Pub Date : 2022-11-05DOI: 10.1109/CISP-BMEI56279.2022.9980292
Xuewei Chen, Zhihua Huang
P300 brain-computer interface (BCI) is an important field of brain science exploration, but the calibration of P300 affects its application. To solve this problem, we propose an algorithm that combines transfer learning and reinforcement learning. In the reinforcement learning algorithm, we refer to P300 linear upper confidence bound(PLUCB). Due to the particularity of the PLUCB algorithm, we modify it and integrate the idea of online transfer learning. The new algorithm is applied to the calibration-free classification of P300 BCI, using the classifier matrices of the subjects in the source domain, without collecting additional session data of the target subjects for calibration. We test the performance of the classifier at different stages of the algorithm. For each subject, the agent constantly updates on the first part of the data and the second part of the data is used for testing. The results show that our designed algorithm P300 Homogeneous Online Transfer Learning (PHomOTL) has better performance than PLUCB, transfer PLUCB (TPLUCB) and Stepwise Linear Discriminant Analysis (SWLDA). When 10000 trials are used for training and the remaining 5120 trials are used for testing, the average P300 classification accuracy of PHomOTL is 73.15% and the average character classification accuracy of PHomOTL is 79.46%.
{"title":"A P300 BCI calibration-free algorithm based on intersubject transfer and reinforcement learning","authors":"Xuewei Chen, Zhihua Huang","doi":"10.1109/CISP-BMEI56279.2022.9980292","DOIUrl":"https://doi.org/10.1109/CISP-BMEI56279.2022.9980292","url":null,"abstract":"P300 brain-computer interface (BCI) is an important field of brain science exploration, but the calibration of P300 affects its application. To solve this problem, we propose an algorithm that combines transfer learning and reinforcement learning. In the reinforcement learning algorithm, we refer to P300 linear upper confidence bound(PLUCB). Due to the particularity of the PLUCB algorithm, we modify it and integrate the idea of online transfer learning. The new algorithm is applied to the calibration-free classification of P300 BCI, using the classifier matrices of the subjects in the source domain, without collecting additional session data of the target subjects for calibration. We test the performance of the classifier at different stages of the algorithm. For each subject, the agent constantly updates on the first part of the data and the second part of the data is used for testing. The results show that our designed algorithm P300 Homogeneous Online Transfer Learning (PHomOTL) has better performance than PLUCB, transfer PLUCB (TPLUCB) and Stepwise Linear Discriminant Analysis (SWLDA). When 10000 trials are used for training and the remaining 5120 trials are used for testing, the average P300 classification accuracy of PHomOTL is 73.15% and the average character classification accuracy of PHomOTL is 79.46%.","PeriodicalId":198522,"journal":{"name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129523828","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 : 2022-11-05DOI: 10.1109/CISP-BMEI56279.2022.9979973
Yu Su
In allusion to the problems of the conventional electrocardiogram (ECG) acquisition system, such as large volume, high price and complexity, a portable ECG acquisition and display system based on ADS1292R chip and STM32F103 is designed in the paper. The system uses ASD1292R as analog front end, processes the signal through STM32 microcontroller, and displays heart rate and ECG on the TFT-LCD. Moving average filter and FIR band-pass filter algorithm are adopted in order to remove interference signal. At the same time, the ECG signal can be transmitted to the mobile APP by the serial port Bluetooth module, user can observe their own heart rate and ECG waveform in real time and understand their own physical condition clearly. Through the experiment test, the relative error of heart rate measurement is less than 3%. The research results show that the designed system can stably and effectively collect the ECG signal of human body, and realize the signal transmission and display. It has the characteristics of small size, low cost and low power consumption and is convenient for daily use.
