2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)最新文献_第8页

An Effective Design Approach to Implementation of MIMO-SDM-PNC Relay Stations on FPGA 在FPGA上实现MIMO-SDM-PNC中继站的有效设计方法

2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2022-11-21 DOI: 10.1109/ICCAIS56082.2022.9990538

Minh Le Nguyen, X. Tran, Vu-Duc Ngo, Duc-Thang Nguyen, Tien Anh Vu, Quang-Kien Trinh

引用次数: 0

Multi-Frame STAP Strategy in Range-Doppler Domain for Airborne Radars 机载雷达距离-多普勒域多帧STAP策略

2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2022-11-21 DOI: 10.1109/ICCAIS56082.2022.9990184

Xingyue Long, Wen Qin, Wei Zhang, Chuan Zhu, Yong Zhao, Wei Yi

{"title":"Multi-Frame STAP Strategy in Range-Doppler Domain for Airborne Radars","authors":"Xingyue Long, Wen Qin, Wei Zhang, Chuan Zhu, Yong Zhao, Wei Yi","doi":"10.1109/ICCAIS56082.2022.9990184","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990184","url":null,"abstract":"In airborne radar system, clutter suppression and dim target detection are two challenging problems. Space-time adaptive processing (STAP) can provide good clutter suppression potential. Nevertheless, the low energy of dim targets and the energy loss after STAP make traditional detection method invalid. Based on the problem, the multi-frame joint space-time adaptive processing strategy (MF-STAP) is proposed. Through the multi-frame accumulation, dim targets can be clearly distinguished from the clutter. The original MF-STAP restrict attention to the range domain, which we refer to as range domain MF-STAP (R-MF-STAP) in this paper. Whereas, the elimination of Doppler parameter brings raw information loss and miss detection. To remedy this deficiency, we propose a range-Doppler domain MF-STAP strategy (RD-MF-STAP) in this paper, operating multi-frame accumulation at both range and Doppler domain after STAP process. The performance assessment, conducted resorting to Monte Carlo simulation, shows that the proposed RD-MF-STAP strategy can achieve superior detection and tracking performance than R-MF-STAP strategy.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133134475","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

Multi-class Multi-target Tracking with the Poisson Labeled Multi-Bernoulli filter 泊松标记多伯努利滤波器的多类多目标跟踪

2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2022-11-21 DOI: 10.1109/ICCAIS56082.2022.9990201

Leonardo A. Cament, M. Adams

引用次数: 0

Active Power Filter DC Voltage Control Based on Capacitor Energetic Model 基于电容能量模型的有源电力滤波器直流电压控制

2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2022-11-21 DOI: 10.1109/ICCAIS56082.2022.9990433

Quang-Manh Hoang, Bảo-Huy Nguyễn, Thanh Vo-Duy, J. Trovão, M. C. Ta

{"title":"Active Power Filter DC Voltage Control Based on Capacitor Energetic Model","authors":"Quang-Manh Hoang, Bảo-Huy Nguyễn, Thanh Vo-Duy, J. Trovão, M. C. Ta","doi":"10.1109/ICCAIS56082.2022.9990433","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990433","url":null,"abstract":"Active power filter (APF) is a common solution to suppress the influence of current harmonics in power systems in which the phase current compensation performance of an APF system is affected by the DC-link voltage control loop. In a conventional APF control scheme, the converter power losses are directly conducted from the voltage error by using a PI controller. Due to the lack of physical relationship between the DC voltage error and the converter losses, the conventional controller synthesis is often only based on strict mathematics of control theory. This paper proposes two novel methods to design the DC-link voltage controller taking into account the physical insight of the system model and control. The first method deduces the loss power reference through controlling the energetic model of the capacitor. In the second approach, the loss power is determined through multiplication of the measured DC voltage and current reference conducting from the regulation of the capacitor electrical model. To systematically deduce the control structure, we employ energetic macroscopic representation (EMR) and its associated inversion-based control scheme to organize the studied system. The studied system is simulated on MATLAB/Simulink and the results highlight the correctness and rationale of the proposed control design method.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131316067","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

Dual-scale generalized Radon-Fourier transform family for long time coherent integration 长时间相干积分的双尺度广义Radon-Fourier变换族

2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2022-11-21 DOI: 10.1109/ICCAIS56082.2022.9990039

