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2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)最新文献

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Sonar echo signal processing based on Convolution Blind source separation 基于卷积盲源分离的声纳回波信号处理
2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP) Pub Date : 2020-09-01 DOI: 10.1109/ICICSP50920.2020.9232058
Zhang Yan, Sun Sheng-kai, Liu Yue, Wang Jia-qi
{"title":"Sonar echo signal processing based on Convolution Blind source separation","authors":"Zhang Yan, Sun Sheng-kai, Liu Yue, Wang Jia-qi","doi":"10.1109/ICICSP50920.2020.9232058","DOIUrl":"https://doi.org/10.1109/ICICSP50920.2020.9232058","url":null,"abstract":"The existence of noise, sound scattering and reverberation in active sonar echo signal makes it very difficult to extract the target echo signal. This paper uses the convolution blind source separation algorithm to process the active sonar echo signal. The signal is transferred to the frequency-domain by sliding the STFT. The JADE blind source separation algorithm is used in the frequency domain, and the signal is finally inverted to the time domain through the ISTFT. The separation effect is compared and evaluated through similarity coefficients, time-domain waveforms, and time-frequency diagrams. The simulation results show that this method has a good effect on the separation of active sonar echo signals.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133212262","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: 2
Analysis on the Influence of BeiDou Satellite Pseudorange Bias on Positioning 北斗卫星伪距偏差对定位的影响分析
2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP) Pub Date : 2020-09-01 DOI: 10.1109/ICICSP50920.2020.9232128
L. Li, Xiaohui Liu, Wei Xiao, Xiaomei Tang
{"title":"Analysis on the Influence of BeiDou Satellite Pseudorange Bias on Positioning","authors":"L. Li, Xiaohui Liu, Wei Xiao, Xiaomei Tang","doi":"10.1109/ICICSP50920.2020.9232128","DOIUrl":"https://doi.org/10.1109/ICICSP50920.2020.9232128","url":null,"abstract":"Pseudorange bias is an important error that affects the quality of satellite navigation signals, and it has a certain influence on the precise orbit determination and user positioning accuracy related to the pseudorange observation. However, there are few studies on the influence of pseudorange bias due to Beidou satellite signal distortion and receiver technical parameters on positioning performance at present. This paper theoretically analyze of pseudorange bias on positioning and draw simulates of results firstly, which shows a consistent result with the theoretical result. Then based on this, the different Beidou satellites pseudorange biases are estimated using IGS station measured data, and analyze the mean and variance of the single point positioning (SPP) error of the Beidou satellite signal. Finally, the work compared the positioning accuracy results with pseudorange bias and pseudorange bias correction. The results show that pseudorange bias will make a certain bias to the mean value of the positioning error, while the variance is almost constant. Correction of pseudorange bias, can improve the SPP accuracy of user receiver Beidou satellite signal.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114582857","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: 2
Experimental Results of Maritime Target Detection Based on SVM Classifier 基于SVM分类器的海上目标检测实验结果
2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP) Pub Date : 2020-09-01 DOI: 10.1109/ICICSP50920.2020.9232038
Song Jie, Wankun Hu
{"title":"Experimental Results of Maritime Target Detection Based on SVM Classifier","authors":"Song Jie, Wankun Hu","doi":"10.1109/ICICSP50920.2020.9232038","DOIUrl":"https://doi.org/10.1109/ICICSP50920.2020.9232038","url":null,"abstract":"A radar target detection algorithm based on Support Vector Machine (SVM) Classifier is proposed in this paper for the problem of target detection of high resolution range profile (HRRP). In solving nonlinear and high-dimensional pattern recognition, the SVM classification algorithm proposed based on statistical theory shows many advantages. the basic idea of SVM can be summarized as transforming the input space into a high-dimensional space by the nonlinear variation defined by the inner product, and then finding the optimal classification plane in this new space. The experimental results show the radar target detection algorithm based on SVM classifier can detect targets successfully in different clutter environment and has good performances.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114091715","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: 5
Measuring Similarity in CCTV Systems for a Real-time Assessment of Traffic Jams 基于CCTV系统的交通阻塞实时评估相似度测量
2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP) Pub Date : 2020-09-01 DOI: 10.1109/ICICSP50920.2020.9232098
A. Diop, Amadou Dahirou Gueye, K. Tall, S. M. Farssi
