Pub Date : 2021-06-18DOI: 10.1109/IMCEC51613.2021.9482267
Xiaomeng Wu, Zexuan Li
Since the industrial revolution, the application of traditional petrochemical energy has brought a lot of pollution and greenhouse effect to the global environment, and new energy technology, as one of the important ways to solve global environmental problems, has been widely recognized by all countries in the world, and its application has become more and more deep widely. As a majority of distributed photovoltaic projects are integrated into the distribution network to generate electricity, the impact on the distribution network and system stability has become increasingly prominent. Since distributed photovoltaic grid connection is the main form and development trend of photovoltaic power generation in the future, analyzing the impact of its harmonics on the distribution network is particularly important for maintaining the stable operation of the grid system.
{"title":"The Impact of Harmonic Generated by Distributed Photovoltaic Grid-connected Power Generation System","authors":"Xiaomeng Wu, Zexuan Li","doi":"10.1109/IMCEC51613.2021.9482267","DOIUrl":"https://doi.org/10.1109/IMCEC51613.2021.9482267","url":null,"abstract":"Since the industrial revolution, the application of traditional petrochemical energy has brought a lot of pollution and greenhouse effect to the global environment, and new energy technology, as one of the important ways to solve global environmental problems, has been widely recognized by all countries in the world, and its application has become more and more deep widely. As a majority of distributed photovoltaic projects are integrated into the distribution network to generate electricity, the impact on the distribution network and system stability has become increasingly prominent. Since distributed photovoltaic grid connection is the main form and development trend of photovoltaic power generation in the future, analyzing the impact of its harmonics on the distribution network is particularly important for maintaining the stable operation of the grid system.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117171780","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}
Pub Date : 2021-06-18DOI: 10.1109/IMCEC51613.2021.9482382
J. Kan, Zongyun Gu, Chun-Yue Ma, Qing Wang
In order to segment leaf image under complex background and improve the accuracy of leaf image segmentation, an image segmentation method based on improved U-shaped network is proposed. Based on the Pytorch deep learning framework, the U-shaped network model FPN is improved, the model adopts the encoder-decoder structure, ResNet50 is used as the trunk network, the encoder receives the image input, the feature extraction is accomplished by convolution, and the decoder uses the bilinear interpolation to complete the image reconstruction and outputs the segmentation results. In order to integrate the underlying position features and high-level semantic features better, the feature fusion module is introduced in the decoder. The experimental results show that the model has a significant effect in plant leaf segmentation, and the technical index is better than most traditional image segmentation algorithms.
{"title":"Leaf Segmentation Algorithm Based on Improved U-shaped Network under Complex Background","authors":"J. Kan, Zongyun Gu, Chun-Yue Ma, Qing Wang","doi":"10.1109/IMCEC51613.2021.9482382","DOIUrl":"https://doi.org/10.1109/IMCEC51613.2021.9482382","url":null,"abstract":"In order to segment leaf image under complex background and improve the accuracy of leaf image segmentation, an image segmentation method based on improved U-shaped network is proposed. Based on the Pytorch deep learning framework, the U-shaped network model FPN is improved, the model adopts the encoder-decoder structure, ResNet50 is used as the trunk network, the encoder receives the image input, the feature extraction is accomplished by convolution, and the decoder uses the bilinear interpolation to complete the image reconstruction and outputs the segmentation results. In order to integrate the underlying position features and high-level semantic features better, the feature fusion module is introduced in the decoder. The experimental results show that the model has a significant effect in plant leaf segmentation, and the technical index is better than most traditional image segmentation algorithms.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"176 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114073194","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}
Pub Date : 2021-06-18DOI: 10.1109/IMCEC51613.2021.9482000
Zhu Shi, Yanpeng Zhao, B. Yang, Fei Yin, Bin Wang, Wenping Liu
A highly current matched charge pump (CP) is proposed to improve the precision of the output clock for a delay-locked loop (DLL). The presented CP based on source-switched structure achieves good matching of charging and discharging currents over a broad dynamic range by introducing a novel rail-to-rail operational amplifier. The stable output voltage of the modified charge pump dramatically reduces the jitter of all output clocks in the locking state. Simulation results at a 1.2V supply voltage and a 40 nm COMS technology demonstrate the maximum mismatching ratio of charging and discharging currents decreases from 26.3% to 5.4% over the operating range of 0.2~1V. Furthermore, compared with the conventional charge pump, the maximum reduction magnitude of jitter for the related output clock is as much as 74.3% at the reference input clock of 1GHz.