Bailu Wang, Suqi Li, G. Battistelli, L. Chisci

{"title":"Dual-scale generalized Radon-Fourier transform family for long time coherent integration","authors":"Bailu Wang, Suqi Li, G. Battistelli, L. Chisci","doi":"10.1109/ICCAIS56082.2022.9990039","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990039","url":null,"abstract":"Long time coherent integration (LTCI) is to accumulate target’s energy through long time integration, which is an effective method for the detection of weak target. However, for a moving target, defocusing can occur due to the range migration (RM) and the Doppler frequency migration (DFM). To address this problem, RM and DFM corrections are required to in order to achieve a well-focused image for the subsequent detection. Due to the RM and DFM are caused by the same motion parameters, the generalized Radon–Fourier transform (GRFT), the optimal correction method, adopts the same searching space of motion parameters in order to eliminate both of these two effects simultaneously, leading to large redundant computation. To this end, this paper firstly proposes a dual-scaled decomposition of the target’s motion parameter. Then utilizing this decomposition, the Range-Doppler joint GRFT are degraded into a GIFT process in Range domain and GFT processes in Doppler domain conditioned on the coarse motion parameter. With this appealing property, the joint correction of the RM and DFM effects is decoupled into a cascade procedure, firstly RM correction on the coarse searching space and then the DFM correction on the fine searching spaces, called Dual–Scaled GRFT (DS–GRFT). Compared with the standard GRFT, the proposed DS-GRFT can provide comparable performance while providing significant improvement on computational efficiency. Simulation experiments verify the effectiveness and the efficiency of the proposed method.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"65 Supplement 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115498002","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

PHD Filter Based Traffic Target Tracking Framework with FMCW Radar 基于PHD滤波的FMCW雷达交通目标跟踪框架

2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2022-11-21 DOI: 10.1109/ICCAIS56082.2022.9990385

Xinhua Cao, Chuan Zhu, Wei Yi

{"title":"PHD Filter Based Traffic Target Tracking Framework with FMCW Radar","authors":"Xinhua Cao, Chuan Zhu, Wei Yi","doi":"10.1109/ICCAIS56082.2022.9990385","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990385","url":null,"abstract":"Aiming at tracking traffic target based on frequency modulated continuous wave (FMCW) radar in traffic scenes, this paper proposes a robust Gaussian mixture probability hypothesis density (GM-PHD) filter combined with measurement processing. Due to the different recognition requirements of moving and static targets in this application, the raw measurements are separated into moving and static parts. To deal with the problem of extended target, a density-based spatial clustering of applications with noise (DBSCAN) algorithm is used to cluster the moving measurements and then extract the feature measurements. After the above two steps, the number of measurements input to PHD filter is reduced, which ensures the real-time performance and accuracy of the algorithm. In order to solve the problems of the PHD filter with track information in traffic scenes, this paper proposes some improvements, including target birth intensity generation, track merging and extraction, and target weight correction. The experimental data is used to compare the proposed algorithm with the conventional algorithm, which proves the advantages of the proposed algorithm.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117167680","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

Message passing based data association algorithm for multiple extended object Tracking 基于消息传递的多扩展目标跟踪数据关联算法

2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2022-11-21 DOI: 10.1109/ICCAIS56082.2022.9990408

Feng Yang, Yu Wei, Linfeng Xu

引用次数: 0

A Study of Datum Search Patterns Using a Stochastic Game Framework 基于随机博弈框架的基准搜索模式研究

2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2022-11-21 DOI: 10.1109/ICCAIS56082.2022.9990275

B. Ristic, A. Skvortsov, S. Arulampalam, D. Kim

引用次数: 0

Automatic classification of upper gastrointestinal tract diseases from endoscopic images 上消化道疾病的内镜图像自动分类

2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2022-11-21 DOI: 10.1109/ICCAIS56082.2022.9990445

Phuong Thi Tuyet Nguyen, M. Le, Quoc-Trung Dao, Vu Anh Tran, V. Dao, Thanh-Hai Tran

{"title":"Automatic classification of upper gastrointestinal tract diseases from endoscopic images","authors":"Phuong Thi Tuyet Nguyen, M. Le, Quoc-Trung Dao, Vu Anh Tran, V. Dao, Thanh-Hai Tran","doi":"10.1109/ICCAIS56082.2022.9990445","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990445","url":null,"abstract":"Artificial Intelligence (AI) has played an increasingly crucial part in our daily lives in recent years. Convolutional neural network (CNN) in medical image processing has lately received a lot of interest. With the introduction of modern endoscopic technologies, the doctor could be able to diagnose a patient more accurately. Consequently, it becomes crucial and advantageous to use computer-aided support during procedures. This paper proposes a framework for automatic classification of Upper Gastrointestinal tract diseases that consists of two main parts: a Convolutional Neural Network model (ResNet-50) with Focal Loss application and Data Augmentation techniques that consists of Geometric Transformation (GeoT), Brightness and Contrast Transformation (BaC), which learn hidden features of various Upper GI diseases and anatomical landmark classes, as well as solving the imbalanced dataset problem. As a result, the classification result is improved, with 98.61% of Accuracy on a self-collected dataset from Hanoi Medical University Hospital and Institute of Gastroenterology and Hepatology. Additionally, the proposed method is capable of using in real-time applications by classifying every frame in the video streams.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129829215","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

Maximizing the Geometric Mean of User-Rates to Improve Rate-Fairness in Double RIS-Assisted System 最大化用户速率几何均值以提高双ris辅助系统的速率公平性

2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2022-11-21 DOI: 10.1109/ICCAIS56082.2022.9990383

Yufeng Chen, Y. Fang, Wenbo Zhu, Guannan Tan, Hongwen Yu

引用次数: 0