{"title":"Design of ECG acquisition and display system based on ADS1292R and STM32 microcontroller","authors":"Yu Su","doi":"10.1109/CISP-BMEI56279.2022.9979973","DOIUrl":"https://doi.org/10.1109/CISP-BMEI56279.2022.9979973","url":null,"abstract":"In allusion to the problems of the conventional electrocardiogram (ECG) acquisition system, such as large volume, high price and complexity, a portable ECG acquisition and display system based on ADS1292R chip and STM32F103 is designed in the paper. The system uses ASD1292R as analog front end, processes the signal through STM32 microcontroller, and displays heart rate and ECG on the TFT-LCD. Moving average filter and FIR band-pass filter algorithm are adopted in order to remove interference signal. At the same time, the ECG signal can be transmitted to the mobile APP by the serial port Bluetooth module, user can observe their own heart rate and ECG waveform in real time and understand their own physical condition clearly. Through the experiment test, the relative error of heart rate measurement is less than 3%. The research results show that the designed system can stably and effectively collect the ECG signal of human body, and realize the signal transmission and display. It has the characteristics of small size, low cost and low power consumption and is convenient for daily use.","PeriodicalId":198522,"journal":{"name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"314 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122340393","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 : 2022-11-05DOI: 10.1109/CISP-BMEI56279.2022.9980193
Xiangqian Li, Jinping Sun, Fuyuan Feng
In the low altitude marine multi-target tracking scenario, the multiple hypothesis tracking (MHT) algorithm generates a large number of track segments due to the influence of sea clutter. To address this problem, an amplitude information aided graph-based track stitching method is proposed. First, the method models the track stitching scenario as a graph; after that, the amplitude information of different targets are passed in the track graph to obtain the association likelihood of amplitude information between track segments. Under the assumption of Markov, the association likelihood of the amplitude information between the track segments is multiplied with the association likelihood of the target states to obtain the association likelihood between the track segments. Finally, the minimum-cost maximum-flow (MCMF) algorithm is used to solve the stitching results. The simulation results show that the proposed algorithm can effectively improve the track stitching performance in the low altitude marine multi-target tracking scenario, and has a certain degree of improvement compared with the Hungarian algorithm in terms of rates of false association and target fragmentation.
{"title":"Graph-based Track Stitching Method for Low Altitude Marine Multi-target Tracking","authors":"Xiangqian Li, Jinping Sun, Fuyuan Feng","doi":"10.1109/CISP-BMEI56279.2022.9980193","DOIUrl":"https://doi.org/10.1109/CISP-BMEI56279.2022.9980193","url":null,"abstract":"In the low altitude marine multi-target tracking scenario, the multiple hypothesis tracking (MHT) algorithm generates a large number of track segments due to the influence of sea clutter. To address this problem, an amplitude information aided graph-based track stitching method is proposed. First, the method models the track stitching scenario as a graph; after that, the amplitude information of different targets are passed in the track graph to obtain the association likelihood of amplitude information between track segments. Under the assumption of Markov, the association likelihood of the amplitude information between the track segments is multiplied with the association likelihood of the target states to obtain the association likelihood between the track segments. Finally, the minimum-cost maximum-flow (MCMF) algorithm is used to solve the stitching results. The simulation results show that the proposed algorithm can effectively improve the track stitching performance in the low altitude marine multi-target tracking scenario, and has a certain degree of improvement compared with the Hungarian algorithm in terms of rates of false association and target fragmentation.","PeriodicalId":198522,"journal":{"name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116511001","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 : 2022-11-05DOI: 10.1109/CISP-BMEI56279.2022.9980236
Tianhao Wang, Haiqing Jiang
The analysis of intra-pulse characteristics of radar signal is an important part of radar reconnaissance, real-time analysis of intra-pulse features based on instantaneous frequency can efficiently recognize signals of various modulation types and extract parameters. This method has a high recognition rate under certain signal-to-noise ratio, and the algorithm is simple. It can be implemented at high speed on radar reconnaissance digital receiver.
{"title":"Real-time analysis of Intra-pulse characteristics based on instantaneous frequency","authors":"Tianhao Wang, Haiqing Jiang","doi":"10.1109/CISP-BMEI56279.2022.9980236","DOIUrl":"https://doi.org/10.1109/CISP-BMEI56279.2022.9980236","url":null,"abstract":"The analysis of intra-pulse characteristics of radar signal is an important part of radar reconnaissance, real-time analysis of intra-pulse features based on instantaneous frequency can efficiently recognize signals of various modulation types and extract parameters. This method has a high recognition rate under certain signal-to-noise ratio, and the algorithm is simple. It can be implemented at high speed on radar reconnaissance digital receiver.","PeriodicalId":198522,"journal":{"name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127773437","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 : 2022-11-05DOI: 10.1109/CISP-BMEI56279.2022.9980349
Yingjie Li, Feng Li, Shuang Zhou, P. Miao, G. Jin
This paper presents a data acquisition and processing system for the STAR sTGC detector. The system will be used in the STAR detector forward upgrade program. In the STAR detector forward upgrade program, this data acquisition system is required to be able to read out the electric charge signal of 20,000 channels of the sTGC detector. And it is required to have the functions of configuring various parameters of each channel, filtering valid event data, storing data, real-time monitoring, amplitude distribution statistics and recovering the tracks of charged particles. According to these requirements, we designed a data acquisition system composed of 96 FEBs, 16 RODs and the acquisition software. This data acquisition system uses the VMM3a chip to realize the readout of the signal of the sTGC detector. The event data is transmitted to the ROD via the mini-SAS cable at a rate of 3.2Gbps. In ROD, a trigger window is generated to filter valid event data, and then time stamps are added. Finally, valid event data are transmitted to the acquisition software at a rate of 10Gbps via optical fiber. In functional test and cosmic ray test, it is proved that the data acquisition system meets the requirements of the STAR sTGC detector.
