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检索条件"任意字段=2nd International Conference on Signal and Data Processing, ICSDP 2022"

共 3161 条记录，以下是91-100 订阅

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Adaptive Waveform Design for Cognitive Radar Target Detection with Constant Modulus Constraint 2

Adaptive Waveform Design for Cognitive Radar Target Detectio...

引用

2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Wu, Caihao Huang, Chuan Li, Yaowen Liu, Feifeng Liu, Yu He, You Tsinghua University Tsinghua Shenzhen International Graduate School Shenzhen China Tsinghua University Department of Electronic Engineering Beijing China Beijing Institute of Technology School of Information and Electronics Beijing China

ISBN: (纸本)9798331515669

Waveform design is a critical part in cognitive radar to improve the radar performance. In this paper, an adaptive waveform design method based on maximizing the signal to clutter plus noise ratio (SCNR) is proposed, which aims at optimizing the target detection performance. Moreover, to satisfy the practical application, the constant modulus constraint is taken into account. As the first step of the method, the optimal energy spectral density (ESD) of transmit signal is calculated, which suppresses the clutter via the energy allocation. After that, the constant modulus signal is synthesized to approximate the optimal ESD using alternating projection algorithm. The simulation results demonstrate the effectiveness of the proposed method. © 2024 IEEE.

关键词： Spectral density

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Simultaneous Detection and Estimation with Distributed FDA-MIMO and EPC-MIMO Radars 2

Simultaneous Detection and Estimation with Distributed FDA-M...

引用

2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Zhu, Jiayun Zhang, Xiang Lan, Lan Ma, Runlong Cui, Lei Chen, Guozhong Xu, Jingwei Liao, Guisheng Xidian University National Key Laboratory of Radar Signal Processing Xian710071 China Shanghai Institute of Satellite Engineering Shanghai200090 China

ISBN: (纸本)9798331515669

This paper deals with simultaneous parameter estimation and target detection in a distributed radar system consisting of Frequency Diverse Array Multiple-Input Multiple-Output (FDA-MIMO) and Element-Pulse Coding MIMO (EPC-MIMO) radars. For each local radar station, a binary hypothesis detection problem is formulated with unknown target parameters, and detectors are developed leveraging Generalized Likelihood Ratio Test (GLRT) criterion. Under the hypothesis of target presence, the Coordinate Descent (CD) algorithm is leveraged to estimate the range and angle information of the target. Subsequently, the multiple sets of the local test statistics are fused at the Fusion Center (FC) for the ultimate decision, where the global test statistic can be constructed by taking the logarithm sum of local test statistics. At the analysis stage, the effectiveness of the devised method is evaluated in terms of Root Mean Square Error (RMSE) and Probability of Detection (Pd), where comparisons among different radar frameworks, including the distributed radar composed of traditional phased arrays, monostatic EPC-MIMO, and FDA-MIMO radars are carried out. Numerical results verify the superiorities of the proposed approach for simultaneous target detection and parameter estimation. © 2024 IEEE.

关键词： Mean square error

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Research on IIVIFM Model for Batch processing of Fiber Optic Logging data 24

Research on IIVIFM Model for Batch Processing of Fiber Optic...

引用

2024 2nd international conference on Internet of Things and Cloud Computing Technology, IoTCCT 2024

作者： Qin, Minjun Liu, Dongming Pei, Yang Wang, Zhixing Li, Bing Cao, Juan Song, Wenguang Changqing Division of China Petroleum Logging Co. Ltd. Xi'an China School of Computer Science and Engineering Guangdong Ocean University Yangjiang China

ISBN: (纸本)9798400710148

Fiber optic can not only be used as a data transmission device, but also as a signal acquisition device. Research on fiber optic data acquisition for temperature and sound signals (DTS&DAS) has been widely carried out both domestically and internationally, but it has been hindered by numerous interference signals, massive data volume, and slow signal processing speed, which have become a bottleneck in the application of fiber optic DTS&DAS. The article proposes an integrated batch processing oriented big data retrieval and filtering model, IIVIFM, for the first time to address the difficult problem of fiber optic DTS&DAS big data processing in the development process of oil and gas fields. This model achieves batch processing of DTS&DAS data and can effectively filter the data. Finally, through software programming, this method was implemented, enabling it to be widely promoted and applied, providing a new approach for oil and gas data analysis. © 2024 Copyright held by the owner/author(s).

