Automatic modulation recognition of radio fuzes using a DR2D-based adaptive denoising method and textural feature extraction

The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.

Design and Application of an S-band Fast Radio Bursts Search Pipeline for the Nanshan 26 m Radio Telescope

Fast radio bursts(FRBs)are among the most studied radio transients in astrophysics,but their origin and radiation mechanism are still unknown.It is a challenge to search for FRB events in a huge amount of observational data with high speed and high accuracy.With the rapid advancement of the FRB research process,FRB searching has changed from archive data mining to either long-term monitoring of the repeating FRBs or all-sky surveys with specialized equipments.Therefore,establishing a highly efficient and high quality FRB search pipeline is the primary task in FRB research.Deep learning techniques provide new ideas for FRB search processing.We have detected radio bursts from FRB 20201124A in the L-band observational data of the Nanshan 26 m radio telescope(NSRT-26m)using the constructed deep learning based search pipeline named dispersed dynamic spectra search(DDSS).Afterwards,we further retrained the deep learning model and applied the DDSS framework to S-band observations.In this paper,we present the FRB observation system and search pipeline using the S-band receiver.We carried out search experiments,and successfully detected the radio bursts from the magnetar SGR J1935+2145and FRB 20220912A.The experimental results show that the search pipeline can complete the search efficiently and output the search results with high accuracy.

基于RDS和Data.V技术、HACCP体系的水产药物检测分析

目前,我国鱼药市场存在诸多问题,如有些药物言不符实,品质良莠不齐,养殖户在选择鱼药的时候常常得不到有效合理的信息,不能有效地对疾病做出合理控制,加大了养殖户的损失。利用云数据库等相关信息技术和相关的检测技术分析市场上现有的药品,筛选出优质的、有效成分含量高的高品质鱼药,实现针对性治疗。基于此,本文探究将云数据库RDS、Data.V可视化数据与HACCP检测体系相结合,有效预防水产动物疾病。

基于广播数据系统(RDS)的交通及出行者信息系列标准的研究与制定

基于广播数据系统的交通及出行者信息系列标准的研究与制定工作很好地贯彻了"借鉴国际标准,做好本地转化"的指导思想,有利于国内外基于RDS-TMC的信息发布系统和设备的一致性,适合我国城市交通信息和跨区域高速公路交通信息的发布。

基于SAA6588解码器的RDS接收系统的设计与实现

无线数据系统(Radio Data system,简称RDS)已在欧美得到了广泛的应用。本文介绍了基于SAA6588解码器的RDS接收系统的设计与实现方法,给出了RDS接收系统的硬件电路和软件设计,并成功应用于公交车上的广告系统中。

VB6中RDS数据绑定技术的实现

用远程数据服务 ( RDS)技术进行远程数据的存取 ,是 VB程序中的一个重要课题。文章分析了 RDS的运行原理 ,实现了在 VB程序中进行远程数据绑定的技术。

复杂环境下少样本域自适应雷达RD智能识别技术

针对复杂电磁环境下,传统基于雷达回波的目标识别方法定位精度差和识别能力不足的问题,以典型海背景环境下的雷达时频二维像目标为研究对象,提出了复杂环境下少样本域自适应雷达智能RD识别技术,通过设计基于分离注意力的偏移区间配准目标识别算法架构,实现了对目标的精确定位和识别,同时设计了域自适应技术对源域和目标域进行特征配准,解决少样本条件下算法场景适应性不足的问题。通过在雷达回波仿真数据和真实数据上对算法测试验证,取得了较优的结果,证明了该算法的有效性。

基于RDS技术的矿井应急定位呼救器设计与实现

使用RDS技术设计了矿井定位应急呼救器,对其实现过程进行详细描述,并给出实测结果;采用RDS协议中2A组型码,设计了寻址定位需要的信息格式;呼救器通过SI4721调制解调呼救及定位信息,并使用声表面波滤波器、PLL-VCO以及混频器,消除了SI4721输出信号的旁瓣,解决了相邻信号频率干扰问题;实测结果表明,呼救器可以实现实时的清晰语音呼救功能的要求,同时,可以实现井下呼叫单元定位,具备人机界面友好、工作稳定以及安全等优点;系统的信噪比达到96dB,寻址定位信息正确率在98%以上。

基于SI473X的RDS功能设计与实现

介绍了RDS功能在车载音响系统中的应用与实现,并设计低功耗硬件电路以适应车载供电的要求。RDS功能采用SI473X嵌入式芯片实现,通过软件编程实现了带RDS的数字调频立体收音功能,为车载音响系统提供调频接收和RDS信息服务。通过平台测试,证明是一种廉价可行的解决方案。