{"title":"Design of Data Acquisition and Signal Processing System for STAR sTGC Detector","authors":"Yingjie Li, Feng Li, Shuang Zhou, P. Miao, G. Jin","doi":"10.1109/CISP-BMEI56279.2022.9980349","DOIUrl":"https://doi.org/10.1109/CISP-BMEI56279.2022.9980349","url":null,"abstract":"This paper presents a data acquisition and processing system for the STAR sTGC detector. The system will be used in the STAR detector forward upgrade program. In the STAR detector forward upgrade program, this data acquisition system is required to be able to read out the electric charge signal of 20,000 channels of the sTGC detector. And it is required to have the functions of configuring various parameters of each channel, filtering valid event data, storing data, real-time monitoring, amplitude distribution statistics and recovering the tracks of charged particles. According to these requirements, we designed a data acquisition system composed of 96 FEBs, 16 RODs and the acquisition software. This data acquisition system uses the VMM3a chip to realize the readout of the signal of the sTGC detector. The event data is transmitted to the ROD via the mini-SAS cable at a rate of 3.2Gbps. In ROD, a trigger window is generated to filter valid event data, and then time stamps are added. Finally, valid event data are transmitted to the acquisition software at a rate of 10Gbps via optical fiber. In functional test and cosmic ray test, it is proved that the data acquisition system meets the requirements of the STAR sTGC detector.","PeriodicalId":198522,"journal":{"name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129108048","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}
Hypokalemia is one of the most common electrolyte disorders in clinic. The detection of hypokalemia mainly depends on the detection of serum potassium concentration. Previous studies have shown that with the decrease of serum potassium ion concentration, ECG will show corresponding characteristics. In this paper, 12-lead ECG is used for intelligent detection of hypokalemia. After six artificial features based on ECG are extracted, a two-stream deep learning model is trained by using these features and 12-lead ECG to detect hypokalemia. The AVC of the two-stream model on the verification set is 0.84, and the AVC on the test set is 0.82. After taking the best working point, on the verification set, the sensitivity is 81.45%, the specificity is 74.21 %, and the recognition accuracy is 77.82%, while on the test set, the sensitivity is 77.54%, the specificity is 74.28%, and the recognition accuracy is 75.91 %. The results show that these time-domain features can significantly improve the recognition accuracy of hypokalemia.
{"title":"Intelligent Detection of Hypokalemia Based on 12-Lead ECG Using Two-stream Deep Learning Model","authors":"Yueyi Wang, Gaoyan Zhong, Ya’nan Wang, Qiang Zhu, Jiayong Xie, Xintao Deng, Aiguo Wang, Cuiwei Yang","doi":"10.1109/CISP-BMEI56279.2022.9980196","DOIUrl":"https://doi.org/10.1109/CISP-BMEI56279.2022.9980196","url":null,"abstract":"Hypokalemia is one of the most common electrolyte disorders in clinic. The detection of hypokalemia mainly depends on the detection of serum potassium concentration. Previous studies have shown that with the decrease of serum potassium ion concentration, ECG will show corresponding characteristics. In this paper, 12-lead ECG is used for intelligent detection of hypokalemia. After six artificial features based on ECG are extracted, a two-stream deep learning model is trained by using these features and 12-lead ECG to detect hypokalemia. The AVC of the two-stream model on the verification set is 0.84, and the AVC on the test set is 0.82. After taking the best working point, on the verification set, the sensitivity is 81.45%, the specificity is 74.21 %, and the recognition accuracy is 77.82%, while on the test set, the sensitivity is 77.54%, the specificity is 74.28%, and the recognition accuracy is 75.91 %. The results show that these time-domain features can significantly improve the recognition accuracy of hypokalemia.","PeriodicalId":198522,"journal":{"name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116926868","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 : 2022-11-05DOI: 10.1109/CISP-BMEI56279.2022.9980099
Guang Li, Chengwei Sun, Zeyu Sun
At the beginning of 2020, coronavirus disease 2019(COVID-19) infection spread in Wuhan, China and all over the world. Until April, it had affected millions of people. The computed tomography (CT) imaging is confirmed as one of the assessment method for COVID-19 patients. However distinguish the COVID-19 from those CT images is extremely challenging as it is very time-consuming, and lack of the experienced radiologists. So deep learning based approaches are proposed to triage the COVID-19 images from the normal or other pneumonia images. Here, we proposed a novel global average pooling (GAP) method for the deep neural network to improve the performance of the COVID-19 classification. The novel GAP method is using lung mask region as weighting factor for GAP, which reduce the influence of background region and highlight the classification features of interesting tissue region. The result of our method achieved the triage of COVID-19 with sensitivity 96.4 % and specificity 93.3 % on the independence validation dataset with 2062 CT scans.