{"title":"A High-performance Charge Pump for 40 nm Delay Locked Loops","authors":"Zhu Shi, Yanpeng Zhao, B. Yang, Fei Yin, Bin Wang, Wenping Liu","doi":"10.1109/IMCEC51613.2021.9482000","DOIUrl":"https://doi.org/10.1109/IMCEC51613.2021.9482000","url":null,"abstract":"A highly current matched charge pump (CP) is proposed to improve the precision of the output clock for a delay-locked loop (DLL). The presented CP based on source-switched structure achieves good matching of charging and discharging currents over a broad dynamic range by introducing a novel rail-to-rail operational amplifier. The stable output voltage of the modified charge pump dramatically reduces the jitter of all output clocks in the locking state. Simulation results at a 1.2V supply voltage and a 40 nm COMS technology demonstrate the maximum mismatching ratio of charging and discharging currents decreases from 26.3% to 5.4% over the operating range of 0.2~1V. Furthermore, compared with the conventional charge pump, the maximum reduction magnitude of jitter for the related output clock is as much as 74.3% at the reference input clock of 1GHz.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116608558","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}
Pub Date : 2021-06-18DOI: 10.1109/IMCEC51613.2021.9482284
Tianhe Lu, Li Liu
Road-network plays an important role in urban environment, so the reconnaissance along it should be attached much attention. However, the complexity of the road-network brings a lot of difficulties. In this paper, considering the constraints of road-network adjacent relationship and turn radius of fixed-wing UAV, we defined the problem model, including the road-network model with the description for different kinds of nodes. For road-network traversal problem, this paper proposed a method using improved depth-first search with angle constraint (DFS-AC) and genetic algorithm with double chromosome. The simulation results show that this method is able to solve road-network traversal problem both with and without infeasible nodes, at which fixed-wing UAV has no road to fly along.
{"title":"Research on Road-Network Traversal of Fixed-Wing Multi-UAV in Urban Environment","authors":"Tianhe Lu, Li Liu","doi":"10.1109/IMCEC51613.2021.9482284","DOIUrl":"https://doi.org/10.1109/IMCEC51613.2021.9482284","url":null,"abstract":"Road-network plays an important role in urban environment, so the reconnaissance along it should be attached much attention. However, the complexity of the road-network brings a lot of difficulties. In this paper, considering the constraints of road-network adjacent relationship and turn radius of fixed-wing UAV, we defined the problem model, including the road-network model with the description for different kinds of nodes. For road-network traversal problem, this paper proposed a method using improved depth-first search with angle constraint (DFS-AC) and genetic algorithm with double chromosome. The simulation results show that this method is able to solve road-network traversal problem both with and without infeasible nodes, at which fixed-wing UAV has no road to fly along.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116342100","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}
Pub Date : 2021-06-18DOI: 10.1109/IMCEC51613.2021.9482329
Ming Long, Jun Yang, S. Xia, Xu Wei
In this paper, convolutional neural network (CNN) is used to classificate the rotor blade number of rotor targets micro-motion signal with deep learning’s strong feature extraction ability. Firstly, the scattering point model of the rotor blade echo is used to generate the target echo. Under the condition of different signal-to-noise ratio, time-frequency diagram of the echo with different number of rotor blades is constructed by using short-time Fourier transform, which is used as the test set and training set. Three convolutional neural network models of lenet, alexnet and vggnet are used for training. The performance of the network model is compared, and the recognition performance of the alexnet network model is analyzed under ambiguous, unambiguous and a method of Interpolation to resolve ambiguous. Through experiments, it can be found that the recognition rate of the proposed method can reach 95% under the condition of signal-to-noise ratio of 10dB. It has good recognition performance for classification of rotor blade number, and provides effective data and algorithm support for the rotor target recognition in the future.
{"title":"Classification of rotor blade number of rotor targets micro-motion signal based on CNN","authors":"Ming Long, Jun Yang, S. Xia, Xu Wei","doi":"10.1109/IMCEC51613.2021.9482329","DOIUrl":"https://doi.org/10.1109/IMCEC51613.2021.9482329","url":null,"abstract":"In this paper, convolutional neural network (CNN) is used to classificate the rotor blade number of rotor targets micro-motion signal with deep learning’s strong feature extraction ability. Firstly, the scattering point model of the rotor blade echo is used to generate the target echo. Under the condition of different signal-to-noise ratio, time-frequency diagram of the echo with different number of rotor blades is constructed by using short-time Fourier transform, which is used as the test set and training set. Three convolutional neural network models of lenet, alexnet and vggnet are used for training. The performance of the network model is compared, and the recognition performance of the alexnet network model is analyzed under ambiguous, unambiguous and a method of Interpolation to resolve ambiguous. Through experiments, it can be found that the recognition rate of the proposed method can reach 95% under the condition of signal-to-noise ratio of 10dB. It has good recognition performance for classification of rotor blade number, and provides effective data and algorithm support for the rotor target recognition in the future.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116727424","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}
Pub Date : 2021-06-18DOI: 10.1109/IMCEC51613.2021.9482020
Jing Zhou, Aimei Dong
Deep learning is a branch of machine learning, and its methods are now being used to solve all kinds of problems. Deep learning algorithms can learn advanced features from massive data and automatically extract features, which makes deep learning surpass traditional machine learning algorithms. However, as deep learning algorithms rely on large amounts of data and run too slowly, transfer learning arises in response to this disadvantage. Transfer learning allows the use of existing knowledge in the relevant domain to solve a learning problem with only a small number of sample data in the target domain. Combining the two technologies of deep learning and transfer learning, on the one hand, advanced features of data samples can be automatically learned, and on the other hand, it can get rid of the dependence on sample data capacity. In this paper, the electrocardiogram (ECG) signal into spectrogram, and the model is trained with the ImageNet dataset, and then the trained model is transferred, because AlexNet model needs to be fixed image size, so the last pool layer is replaced by a spatial pyramid pooling layer, finally use Softmax classifier for PhysioNet challenge 2017 electrocardiogram data sets are classified, get a 92.84% accuracy and 83.26% F1.
