2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)最新文献_第2页

JYOLO: Joint Point Cloud for Autonomous Driving 3D Object Detection JYOLO:自动驾驶3D目标检测的联合点云

2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) Pub Date : 2022-10-25 DOI: 10.1109/ICSPCC55723.2022.9984261

Hongpeng Tian, Lunlun Guo

引用次数: 1

A total uncertainty measure for Atanassov’s intuitionistic fuzzy sets Atanassov直觉模糊集的全不确定性测度

2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) Pub Date : 2022-10-25 DOI: 10.1109/ICSPCC55723.2022.9984272

Hailin Zhang, Yafei Song, Lei Lei

引用次数: 0

Secure Symbol-Level Precoding Designs via Intelligent Reflecting Surface 基于智能反射面的安全符号级预编码设计

2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) Pub Date : 2022-10-25 DOI: 10.1109/ICSPCC55723.2022.9984307

Yong Jin, Chuang Liu, Zewen Li

引用次数: 1

Wideband DOA estimation via low rank and denoising covariance matrix reconstruction 基于低秩去噪协方差矩阵重构的宽带DOA估计

2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) Pub Date : 2022-10-25 DOI: 10.1109/ICSPCC55723.2022.9984440

Juan Shi, Lihuan Huang, Weidong Wang, Quanhe Chen, Xuan Shi

{"title":"Wideband DOA estimation via low rank and denoising covariance matrix reconstruction","authors":"Juan Shi, Lihuan Huang, Weidong Wang, Quanhe Chen, Xuan Shi","doi":"10.1109/ICSPCC55723.2022.9984440","DOIUrl":"https://doi.org/10.1109/ICSPCC55723.2022.9984440","url":null,"abstract":"1In wideband array signal processing, most existing direction of arrival (DOA) estimation methods have poor performance with finite snapshots. Aiming at this problem, this paper proposes a novel DOA estimation method for wideband signal sources using denoising covariance matrix reconstruction based on Toeplitz structure presented, followed by the low rank and denoising MUSIC method. Specifically, the wideband signal covariance matrix with finite snapshots is directly modeled as the sum of the covariance matrix of the signal sources and that of the noise according to the low rank recovery theory. Then, a convex model is established by weakening the noise subspace of the data sampling covariance matrix. Afterwords, a low rank and denoising Toeplitz covariance matrix is reconstructed via performing semidefinite programming (SDP) on the optimization target. Finally, the target angles are efficiently estimated by the improved MUSIC method. The numerical simulation results show that the improved wideband DOA (WDOA) estimation method solution outperforms the other two classical DOA estimation methods in the case of small angular separation and low signal to noise ratio(SNR).","PeriodicalId":346917,"journal":{"name":"2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114605572","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

TDOA-based Target Localization Under Distance-dependent Noise Model 距离依赖噪声模型下基于tdoa的目标定位

2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) Pub Date : 2022-10-25 DOI: 10.1109/ICSPCC55723.2022.9984634

Feifei Pang, Pei Song, Jian-Yin Lu, Lihuan Huang, Zhixiang Gao

引用次数: 0

SBL Based on Fixed Noise Power Estimation Applying to Conformal Array Beamforming 基于固定噪声功率估计的SBL在共形阵波束形成中的应用

2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) Pub Date : 2022-10-25 DOI: 10.1109/ICSPCC55723.2022.9984328

Miao Xu, Wenting Cui, Jidan Mei

引用次数: 0

Code Index Modulation CSK Spread Spectrum Underwater Acoustic Communications 码索引调制CSK扩频水声通信

2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) Pub Date : 2022-10-25 DOI: 10.1109/ICSPCC55723.2022.9984262

Xinyuan Tian, Chengbing He, Jiachao Li, Run Zhang, Dengwen Chen

{"title":"Code Index Modulation CSK Spread Spectrum Underwater Acoustic Communications","authors":"Xinyuan Tian, Chengbing He, Jiachao Li, Run Zhang, Dengwen Chen","doi":"10.1109/ICSPCC55723.2022.9984262","DOIUrl":"https://doi.org/10.1109/ICSPCC55723.2022.9984262","url":null,"abstract":"Limited bandwidth restricts the data rate of spread spectrum underwater acoustic communication systems. In this paper, we propose a novel high-rate spread spectrum underwater acoustic communication approach, which utilizes spread spectrum code index modulation (CIM-SS), cyclic shift keying (CSK) and maximum ratio combined frequency domain equalization (MRC-FDE). In this approach, information bits are jointly conveyed by CIM, CSK and the M-ary PSK modulated symbols. PeCAN polyphase sequences with excellent correlation characteristics are used as spreading codes, and spreading code index modulation is to select spreading code from predefined spreading code set. CSK uses the cyclic shifted version of the selected spreading codes to obtain higher transmission efficiency than direct sequence spread spectrum (DSSS) system. A low complexity detector is designed at the receiver to detect the code index and cyclic shift value of the selected spreading code, so as to despread and demodulate the symbols. Simulation and lake experiment show that the proposed method can improve the data rate and spectrum utilization, and resist the underwater acoustic multipath effect.","PeriodicalId":346917,"journal":{"name":"2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121845878","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: 0

Analysis of Cross-polarized Characteristics of Sea Clutter Based on Airborne Radar Measured Data 基于机载雷达测量数据的海杂波交叉极化特性分析

2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) Pub Date : 2022-10-25 DOI: 10.1109/ICSPCC55723.2022.9984548

Boyu Yang, M. Jiang, Jianmin Wang, Yong Yang

引用次数: 0

Detection of Dangerous Driving Behavior Based on CG-YOLOv5 基于CG-YOLOv5的危险驾驶行为检测

2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) Pub Date : 2022-10-25 DOI: 10.1109/ICSPCC55723.2022.9984614

Weiguo Zhang, Yunxia Xiao

引用次数: 2

Lightweight Vehicle Detection and Recognition Method Based on Improved YOLOv5 in SAR Images 基于改进YOLOv5的SAR图像轻量化车辆检测与识别方法

2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) Pub Date : 2022-10-25 DOI: 10.1109/ICSPCC55723.2022.9984375

Zhitao Wu, Hongtu Xie, Xiao Hu, Jinfeng He, Guoqian Wang

{"title":"Lightweight Vehicle Detection and Recognition Method Based on Improved YOLOv5 in SAR Images","authors":"Zhitao Wu, Hongtu Xie, Xiao Hu, Jinfeng He, Guoqian Wang","doi":"10.1109/ICSPCC55723.2022.9984375","DOIUrl":"https://doi.org/10.1109/ICSPCC55723.2022.9984375","url":null,"abstract":"Synthetic aperture radar (SAR) is very widely used in the military and civilian fields, but the target recognition and detection in the SAR images are relatively difficult. The existing deep learning methods for the SAR target detection and recognition has the problem of many model parameters and low efficiency, thus this paper has proposed a lightweight vehicle detection and recognition method based on the improved YOLOv5 in the SAR images. First, the lightweight processing of reducing the number of the channels is carried out, which can reduce many parameters and speed up the inference. Then, because the vehicles in the SAR image are relatively small and the detection head for detecting the large targets is redundant, the lightweight processing of removing the detection head is performed, which can shorten the running time of the proposed algorithm. Finally, the convolutional block attention module (CBAM) has been added to make the training set fit better when the network model parameters are limited, which can avoid the problem of the excessive decline in the detection and recognition performance after the network model is reduced in the parameters. The experimental results are shown to verify the correctness and the effectiveness of the proposed method.","PeriodicalId":346917,"journal":{"name":"2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131956179","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: 0