{"title":"Measuring Similarity in CCTV Systems for a Real-time Assessment of Traffic Jams","authors":"A. Diop, Amadou Dahirou Gueye, K. Tall, S. M. Farssi","doi":"10.1109/ICICSP50920.2020.9232098","DOIUrl":"https://doi.org/10.1109/ICICSP50920.2020.9232098","url":null,"abstract":"Traffic jams are inevitable on the roads that many of us use every day. Their number and scale are generally increasing, especially in cities where economic activities are flourishing. The causes of these traffic jams are numerous and generally have economic and socio-environmental consequences. Many solutions have been proposed for detecting traffic jams without considering mathematical tools. In this article, we propose to provide solutions based on mathematical tools which make it possible to measure the similarity between two successive images acquired via closed circuit television (CCTV) systems. This similarity measure will allow us to assess the state of traffic jams in a CCTV system in order to prevent them. By analyzing the transmission of images through a variable sliding window, the implementation of the SSIM (Structural Similarity Index Measure) and the cross-correlation metrics which make possible to measure the similarity between two successive images in transmission in standardized Performance Evaluation of Tracking and Surveillance (PETS) datasets. The comparison between these two metrics based on the processing time and the probability distributions reveals that the SSIM metric provides better performance to prevent traffic jams.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127214082","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
Sound speed profile and geoacoustic parameters estimation 声速分布和地声参数估计
2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP) Pub Date : 2020-09-01 DOI: 10.1109/ICICSP50920.2020.9232084
Xiaofeng Zhao, J. Ding, Yongchui Zhang, Pinglv Yang, Chenjing Tian, Zeming Zhou, Chongwei Zheng
{"title":"Sound speed profile and geoacoustic parameters estimation","authors":"Xiaofeng Zhao, J. Ding, Yongchui Zhang, Pinglv Yang, Chenjing Tian, Zeming Zhou, Chongwei Zheng","doi":"10.1109/ICICSP50920.2020.9232084","DOIUrl":"https://doi.org/10.1109/ICICSP50920.2020.9232084","url":null,"abstract":"With the advancement of sonar technology and inverse problem theory, the use of acoustic signals to retrieve the parameters of underwater acoustic environments has received more and more attention. Based on the parabolic equation (PE) solver and genetic algorithm, this paper studied the problem of jointly inverting the water sound speed profile (SSP) and geoacoustic parameters, where the dimension of water SSP was greatly reduced by the EOFs. Numerical experiments show that this method can provide a high accurately retrieved results with noise free case observations, as well as a favorable anti-noise ability for 3dB Gaussian noise case.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125872158","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
A Super Resolution Method for Remote Sensing Images Based on Cascaded Conditional Wasserstein GANs 基于级联条件Wasserstein gan的遥感图像超分辨方法
2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP) Pub Date : 2020-09-01 DOI: 10.1109/ICICSP50920.2020.9232066
Bo Liu, Heng Li, Yutao Zhou, Yuqing Peng, A. Elazab, Changmiao Wang
{"title":"A Super Resolution Method for Remote Sensing Images Based on Cascaded Conditional Wasserstein GANs","authors":"Bo Liu, Heng Li, Yutao Zhou, Yuqing Peng, A. Elazab, Changmiao Wang","doi":"10.1109/ICICSP50920.2020.9232066","DOIUrl":"https://doi.org/10.1109/ICICSP50920.2020.9232066","url":null,"abstract":"High-resolution (HR) remote sensing imagery is quite beneficial for subsequent interpretation. Obtaining HR images can be achieved by upgrading the imaging device. Yet, the cost to perform this task is very huge. Thus, it is necessary to obtain HR images from low-resolution (LR) ones. In the literature, the super-resolution image reconstruction methods based on deep learning have unparalleled advantages in comparison to traditional reconstruction methods. This work is inspired by these current mainstream methods and proposes a novel cascaded conditional Wasserstein generative adversarial network (CCWGAN) architecture with the residual dense block to generate high quality remote sensing images. We validate the proposed method on the NWPU VHR-10 dataset. Experimental results show our CCWGAN method has superior performance compared with the state-of-the-art GAN methods.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121497730","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: 2
Network Traffic Forecasting Based on Logistic Iterative Regression Model 基于Logistic迭代回归模型的网络流量预测
2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP) Pub Date : 2020-09-01 DOI: 10.1109/ICICSP50920.2020.9232022
Zhang Jianjun, Xu Yuanbiao, Feng Renhai
{"title":"Network Traffic Forecasting Based on Logistic Iterative Regression Model","authors":"Zhang Jianjun, Xu Yuanbiao, Feng Renhai","doi":"10.1109/ICICSP50920.2020.9232022","DOIUrl":"https://doi.org/10.1109/ICICSP50920.2020.9232022","url":null,"abstract":"The size of the network traffic is of great significance to the design of the network architecture. This paper forecast network traffic based on logistic regression model, proposes an improved network traffic forecasting method. In this method, the logistic regression model parameters need to be estimated from historical data. For the three unknown parameters in the logistic regression model, first use the Neyman-Fisher factorization theorem to obtain the unbiased sufficient statistics of one of the parameters. Under the assumption that the general solution is known, use the least square method to solve the other two parameters. Then, under the premise of satisfying the constraints, the scope of the general solution is determined. Among all the parameters, the parameter with the smallest model error is selected to obtain the logistic regression prediction model. Experimental simulations prove that the method improves the accuracy of network traffic forecasting.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130222855","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
