International Conference on Signal Processing, Communications and Computing最新文献

A Real-time Detection Algorithm for Unmanned Aerial Vehicle Target in Infrared Search System 红外搜索系统中无人机目标的实时检测算法

International Conference on Signal Processing, Communications and Computing Pub Date : 1900-01-01 DOI: 10.1109/ICSPCC.2018.8567718

Weihua Wang, Peizao Wang, Z. Niu

引用次数: 3

Application of improved wavelet packet energy entropy and GA-SVM in rolling bearing fault diagnosis 改进小波包能量熵和GA-SVM在滚动轴承故障诊断中的应用

International Conference on Signal Processing, Communications and Computing Pub Date : 1900-01-01 DOI: 10.1109/ICSPCC.2018.8567808

Shuangli Li, Zengli Liu

引用次数: 0

Experimental study of Acoustic Communication over Deep-sea Vertical Channel 深海垂直航道声通信实验研究

International Conference on Signal Processing, Communications and Computing Pub Date : 1900-01-01 DOI: 10.1109/ICSPCC.2018.8567738

Shengjun Xiong, Lisheng Zhou, Xiaohui Zhu, Chao Wang, Hongmei Shang

{"title":"Experimental study of Acoustic Communication over Deep-sea Vertical Channel","authors":"Shengjun Xiong, Lisheng Zhou, Xiaohui Zhu, Chao Wang, Hongmei Shang","doi":"10.1109/ICSPCC.2018.8567738","DOIUrl":"https://doi.org/10.1109/ICSPCC.2018.8567738","url":null,"abstract":"Underwater acoustic communication (UAC) has been widely used in UUVs navigation control data transmission, deep-seabed resource investigation and underwater acoustic communication networks. Many scholars have carried out more research on acoustic communication technology over underwater horizontal channels, and there are relatively few researches on UAC over deep-sea vertical channels. This paper is devoted to an experimental study of UAC over deep-sea vertical channels between two types of underwater acoustic MODEM which were installed on the tsunami buoy and the sea-bed base, and based on two types of spread-spectrum technique, direct sequence spread spectrum (DSSS) and sweep-spread carrier (S2C), respectively. We analyze two times long-term experimental data recorded in the SD card after MODEM demodulation with 1360m sea-depth and 3870m sea-depth, and concentrate on the deep-sea vertical channel properties such as the time-delay spread, the amplitude of the successive paths and the time-varying multipath structure. The tsunami buoy received packets demonstrate the better BER performance of DSSS than S2C, and it can be explained by the deep-sea vertical channel properties and the derivation of two types of spread-spectrum technique principle.","PeriodicalId":192839,"journal":{"name":"International Conference on Signal Processing, Communications and Computing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122369808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Hierarchical FOD Detection Scheme Based on Clutter Map CFAR and Pattern Classification 基于杂波图CFAR和模式分类的分层FOD检测方案

International Conference on Signal Processing, Communications and Computing Pub Date : 1900-01-01 DOI: 10.1109/ICSPCC.2018.8567834

Baoshuai Wang, Minjue He, Jianghong Liu, Xiaoliang Zheng

引用次数: 5

Precision Clock Synchronization Method for Towed Line Array Sonar 拖曳线阵声纳精密时钟同步方法

International Conference on Signal Processing, Communications and Computing Pub Date : 1900-01-01 DOI: 10.1109/ICSPCC52875.2021.9564629

Guofei Lv, Qinghua Jiang, Dongdong Wang

引用次数: 0

Backward numerical integration method for nonlinear system 非线性系统的倒向数值积分法

International Conference on Signal Processing, Communications and Computing Pub Date : 1900-01-01 DOI: 10.1109/ICSPCC.2017.8242509

Hao Qiao, Zenghao Li, Peng Sun, Xinguo Li

引用次数: 1

Demonstration system of underwater unmanned swarm combat based on Unity3D 基于Unity3D的水下无人群战演示系统

International Conference on Signal Processing, Communications and Computing Pub Date : 1900-01-01 DOI: 10.1109/ICSPCC55723.2022.9984419