{"title":"A Deep Learning Based Method For COVID-19 Classification Using Chest CT Images","authors":"Guang Li, Chengwei Sun, Zeyu Sun","doi":"10.1109/CISP-BMEI56279.2022.9980099","DOIUrl":"https://doi.org/10.1109/CISP-BMEI56279.2022.9980099","url":null,"abstract":"At the beginning of 2020, coronavirus disease 2019(COVID-19) infection spread in Wuhan, China and all over the world. Until April, it had affected millions of people. The computed tomography (CT) imaging is confirmed as one of the assessment method for COVID-19 patients. However distinguish the COVID-19 from those CT images is extremely challenging as it is very time-consuming, and lack of the experienced radiologists. So deep learning based approaches are proposed to triage the COVID-19 images from the normal or other pneumonia images. Here, we proposed a novel global average pooling (GAP) method for the deep neural network to improve the performance of the COVID-19 classification. The novel GAP method is using lung mask region as weighting factor for GAP, which reduce the influence of background region and highlight the classification features of interesting tissue region. The result of our method achieved the triage of COVID-19 with sensitivity 96.4 % and specificity 93.3 % on the independence validation dataset with 2062 CT scans.","PeriodicalId":198522,"journal":{"name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130969111","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 : 2022-11-05DOI: 10.1109/CISP-BMEI56279.2022.9980092
Yupeng Wang, Shuqing He, Xiaowei Wei, Samuel Akolade George
Most of the human action recognition systems based on 3-Dimensional Convolutional Neural Network (3D CNN) architecture recognize human actions frame by frame in video streams, which need to be deployed on high-performance platforms such as cloud servers. Through the targeted optimization of the processing method of each frame of the video in the process of human action recognition, the computing power requirements and the total processing time of human action recognition are reduced. The optimization of human action recognition is tested and verified by the Kinetics-700 dataset, and the accuracy of action recognition is similar to that before optimization, and the total recognition time is only 14.1 % of the total time before optimization. It effectively reduces the performance requirements of the deployment platform, improves the real-time performance of action recognition, and increases the practicability of human action recognition based on deep learning in the application of low computing power platforms.
{"title":"Research on an Effective Human Action Recognition Model Based on 3D CNN","authors":"Yupeng Wang, Shuqing He, Xiaowei Wei, Samuel Akolade George","doi":"10.1109/CISP-BMEI56279.2022.9980092","DOIUrl":"https://doi.org/10.1109/CISP-BMEI56279.2022.9980092","url":null,"abstract":"Most of the human action recognition systems based on 3-Dimensional Convolutional Neural Network (3D CNN) architecture recognize human actions frame by frame in video streams, which need to be deployed on high-performance platforms such as cloud servers. Through the targeted optimization of the processing method of each frame of the video in the process of human action recognition, the computing power requirements and the total processing time of human action recognition are reduced. The optimization of human action recognition is tested and verified by the Kinetics-700 dataset, and the accuracy of action recognition is similar to that before optimization, and the total recognition time is only 14.1 % of the total time before optimization. It effectively reduces the performance requirements of the deployment platform, improves the real-time performance of action recognition, and increases the practicability of human action recognition based on deep learning in the application of low computing power platforms.","PeriodicalId":198522,"journal":{"name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131209518","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 : 2022-11-05DOI: 10.1109/CISP-BMEI56279.2022.9979931
Zhaoxin Hao, J. Sun, D. Gu
Airborne terahertz synthetic aperture radar (THz-SAR) is sensitive to the tiny vibration of the platform because of the short wavelength. Therefore, the phase errors caused by high-frequency vibration of the platform needs to be considered in the motion compensation (MOCO) for THz-SAR imaging. There have been many MOCO methods to compensate the phase errors caused by high-frequency vibration. However, in some cases, the low-frequency motion errors also need to be considered. Different from these methods, this paper proposes a novel MOCO method which compensates both the high-frequency vibration and the low-frequency motion errors. Firstly, the instantaneous chirp rate (ICR) and the instantaneous frequency are both estimated using chirplet decomposition. After filtering out the low-frequency component of the ICR, we obtain the estimate of high-frequency component by using the least squares (LS) sequential estimators. Then, the high-frequency component in the instantaneous frequency is removed, and the parameters of the low-frequency motion are estimated using LS estimator. Finally, the errors are compensated according to the estimated parameters, and the residual phase errors can be compensated by the phase gradient autofocus (PGA) algorithm. The simulation results validate the effectivity of the proposed method.