{"title":"Electrocardiogram classification based on convolutional neural network and transfer learning","authors":"Jing Zhou, Aimei Dong","doi":"10.1109/IMCEC51613.2021.9482020","DOIUrl":"https://doi.org/10.1109/IMCEC51613.2021.9482020","url":null,"abstract":"Deep learning is a branch of machine learning, and its methods are now being used to solve all kinds of problems. Deep learning algorithms can learn advanced features from massive data and automatically extract features, which makes deep learning surpass traditional machine learning algorithms. However, as deep learning algorithms rely on large amounts of data and run too slowly, transfer learning arises in response to this disadvantage. Transfer learning allows the use of existing knowledge in the relevant domain to solve a learning problem with only a small number of sample data in the target domain. Combining the two technologies of deep learning and transfer learning, on the one hand, advanced features of data samples can be automatically learned, and on the other hand, it can get rid of the dependence on sample data capacity. In this paper, the electrocardiogram (ECG) signal into spectrogram, and the model is trained with the ImageNet dataset, and then the trained model is transferred, because AlexNet model needs to be fixed image size, so the last pool layer is replaced by a spatial pyramid pooling layer, finally use Softmax classifier for PhysioNet challenge 2017 electrocardiogram data sets are classified, get a 92.84% accuracy and 83.26% F1.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116908651","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}
Pub Date : 2021-06-18DOI: 10.1109/IMCEC51613.2021.9482153
Bingxin Xu, Rui-xia Liu, Yinglong Wang
ECG is a kind of weak body surface signal that is easily disturbed by noise during the collection process. The traditional ECG signal denoising technology depends on effective filters, which is artificially created by experience. Once the form of the signal is updated, the inherent space may no longer be suitable for this problem. As the deep learning method can learn sparse features from the data without manual intervention. We designed a deep learning process to apply the powerful functions of neural networks to the inference of the ECG sparse noise reduction model, which can also solve the optimization problem in sparse signal processing. By using this method of deep expansion, an optimization strategy is proposed, which turns the iterative optimization problem into constructing a new network framework. In this way, the model parameters can be easily solved through cross-layer. Through experimental verification, our method improves the SNR by 83.29% compared with the current advanced method.
{"title":"An ECG Sparse Noise Reduction Method based on Deep Unfolding Network","authors":"Bingxin Xu, Rui-xia Liu, Yinglong Wang","doi":"10.1109/IMCEC51613.2021.9482153","DOIUrl":"https://doi.org/10.1109/IMCEC51613.2021.9482153","url":null,"abstract":"ECG is a kind of weak body surface signal that is easily disturbed by noise during the collection process. The traditional ECG signal denoising technology depends on effective filters, which is artificially created by experience. Once the form of the signal is updated, the inherent space may no longer be suitable for this problem. As the deep learning method can learn sparse features from the data without manual intervention. We designed a deep learning process to apply the powerful functions of neural networks to the inference of the ECG sparse noise reduction model, which can also solve the optimization problem in sparse signal processing. By using this method of deep expansion, an optimization strategy is proposed, which turns the iterative optimization problem into constructing a new network framework. In this way, the model parameters can be easily solved through cross-layer. Through experimental verification, our method improves the SNR by 83.29% compared with the current advanced method.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115006413","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}
In this paper, collected the operation data of a fuel cell vehicle (FCV) at - 30 ℃ by analyzing the vehicle CAN message. Took stack temperature, stack voltage, stack calorific value and battery SOC as the target objects, analyzed the control logic of fast cold start of the fuel cell vehicle stack at low temperature, and summarized the technical highlights of the fuel cell vehicle, which can be used to guide the product development of domestic automobile enterprises.
