Compressive sensing SAR range compression with chirp scaling principle

Compressive sensing(CS) techniques offer a framework for the detection and allocation of sparse signal with a reduced number of measurements.This paper proposes a novel SAR range compression,namely compressive sensing with chirp scaling(CS-CS),achieving the same range resolution as conventional SAR approach,while using fewer range samplings.In order to realize accurate range cell migration correction(RCMC),chirp scaling principle is used to construct reference matrix for compressive sensing recovery.Additionally,error diagrams are designed for measurement of the performance of CS-CS,and some experiments of using real data are performed to deal with the errors caused by three conditions:SNR,sparsity and sampling.     

Multi-channel SAR imaging based on distributed compressive sensing

The rapid development of compressive sensing(CS)shows that it is possible to recover a sparse signal from very limited measurements.Synthetic aperture radar(SAR)imaging based on CS can reconstruct the target scene with a reduced number of collected samples by solving an optimization problem.For multi-channel SAR imaging based on CS,each channel requires sufficient samples for separate imaging and the total number of samples could still be large.We propose an imaging algorithm based on distributed compressive sensing(DCS)that reconstructs scenes jointly under multiple channels.Multi-channel SAR imaging based on DCS not only exploits the sparsity of the target scene,but also exploits the correlation among channels.It requires significantly fewer samples than multi-channel SAR imaging based on CS.If multiple channels offer different sampling rates,DCS joint processing can reconstruct target scenes with a much more flexible allocation of the number of measurements offered by each channel than that used in separate CS processing.     

浅谈新疆空管系统中的GIS与RS技术应用

新疆空管运行管理系统是基于三维地理信息平台,研究遥感技术和地理信息系统在现代民用航空中的应用,将三维空间遥感数据、民航各专业数据、管理信息、业务流程等多业务平台、多管理系统结合起来,提供直观的操作控制界面,实现民航空管运行集中监控、运行保障、特殊事件及影响分析、突发事件处理及预案生成等功能。     

Transit smart card data mining for passenger origin information extraction

The automated fare collection(AFC) system,also known as the transit smart card(SC) system,has gained more and more popularity among transit agencies worldwide.Compared with the conventional manual fare collection system,an AFC system has its inherent advantages in low labor cost and high efficiency for fare collection and transaction data archival.Although it is possible to collect highly valuable data from transit SC transactions,substantial efforts and methodologies are needed for extracting such data because most AFC systems are not initially designed for data collection.This is true especially for the Beijing AFC system,where a passenger’s boarding stop(origin) on a flat-rate bus is not recorded on the check-in scan.To extract passengers’ origin data from recorded SC transaction information,a Markov chain based Bayesian decision tree algorithm is developed in this study.Using the time invariance property of the Markov chain,the algorithm is further optimized and simplified to have a linear computational complexity.This algorithm is verified with transit vehicles equipped with global positioning system(GPS) data loggers.Our verification results demonstrated that the proposed algorithm is effective in extracting transit passengers’ origin information from SC transactions with a relatively high accuracy.Such transit origin data are highly valuable for transit system planning and route optimization.     

物联网热点问题研究

从物联网的定义出发,引出了物联网感知层研究中亟待解决的若干问题。"物联网"的"物"体现在对物体信息的感知,这可由无线传感网和RFID技术实现,属于感知层研究的内容。对于无线传感网来说,目前需要解决的问题包括能量的获取与控制,这可以从增加能量供应和控制能量消耗两方面进行研究,其热点研究方向有超级电容、无线供电、功耗控制等;无线传感器的自动组网技术包括Ad hoc网络和ZigBee协议研究两个热点方向,分别对应不同的应用场景。对于RFID来说,亟待解决的问题包括天线设计、声表面波技术、碰撞算法等,此外,文中还在感知层研究中研究了一些共性的问题,如电磁波传播特性、节点定位、超宽带技术、网络安全等。     

基于AROP程序包的类Landsat遥感影像配准与正射纠正试验和精度分析

遥感影像的精确配准和正射纠正是进行图像融合、变化检测、图像镶嵌、定量遥感建模、多时相和多传感器影像协同应用的基础和前提。以美国国家航空和航天管理局下设LEDAPS(Landsat Ecosystem Disturbance Adaptive Processing System)课题组开发的配准与正射纠正程序包AROP(Automated Registration and Orthorectification Package)为例,详细阐述了其配准的原理与程序设计流程,并对其配准的精度进行了分析和评价。试验表明:AROP程序包算法能够找出足够的控制点,且控制点分布较为均匀,配准误差小于0.5个像元。误差特征表现为:扫描误差明显大于航向误差,误差的结果与影像漂移、DEM、坡度存在一定的相关性,高程和坡度是影响配准精度的主要因素之一。该程序包目前能够用于对我国CBERS影像的正射校正以及波段不匹配处理,但是对HJ卫星CCD影像数据配准还有待于进一步研究。     

基于跨层快速邻居感知的OLSR协议

提出了一种基于跨层快速邻居感知的OLSR协议——FS-OLSR,协议在采用hello消息进行链路感知和邻居探测的基础上,结合链路层反馈的信息对网络层邻居表进行更新,以增强节点的邻居感知能力;并将邻居节点的新鲜度作为MPR计算的依据,以提高拓扑消息中广播邻居节点的新鲜度,使之更加适合于快速移动场景。仿真结果表明,在快速移动场景中,FS-OLSR能够在增加少量路由开销的情况下,显著降低丢包率。     

时分复用光纤光栅传感阵列中DFB激光器的高精度温控设计

针对时分复用光纤光栅(TDM-FBG)传感阵列中使用的分布反馈(DFB)激光器高波长稳定度的要求,设计了一个高精度的DFB温控方案,包括温度测量与设定、热敏电阻线性化、PID补偿回路、H桥驱动、温度电压采集与显示等。使用DFB内置的热敏电阻和半导体制冷器(TEC)对温控电路进行了测试,其精度在180s内达到±0.04℃,温控后激光器温度变化引起的应变测量误差为±3.4με左右,满足TDM-FBG传感阵列的要求。