Ke Liu, Duoming Lai, Jiangyang Zhang, Zongxing Li, Jing Wang, Mingchuan Tan

引用次数: 0

Performance analysis of coherent parameters estimation algorithm for distributed coherent aperture radar 分布式相干孔径雷达相干参数估计算法性能分析

International Conference on Signal Processing, Communications and Computing Pub Date : 1900-01-01 DOI: 10.1109/ICSPCC.2017.8242388

Xinghua Liu, Zhen-hai Xu, Luoshengbin Wang, Wei Dong, S. Xiao

引用次数: 2

Jamming Style Selection for Small Sample Radar Jamming Rule Base 小样本雷达干扰规则库的干扰方式选择

International Conference on Signal Processing, Communications and Computing Pub Date : 1900-01-01 DOI: 10.1109/ICSPCC.2018.8567613

Qiang Xing, Weigang Zhu, Y. Bo

{"title":"Jamming Style Selection for Small Sample Radar Jamming Rule Base","authors":"Qiang Xing, Weigang Zhu, Y. Bo","doi":"10.1109/ICSPCC.2018.8567613","DOIUrl":"https://doi.org/10.1109/ICSPCC.2018.8567613","url":null,"abstract":"Aiming at the poor effect of traditional electronic warfare (EW) jamming style selection on modern multifunctional radar, a jamming style selection model based on jamming rule base and the support vector machine (SVM) jamming style selection method suitable for the model is proposed to improve the jamming style selection correct rate and reduce the jamming style selection time. For air-to-air scene of airborne multifunction fire control radar, the pulse repetition frequency (PRF), carrier frequency (CF), pulse width (PW) and intra-pulse box dimension (BoxD), spectral resemblance coefficient (Cr) characteristics of radar signal are extracted and a small sample jamming rule base is constructed. The SVM theory is used to select the jamming style, and the inner product of the input space is transformed into the inner product of the feature space by using the nonlinear mapping radial basis function (RBF). The feature space hyperplane is established and the input is labeled as the corresponding jamming style label. Jamming style is selected shortly and effectively. The experimental results show that compared with the traditional template matching (TM) method, the proposed method can effectively improve the accuracy and real-time performance of jamming style selection. The practical problem of small sample and non-linear interference style selection are solved for its excellent learning and generalization ability.","PeriodicalId":192839,"journal":{"name":"International Conference on Signal Processing, Communications and Computing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127485558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Object-based Indoor Localization using Region-based Convolutional Neural Networks 基于区域卷积神经网络的室内目标定位

International Conference on Signal Processing, Communications and Computing Pub Date : 1900-01-01 DOI: 10.1109/ICSPCC.2018.8567795

Chenning Li, Ting Yang, Qian Zhang, Haowei Xu

{"title":"Object-based Indoor Localization using Region-based Convolutional Neural Networks","authors":"Chenning Li, Ting Yang, Qian Zhang, Haowei Xu","doi":"10.1109/ICSPCC.2018.8567795","DOIUrl":"https://doi.org/10.1109/ICSPCC.2018.8567795","url":null,"abstract":"This study presents a novel method that utilizes Region-based Convolution Neural Network (R-CNN) for identifying objects in an image, and then, localizes the image using a pre-stored map of these objects. The algorithm follows the next steps. First, an image, taken by a smart phone, is uploaded to the server, where a pre-trained R-CNN and template images are combined to identify the objects in the image. In the second step, the location of the image is derived according to the spatial relationships of the objects in the image with a prior knowledge of the objects location in a digital map. Finally, if more than one location solutions are obtained from the previous step, a range-based localization method is utilized to eliminate the wrong results. To prove the concept, a test is conducted in typical yet challenging indoor environment. Selected objects were labeled in 600 images, taken randomly around the test environment, to train the R-CNN and used for template matching. Another 42 images, with known capture locations, were utilized to assess the performance of the method. The proposed object-based indoor localization method detected 81.7% of the objects in the images, and provided 59.5% success rate with 1-5 m accuracy.","PeriodicalId":192839,"journal":{"name":"International Conference on Signal Processing, Communications and Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125560001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3