{"title":"Research on the performance of fuel cell vehicle at cold start of -30 ℃","authors":"Tong Wang, Nanlin Lei, Shaoqing He, Xiaoyu Jia, Qiang Zhang, Feikun Zhou, Wenwen Guo","doi":"10.1109/imcec51613.2021.9481959","DOIUrl":"https://doi.org/10.1109/imcec51613.2021.9481959","url":null,"abstract":"In this paper, collected the operation data of a fuel cell vehicle (FCV) at - 30 ℃ by analyzing the vehicle CAN message. Took stack temperature, stack voltage, stack calorific value and battery SOC as the target objects, analyzed the control logic of fast cold start of the fuel cell vehicle stack at low temperature, and summarized the technical highlights of the fuel cell vehicle, which can be used to guide the product development of domestic automobile enterprises.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115770476","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}
Pub Date : 2021-06-18DOI: 10.1109/IMCEC51613.2021.9482369
Sun Xi-yan, Hu Xun-Xiong, Ji Yuan-fa, Guo Ning
In the satellite positioning receiver, it is essential to capture the satellite signal and obtain the carrier and Doppler frequency. Whereas, there is a vital problem that the Doppler frequency offset of 100 kilohertz with the change rate of thousands of kilohertz per second under the high dynamic environment which has higher requirements on capture algorithm. Aiming at the Doppler frequency search efficiency of traditional PMF-FFT algorithm, this paper proposes a Quinn-PMF-FFT. Before estimating the Doppler frequency, there is double zero padding, the point of signal does 2N to fill after zero Fourier transform arithmetic, and makes the increase in the number of spectral signal spectrum in the main lobe, then gets more spectral information to modified of the peak position. It is also can obtain more accurate Doppler frequency estimation, and carry out the simulation experiment. Via comparing the mean square frequency error, it is verified that the Quinn-PMF-FFT algorithm can avoid the error of interpolation direction in high dynamic environment, and has higher search efficiency and estimation accuracy.
{"title":"A Method Based on Quinn Algorithm to Improve The Accuracy of PMF-FFT Doppler Frequency Estimation","authors":"Sun Xi-yan, Hu Xun-Xiong, Ji Yuan-fa, Guo Ning","doi":"10.1109/IMCEC51613.2021.9482369","DOIUrl":"https://doi.org/10.1109/IMCEC51613.2021.9482369","url":null,"abstract":"In the satellite positioning receiver, it is essential to capture the satellite signal and obtain the carrier and Doppler frequency. Whereas, there is a vital problem that the Doppler frequency offset of 100 kilohertz with the change rate of thousands of kilohertz per second under the high dynamic environment which has higher requirements on capture algorithm. Aiming at the Doppler frequency search efficiency of traditional PMF-FFT algorithm, this paper proposes a Quinn-PMF-FFT. Before estimating the Doppler frequency, there is double zero padding, the point of signal does 2N to fill after zero Fourier transform arithmetic, and makes the increase in the number of spectral signal spectrum in the main lobe, then gets more spectral information to modified of the peak position. It is also can obtain more accurate Doppler frequency estimation, and carry out the simulation experiment. Via comparing the mean square frequency error, it is verified that the Quinn-PMF-FFT algorithm can avoid the error of interpolation direction in high dynamic environment, and has higher search efficiency and estimation accuracy.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123868244","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}
Pub Date : 2021-06-18DOI: 10.1109/IMCEC51613.2021.9481967
Shiyu Wang, Lihua Li, Tianhui Fu, S. Feng, Yongbin Wang
Based on Maxwell equations, the propagation characteristics of electromagnetic waves across the three layers of the air-water-film-towed cable propagation medium were analyzed, the effect of the antenna's proximity to the medium was proved, and the influence of the seawater film attached to the outside of the towed cable on the reception performance of the towed antenna was obtained, and the FEKO electromagnetic simulation software was used for example verification.
{"title":"Study on the propagation characteristics of the electromagnetic wave across water film on the surface of the towed antenna","authors":"Shiyu Wang, Lihua Li, Tianhui Fu, S. Feng, Yongbin Wang","doi":"10.1109/IMCEC51613.2021.9481967","DOIUrl":"https://doi.org/10.1109/IMCEC51613.2021.9481967","url":null,"abstract":"Based on Maxwell equations, the propagation characteristics of electromagnetic waves across the three layers of the air-water-film-towed cable propagation medium were analyzed, the effect of the antenna's proximity to the medium was proved, and the influence of the seawater film attached to the outside of the towed cable on the reception performance of the towed antenna was obtained, and the FEKO electromagnetic simulation software was used for example verification.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121947539","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}
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