信系统,其系统架构和工作方式类似,因此对其干扰方式也基本相同。针对军用TDMA数字移动通信系统,以典型的GSM数字移动通信系统为研究对象,对灵巧式和欺骗式干扰技术进行了研究。     

Two local search approaches for solving real-life car sequencing problems

The NP-hard problem of car sequencing appears as the heart of the logistic process of many car manufacturers. The subject of the ROADEF’2005 challenge addressed a car sequencing problem proposed by the car manufacturer RENAULT, more complex than the academic problem generally addressed in the literature. This paper describes two local search approaches for this problem. In the first part, a new approach by very large-scale neighborhood search is presented. This approach, designed during the qualification stage preceding the final, is based on an original integer linear programming formulation. The second part is dedicated to the approach which enabled us to win the ROADEF’2005 challenge. Inspired by the latest works on the subject, this one is based on very fast explorations of small neighborhoods. Our contribution here is mainly algorithmic, in particular by showing how much exploiting invariants speeds up the neighborhood evaluation and contributes to the diversification of the search. Finally, the two approaches are compared and discussed through an extensive computational study on RENAULT’s benchmarks. The main conclusion drawn at this point is that sophisticated metaheuristics are useless to solve car sequencing problems. More generally, our victory on ROADEF’2005 challenge demonstrates that algorithmic aspects, sometimes neglected, remain the key ingredients for designing and engineering high-performance local search heuristics.     

Deep Learning for Walking Behaviour Detection in Elderly People Using Smart Footwear

The increase in the proportion of elderly in Europe brings with it certain challenges that society needs to address, such as custodial care. We propose a scalable, easily modulated and live assistive technology system, based on a comfortable smart footwear capable of detecting walking behaviour, in order to prevent possible health problems in the elderly, facilitating their urban life as independently and safety as possible. This brings with it the challenge of handling the large amounts of data generated, transmitting and pre-processing that information and analysing it with the aim of obtaining useful information in real/near-real time. This is the basis of information theory. This work presents a complete system aiming at elderly people that can detect different user behaviours/events (sitting, standing without imbalance, standing with imbalance, walking, running, tripping) through information acquired from 20 types of sensor measurements (16 piezoelectric pressure sensors, one accelerometer returning reading for the 3 axis and one temperature sensor) and warn the relatives about possible risks in near-real time. For the detection of these events, a hierarchical structure of cascading binary models is designed and applied using artificial neural network (ANN) algorithms and deep learning techniques. The best models are achieved with convolutional layered ANN and multilayer perceptrons. The overall event detection performance achieves an average accuracy and area under the ROC curve of 0.84 and 0.96, respectively.     

IP2DM: integrated privacy‐preserving data management architecture for smart grid V2G networks

With the development of battery vehicles, vehicle‐to‐grid (V2G) networks are becoming more and more important in smart grid. Although battery vehicles are environmentally friendly and flexible to use two‐way communication and two‐way electricity flow, they also raise privacy‐preservation challenges, such as location and movement privacy. On the one hand, utility companies have to monitor the grid and analyze user data to control the power production, distribution, scheduling, and billing process, while typical users need to access their data later online. On the other hand, users are not willing to provide their personal data because they do not trust the system security of the utility companies where their data stored, and it may potentially expose their privacy. Therefore, in this paper, we study data management of V2G networks in smart grid with privacy‐preservation to benefit both the customers and the utility companies. Both data aggregation and data publication of V2G networks are protected in the proposed architecture. To check its security, we analyze this architecture in several typical V2G networks attacks. We conduct several experiments to show that the proposed architecture is effective and efficient, and it can enhance user privacy protection while providing enough information for utility companies to analyze and monitor the grid. Copyright © 2016 John Wiley & Sons, Ltd.     

智能材料与结构在智能控制中的应用

明确指出了智能材料和结构的概念,针对各种材料的性质和特性,以压电材料和电（磁）流变液在控制中的应用为例进行了讨论,并对智能材料和结构的应用前景进行了展望。     

一种基于激光测距的汽车安全报警装置研究

为防止汽车与前方物体发生碰撞,使汽车始终在安全车速下行驶,减少事故的发生,设计了一种基于激光测距的汽车安全报警装置,它采取激光探测技术,是一种声光电一体的高科技、高智能汽车防撞产品,在出现跟车距离小于安全距离等紧急情况时,发出警报,提醒驾驶员注意并采取减速或制动措施,从而达到有效预防追尾碰撞事故发生的目的,提高了汽车的主动安全性能。测试结果表明,在输入报警距离与制动距离时,均能实现不同方式的报警。     

基于跳频图案补偿的DS/FH混合扩频测控信号载波跟踪技术

DS/FH混合扩频测控系统的中频信号携带有多普勒频率捷变成分,这使载波跟踪环路不断切换到频率阶跃的响应状态,从而导致跟踪精度下降甚至环路失锁.为此,提出一种基于跳频图案辅助的DS/FH混合扩频测控信号载波跟踪方法,通过预知的跳频图案和当前的载体速度测量值估计出下一个跳频点引入的多普勒捷变量,并将其及时补偿到跟踪环路的NCO调整量中.Simulink建模仿真证实了该方法的有效性,在一定的跳频图案时间同步误差范围内,能达到的测量精度与非跳频系统相当.     

多模跟踪技术在轮式侦察车图像处理器的应用

为解决目标旋转形变、遮挡、光照变化等目标跟踪的难题,对粒子滤波和尺度不变特征变换（SIFT）算法进行了改进,结合两种算法提出了决策主导模式的多模跟踪技术。该技术采用粒子滤波预测目标位置进行粗定位,SIFT特征匹配进行精定位的方法,在解决上述难题上有很好的鲁棒性。将该技术应用于轮式侦察车图像处理器,并进行了各种实验验证,结果证明了提出算法的有效性。     

2012年ICT产业发展趋势展望

以全新的视角，首先从电信设备系统侧指出我们正在经历“无线化”的革命转折，之后从用户侧指出我们正在经历的“移动化”的革命转折。这两个转折是同时发生的，因为人类需要任何应用都要能够满足人与生俱来的“移动性”，IT世界技术水平的发展和积累终于达到能够开始全面满足这个基本属性的阶段。这是一个革命性的转变，对无线网络带来五个方面的挑战。