关键词： Gas industry

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Fast Moving Target Focusing with FDMA Radar 2

Fast Moving Target Focusing with FDMA Radar

引用

2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Wang, Yanxing Yan, Shi Lan, Lan Zhu, Shengqi Cui, Lei Chen, Guozhong Li, Ximin Guo, Yixuan Xidian University National Key Laboratory of Radar Signal Processing Xian710071 China Beijing Institute of Remote Sensing Device Beijing100854 China Shanghai Institute of Satellite Engineering Shanghai200090 China

ISBN: (纸本)9798331515669

This paper deal with the challenge of focusing on fast-moving targets in a frequency division multiple access (FD-MA) radar system. At the modeling stage, the linear frequency modulation (LFM) waveform is transmitted by introducing a frequency increment (at least equal to the bandwidth) across the transmit array elements. The received signals are subsequently processed by a filter bank to separate the transmitted waveforms, which in turn provides additional degrees of freedom in the range domain. Particularly, a compensation procedure is designed to eliminate the incoherence between echos between different transmit element due to frequency diversity. To this end, as the outputs of different matched filters become coherent in the spatial domain, the keystone transform (KT) operation is employed to correct the range walk caused by the fast movement of the target, making it possible to focus the target in the space-time-range domain. Furthermore, the angle of the target is estimated and further utilized for beamforming, enhancing the range resolution. Numerical results are provided to verify the effectiveness of the proposed method in focusing the fast moving target with a FDMA radar. © 2024 IEEE.

关键词： Matched filters

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An ISAR Image Reconstruction Method via signal Support Reweighted l1 Minimization 2

An ISAR Image Reconstruction Method via Signal Support Rewei...

引用

2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Zhao, Tiehua Wu, Qihua Xu, Zhiming Ai, Xiaofeng Zhao, Feng Xiao, Shunping National University of Defense Technology The State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology Changsha China

ISBN: (纸本)9798331515669

The sparse aperture caused by data loss or unintentional interference is the actual problem in radar imaging process. Therefore, a compressed sensing (CS) based ISAR image reconstruction method with signal support aided is proposed in this paper. Firstly, the signal support is constructed from FFT-based imaging results. Then the signal support is introduced as a prior information into the reweighted function during the CS reconstruction. The simulation results show that, when the azimuth effective aperture ratio is as low as 30 % and signal-to-noise ratio (SNR) equals to -10 dB, the proposed method can obtain clear imaging results like that of complete aperture data. Besides, compared with the traditional CS reconstruction method, the number of false points in the reconstruction results by proposed method is greatly reduced. © 2024 IEEE.

关键词： Radar imaging

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The Design and System Implementation of Multi-parameter Joint Agile Coherent Radar signal 2

The Design and System Implementation of Multi-parameter Join...

引用

2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Tao, Guang Wang, Tao Zou, Xiaohai Wang, Wei Liu, Yang Sun Yat-sen University College of Electronics and Communication Engineering Guangzhou China Hunan Acqnova Technology Co. Ltd Hunan China

ISBN: (纸本)9798331515669

Advanced deceptive jamming can significantly degrade a radar's detection capabilities and, in severe cases, disable the radar system. Expanding the agility of radar waveform parameters is expected to reduce the effectiveness of jamming parameter reconnaissance, thereby enhancing radar anti-jamming performance. However, complex agile signals pose challenges to the waveform generation of radar systems. Based on this, the paper designs a multi-parameter joint agile radar waveform with low probability of interception. More importantly, it proposes a waveform generation method that meets the real-time requirements of jamming countermeasures. This method involves reading parameters directly from a formatted file, enabling flexible adjustment of waveform parameters and effectively reducing the volume of parameter transmission data. The designed radar signal was implemented on a waveform board card, and test results demonstrate the correctness and effectiveness of the design. © 2024 IEEE.

关键词： Frequency agility

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Improved Deep Matrix Factorization for signal Recovery in Random Frequency Diversity Array Radar 2

Improved Deep Matrix Factorization for Signal Recovery in Ra...

引用

2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Guo, Dayan Lin, Zijian Huang, Tianyao Qi, Yue He, Jie Zhang, Xiao-Ping Wang, Xueqian Li, Gang University of Science and Technology Beijing School of Computer & Communication Engineering Beijing China Tsinghua Shenzhen International Graduate School Institute of Data and Information Shenzhen China Tsinghua University Department of Electronic Engineering Beijing China

ISBN: (纸本)9798331515669

Motivated by the success of recent deep learning researches on radar, we consider a deep learning based matrix factorization method for suppressing the high range-angle side-lobes in random frequency diversity array (FDA) radars. While the existing deep matrix factorization approach is designed for real-valued situations and signals of FDA radars are complex-valued cases, we propose two methods to extend the existing approach into complex-valued framework: 1) adjusting the neural network structures and activation functions for complex-valued operations, and 2) constructing a real-valued representation of the original complex-valued input. Simulation results demonstrate that the proposed methods outperform traditional ones in multi-target scenarios. © 2024 IEEE.