基于Oracle Data Guard的容灾策略与实现

本文论述了数据库容灾备份的概念以及Data Guard概述,从Da-ta Guard保护模式、工作原理等方面分析了Oracle Data Guard容灾技术的可用性。讨论了如何利用Data Guard技术来实现数据容灾备份,并给出了详细的实现方法。

Intelligent Network Selection for Data Offloading in 5G Multi-Radio Heterogeneous Networks

In next generation networks, multiradio networks are emerging in order to deal with exponential data traffic increasing. Integrated Femto-WiFi(IFW) small cells have been introduced by 3GPP to offload data from cellular networks recently. These IFW cells are multi-mode capable(i.e., both licensed bands via cellular interface and unlicensed bands via WiFi interface). Therefore how to offload data effectively has become one of the most significant discussions in 5G Multi-Radio Heterogeneous Network. So far, most researches mainly focus on the generality of UEs, few attention has been paid to UEs' individual requirements. Considering UE's preference vary from individual to individual, in this paper, we present an UE preference-aware network selection scheme for mobile data offloading. It intelligently supports the distribution of heterogeneous classes of services, considers different types of UEs and delay-tolerant flows, and handles the mobility of UEs. The simulation results show the superiority of the proposed algorithm in user fairness, enhanced capacity and energy saving maximization.

Multi-slots Wideband Cooperative Spectrum Sensing Based on Weighed Data Fusion in Cognitive Radio

In order to avoid the interference to the primary user(PU), in this paper Cognitive Radio (CR) periodically senses the presence of PU, and during one period, CR can sense all the sub-channels based on weighed data fusion and then use all the idle channels decided by the coordinator. The local sensing time of CR is divided into multi-slots in which CR can sense any sub-channel. Through reasonably allocating the sensing slots and users by mathematic optimization, the proposed algorithm can improve the total throughput of CR. The optimization problem of the proposed scheme which seeks to maximize the throughput subject to the constraint of the detected performance of each sub-channel is proposed in order to choose the optimum local sense time and the number of the cooperative CRs. The simulation results indicate that the proposed scheme can obtain higher throughput than the conventional single-channel sense, and there are the optimum local sense time and the number of cooperative CRs to make the throughput reach maximum.

Carrier Frequency Offset Estimation for FM and Symbiotic FM Radio Data System Hybrid Signal

The symbiotic FM radio data system(SRDS)is a radio data system that a specially designed OFDM signal co-lives with FM signal,which enables a significantly higher data rate than existing radio data systems.The cyclic prefix of the OFDM symbol has the same length as the OFDM body,which enables the analytic separation of the co-channel OFDM and FM signal at receiver side,utilizing the fact that the OFDM body and prefix is equal.In this work,we show that the OFDM body and prefix cannot be viewed as equal when there is sufficient carrier frequency offset(CFO).Thus,we propose a two-step CFO estimation algorithm for FM and SRDS hybrid signal.The first step estimates the coarse CFO by exploring the characteristics of the FM signal.Once the coarse CFO is removed,the residual CFO is small enough for FM and OFDM separation.The second step fine estimates CFO from the OFDM-only signal using its repeated PN structure after the separation.Detailed mathematical equations are formulated and simulation results are given.The results show that the proposed algorithm works fine with the simulation setup and has a final residual CFO less than 3.9Hz.

Generating a radioheliograph image from SDO/AIA data with the machine learning method

Radioheliograph images are essential for the study of solar short term activities and long term variations, while the continuity and granularity of radioheliograph data are not so ideal, due to the short visible time of the Sun and the complex electron-magnetic environment near the ground-based radio telescope. In this work, we develop a multi-channel input single-channel output neural network, which can generate radioheliograph image in microwave band from the Extreme Ultra-violet(EUV) observation of the Atmospheric Imaging Assembly(AIA) on board the Solar Dynamic Observatory(SDO). The neural network is trained with nearly 8 years of data of Nobeyama Radioheliograph(No RH) at 17 GHz and SDO/AIA from January 2011 to September 2018. The generated radioheliograph image is in good consistency with the well-calibrated No RH observation. SDO/AIA provides solar atmosphere images in multiple EUV wavelengths every 12 seconds from space, so the present model can fill the vacancy of limited observation time of microwave radioheliograph, and support further study of the relationship between the microwave and EUV emission.