An Efficient Correction Method of Direction Finding in Phased Array Reconnaissance System 相控阵侦察系统测向的一种有效校正方法
2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP) Pub Date : 2020-09-01 DOI: 10.1109/ICICSP50920.2020.9232107
Wang Kun-da, Zhang Sheng-feng, Zhu Ye-teng, Zhong Wen
{"title":"An Efficient Correction Method of Direction Finding in Phased Array Reconnaissance System","authors":"Wang Kun-da, Zhang Sheng-feng, Zhu Ye-teng, Zhong Wen","doi":"10.1109/ICICSP50920.2020.9232107","DOIUrl":"https://doi.org/10.1109/ICICSP50920.2020.9232107","url":null,"abstract":"This paper deals with the direction finding problem in the phased array electronic reconnaissance system. With practical application scenarios, an approximate correction method is proposed for the azimuth error of the amplitude comparison method, and the correction method is optimized continuously in combination with the characteristics of the multi-beam reconnaissance task. This method only needs to obtain the elevation of the task, the result of conventional direction finding, and the correction coefficient of each beam which are delivered with the task message. In the simulation section, a series of experiments are proposed to evaluate the effectiveness of the correction method.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130297758","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
Optimal vowels measurements for Obstructive Sleep Apnea Detection Using Speech Signals 使用语音信号进行阻塞性睡眠呼吸暂停检测的最佳元音测量
2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP) Pub Date : 2020-09-01 DOI: 10.1109/ICICSP50920.2020.9231972
Kang-Gao Pang, Tai-Chiu Hsung, Alex Ka-Wing Law, Winnie W S Choi
{"title":"Optimal vowels measurements for Obstructive Sleep Apnea Detection Using Speech Signals","authors":"Kang-Gao Pang, Tai-Chiu Hsung, Alex Ka-Wing Law, Winnie W S Choi","doi":"10.1109/ICICSP50920.2020.9231972","DOIUrl":"https://doi.org/10.1109/ICICSP50920.2020.9231972","url":null,"abstract":"In Obstructive Sleep Apnea (OSA) detection using speech signal during awake, traditional speech-based methods adopt speech features such as Formants and MFCC. As the OSA voice is pathological, the parameters for normal speech processing/recognition is not optimal for the detection. In this paper, we investigate the effects of Linear Predictive coder (LPC) order to the OSA detection. We further propose to adopt dual LPC for feature extractions. In the simulation using 66 OSA patients’ voice signals, we achieve the best accuracy of 95.45% and 86.36% with the proposed parameters using quadratic discriminant analysis classifier for multi-class (4 levels) OSA severity classification using resubstitution and leave-one-out method respectively. As compared to the typical parameters setting, the improvement of resubstitution and leave-one-out are 6.06% and 9.09% respectively.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130944979","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
Welding Wires Centerline Detection Method Based on Image Gradient Segmentation 基于图像梯度分割的焊缝中心线检测方法
2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP) Pub Date : 2020-09-01 DOI: 10.1109/ICICSP50920.2020.9232072
Zeyu Yang, Dirong Yi
{"title":"Welding Wires Centerline Detection Method Based on Image Gradient Segmentation","authors":"Zeyu Yang, Dirong Yi","doi":"10.1109/ICICSP50920.2020.9232072","DOIUrl":"https://doi.org/10.1109/ICICSP50920.2020.9232072","url":null,"abstract":"One of the key problems in integrated circuit (IC) manufacturing is defect detection of welding wires. In welding wire defect detection, center line extraction is a challenging problem due to the large variance of intensity value along a welding wire as against its background. In this paper, a steger centerline detection technique based on gradient amplitude is proposed for automatic extracting centerlines of welding wires. First, the image of an IC chip with a large length-to-side ratio welding wires is taken using dark field imaging method which is suitable for high dynamic reflectivity objects. Then, contrast stretching and gradient threshold techniques are sequentially used to deal with the problem of greatly varying intensity values along welding wire, which is potentially caused by changing normal vectors of the welding wire. Finally, steger center line extraction method is applied. Primary experimental results indicated that the proposed method is superior to traditional methods including threshold segmentation, maximum entropy threshold, and K-means clustering analysis in terms of conserving connectivity of extracted center lines in challenging situations with largely varying contrast of welding wires.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133282941","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
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