关键词： Matrix factorization

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Accurate Vital Signs Detection Based on FMCW Radar in Dynamic Environments 2

Accurate Vital Signs Detection Based on FMCW Radar in Dynami...

引用

2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Zhao, Hongtao Yang, Minglei Xing, Ziyang Xing, Ziyi Li, Xiuping Wang, Xueyi Xidian University National Key Laboratory of Radar Signal Processing Xi'an China

ISBN: (纸本)9798331515669

Non-contact vital signs detection plays an important role in smart healthcare. However, most of the existing algorithms focus on stationary environments and the proposed algorithms are computationally intensive. To address the existing problems, this paper proposes the envelope fitting-adaptive fast ensemble empirical mode decomposition (EF-AFEEMD) algorithm. The time-varying DC offset is estimated by fitting the envelope of the signal. Afterwards, the demodulated signal is decomposed into multiple IMFs by adaptively determining multiple parameters of the decomposition. Finally, the appropriate IMFs corresponding to the vital signs signals are selected by calculating the correlation coefficient and local energy ratio (LER) of each IMF. Simulation has validated the effectiveness of the proposed algorithm. Moreover, experimental results have shown that compared to EEMD and FEEMD, the proposed algorithm can ensure accuracy while greatly reducing computation, which is less than half of the computation time of other algorithms. © 2024 IEEE.

关键词： Empirical mode decomposition

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A Chinese-Japanese Parallel Corpus for Neural Machine Translation Based on Web-Crawled News data 2

A Chinese-Japanese Parallel Corpus for Neural Machine Transl...

引用

2nd international conference on signal processing and Intelligent Computing, SPIC 2024

作者： Gao, Zhonghui Zhang, Jinyi Tian, Ye Matsumoto, Tadahiro Shenyang Ligong University Shenyang China Gifu University Gifu Japan Zhuzhou Crrc Times Electric Co. Ltd. Zhuzhou China

ISBN: (纸本)9798350368888

Current research on Japanese-Chinese parallel corpora is limited, particularly in the general field, and existing corpora are often small in scale. The purpose of this study is to fill this gap by constructing a large scale of Chinese-Japanese parallel corpus, sourced from web-crawled online news data. We also evaluated the quality of the constructed Web Crawled Corpus of Japanese and Chinese News (WCC-JCN), which comprised approximately 660K Chinese-Japanese sentence pairs, by calculating its BLEU scores and comparing it with the established ASPEC-JC corpus. The WCC-JCN is made freely available for download, provided it is used for research purposes only, thereby contributing to future research in this area. © 2024 IEEE.

关键词： Neural machine translation

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MEMS Microphone-based Artery Health Monitoring Prototype: A Comparative Analysis with ECG data 2

MEMS Microphone-based Artery Health Monitoring Prototype: A ...

引用

2nd international conference on Sustainable Computing and Smart Systems (ICSCSS)

作者： Mahapatra, Aditya Narayan Sharma, Yash Sandosh, S. Vellore Inst Technol Sch Comp Sci & Engn Chennai Tamil Nadu India

ISBN: (纸本)9798350391558;9798350379990

This research work presents a novel microphone-based approach for evaluating the health status of arteries and heart using a MEMS (Micro-Electro-Mechanical Systems) sensor. It addresses the shortcomings of the current devices for blood pressure monitoring such as the position of the cuff and monitor should be at the same level. If the arterial pulse pressure changes rapidly during measurement, the blood pressure monitor cannot obtain a good reading. The proposed concept acts as an ECG sensor and blood pressure monitor substitute by recording sounds directly from the heart and converting them into a graphical representation. The concept means of realization, and methods of signal processing applied to extract the features of the cardiac sounds-including pulse transit time (PTT)-are described in detail. A side-by-side comparison of our prototype with conventional ECG data reveals that our prototype is dependable and accurate in getting the vital cardiac parameters, however, extensive data comparison is yet to be completed. We cover topics like mobility, non-invasive nature, continuous monitoring capabilities on one side, and disadvantages such as noise reduction and real-world calibration on the other side.

关键词： MEMS(micro-electromechanical system) ECG(electrocardiogram) Cuffless Artery health Blockage Heart Sounds S2 sounds Cardiovascular ESP32 Micro-controller Low energy

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