Global Statistical Study of Ionospheric Waves Based on COSMIC GPS Radio Occultation Data

Extracting and parameterizing ionospheric waves globally and statistically is a longstanding problem. Based on the multichannel maximum entropy method（MMEM） used for studying ionospheric waves by previous work, we calculate the parameters of ionospheric waves by applying the MMEM to numerously temporally approximate and spatially close global-positioning-system radio occultation total electron content profile triples provided by the unique clustered satellites flight between years 2006 and 2007 right after the constellation observing system for meteorology, ionosphere, and climate（COSMIC） mission launch. The results show that the amplitude of ionospheric waves increases at the low and high latitudes（~0.15 TECU） and decreases in the mid-latitudes（~0.05 TECU）. The vertical wavelength of the ionospheric waves increases in the mid-latitudes（e.g., ~50 km at altitudes of 200–250 km） and decreases at the low and high latitudes（e.g., ~35 km at altitudes of 200–250 km）.The horizontal wavelength shows a similar result（e.g., ~1400 km in the mid-latitudes and ~800 km at the low and high latitudes）.

在Excel中使用VBA编程处理RDS抽样调查数据

Excel是Office办公软件中的一员,其强大的数据处理功能使其在数据表处理方面占有非常重要的地位,特别是可以使用VBA进行编程来处理更加复杂的数据,针对RDS抽样调查数据如何处理进行了探索。

FM-RDS应急广播自动监测平台的构建

对播出信号实时监测是广播电视安全播出的重要保障。本文介绍大理州应急调频广播网自动监测平台建设情况,从大理州78个各级应急调频广播发射站点采集调频广播信号、设备运行状态、RDS控制编码等信息,解调、转码后将TS流打包封装为IP数据包,通过IP网络回传监测数据至大理州监测中心,构建软件平台对应急广播台站播出情况进行实时监测和远程管理,以达到减轻维护人员工作压力的目的。

Green Architecture for Dense Home Area Networks Based on Radio-over-Fiber with Data Aggregation Approach

The high-density population leads to crowded cities. The future city is envisaged to encompass a large-scale network with diverse applications and a massive number of interconnected heterogeneous wireless-enabled devices. Hence, green technology elements are crucial to design sustainable and future-proof network architectures. They are the solutions for spectrum scarcity, high latency, interference, energy efficiency, and scalability that occur in dense and heterogeneous wireless networks especially in the home area network （HAN）. Radio-over-fiber （ROF） is a technology candidate to provide a global view of HAN＇s activities that can be leveraged to allocate orthogonal channel communications for enabling wireless-enabled HAN devices transmission, with considering the clustered-frequency-reuse approach. Our proposed network architecture design is mainly focused on enhancing the network throughput and reducing the average network communications latency by proposing a data aggregation unit （DAU）. The performance shows that with the DAU, the average network communications latency reduces significantly while the network throughput is enhanced, compared with the existing ROF architecture without the DAU.

应急广播“村村响”之RDS调频广播多通道传输的应用

在应急广播"村村响"的发展中,RDS调频广播具有举足轻重的作用,但因全国各地的网络存在多样性、复杂性和不确定性,单纯的共缆传输与无线传输已经不能满足市场的需求,因此必须因地制宜根据网络实际寻求一种最适合的传输模式,使以前的单通道传输向多通道传输发展。

基于心脏超声构建心房颤动射频消融术后复发的预测模型

目的基于心脏超声构建心房颤动射频消融术后复发的预测模型,评价其临床效果。方法选取2021年7月至2023年7月郑州大学第一附属医院收治的306例接受心房颤动射频消融术患者为研究对象,根据术后6个月内复发情况分为复发组、未复发组。比较两组临床资料及心脏超声定量参数,分析术后复发的影响因素,构建术后复发的预测模型,并进行评价与验证。结果306例患者术后6个月内复发89例,复发率为29.08%;复发组高血压、阻塞性睡眠呼吸暂停低通气综合征(OSAHS)、慢性心力衰竭患者占比高于未复发组,病程长于未复发组,左房前后径、右房横径、肺动脉收缩压、经二尖瓣左室舒张早期血流速度/组织多普勒成像舒张早期二尖瓣环运动速度(E/e’)高于未复发组(P<0.05)。高血压、OSAHS、慢性心力衰竭、病程、左房前后径、E/e’均是术后复发的相关影响因素(P<0.05);构建预测模型,该模型的C-index为0.899,评价与验证结果显示该模型具有较高预测价值及明显临床正向净收益。结论左房前后径、慢性心力衰竭、病程、E/e’、高血压、OSAHS是心房颤动射频消融术后复发的独立影响因素,基于上述因素构建随机森林预测模型具有较好预测效能及临床正向净收益,可为临床早期预测术后复发情况提供参考,并对后续临床决策具有一定指导意义。