{"title":"A Novel Motion Compensation Method for High Resolution Terahertz SAR Imaging","authors":"Zhaoxin Hao, J. Sun, D. Gu","doi":"10.1109/CISP-BMEI56279.2022.9979931","DOIUrl":"https://doi.org/10.1109/CISP-BMEI56279.2022.9979931","url":null,"abstract":"Airborne terahertz synthetic aperture radar (THz-SAR) is sensitive to the tiny vibration of the platform because of the short wavelength. Therefore, the phase errors caused by high-frequency vibration of the platform needs to be considered in the motion compensation (MOCO) for THz-SAR imaging. There have been many MOCO methods to compensate the phase errors caused by high-frequency vibration. However, in some cases, the low-frequency motion errors also need to be considered. Different from these methods, this paper proposes a novel MOCO method which compensates both the high-frequency vibration and the low-frequency motion errors. Firstly, the instantaneous chirp rate (ICR) and the instantaneous frequency are both estimated using chirplet decomposition. After filtering out the low-frequency component of the ICR, we obtain the estimate of high-frequency component by using the least squares (LS) sequential estimators. Then, the high-frequency component in the instantaneous frequency is removed, and the parameters of the low-frequency motion are estimated using LS estimator. Finally, the errors are compensated according to the estimated parameters, and the residual phase errors can be compensated by the phase gradient autofocus (PGA) algorithm. The simulation results validate the effectivity of the proposed method.","PeriodicalId":198522,"journal":{"name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"20 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128299036","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 : 2022-11-05DOI: 10.1109/CISP-BMEI56279.2022.9979921
Tian Gao, Xin Zhang, Cuiyun Du
We have numerically evaluated transmission property and bit error rate (BER) performance of 120Gbps Dual-Polarization Quadrature Amplitude Modulation (DP-16QAM) digital coherent signals, with and without nonlinear compensation using digital back propagation (DBP). If the maximum transmitter powers are defined as the powers at which BER floor levels are $1.0times 10^{-2}$ without error correction, the maximum transmitter power is +17.2 dBm for single-channel 120Gbps DP-16QAM formats in large-core and low-loss single-mode silica fibers nonrepeatered systems. There is 2 dB development compared without using DBP approach. However, the performance is affected by nonlinear interference in DWDM non-repeatered systems, the improvement has been reduced to 0.6dB due to disturbance from neighboring DWDM channels.
{"title":"On the Impact of Digital Back Propagation Nonlinearity Compensation in Non-Repeatered Transmission WDM Systems","authors":"Tian Gao, Xin Zhang, Cuiyun Du","doi":"10.1109/CISP-BMEI56279.2022.9979921","DOIUrl":"https://doi.org/10.1109/CISP-BMEI56279.2022.9979921","url":null,"abstract":"We have numerically evaluated transmission property and bit error rate (BER) performance of 120Gbps Dual-Polarization Quadrature Amplitude Modulation (DP-16QAM) digital coherent signals, with and without nonlinear compensation using digital back propagation (DBP). If the maximum transmitter powers are defined as the powers at which BER floor levels are $1.0times 10^{-2}$ without error correction, the maximum transmitter power is +17.2 dBm for single-channel 120Gbps DP-16QAM formats in large-core and low-loss single-mode silica fibers nonrepeatered systems. There is 2 dB development compared without using DBP approach. However, the performance is affected by nonlinear interference in DWDM non-repeatered systems, the improvement has been reduced to 0.6dB due to disturbance from neighboring DWDM channels.","PeriodicalId":198522,"journal":{"name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131600030","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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