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

共 3153 条记录，以下是71-80 订阅

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Enhancing UAV Pitch Angle Measurement Through Radar Cross-Section data and Machine Learning 2

Enhancing UAV Pitch Angle Measurement Through Radar Cross-Se...

引用

2nd IEEE international conference on Image processing and Computer Applications, ICIPCA 2024

作者： Liu, Yuchen Gao, Siqi Wang, Bo School of Information and Electronics Beijing Institute of Technology Beijing102401 China School of Physics and Electronic Information Henan Polytechnic University Jiaozuo454000 China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100088 China

ISBN: (纸本)9798350360240

This study introduces a novel methodology for measuring the pitch angle of Unmanned Aerial Vehicles (UAVs) by leveraging radar cross-section (RCS) data combined with machine learning algorithms. Traditional pitch angle measurement techniques face challenges in accuracy and reliability. Our approach utilizes RCS data as a unique identifier of UAVs' interaction with electromagnetic waves, enhancing the measurement precision of pitch angles. By applying Fourier series for signal analysis and employing machine learning models for pattern recognition, this paper significantly improves the predictability and accuracy of pitch angle measurements under dynamic flight conditions. The methodology's effectiveness is validated through extensive simulations and numerical experiments, demonstrating its superiority over conventional methods. © 2024 IEEE.

关键词： Angle measurement

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Application of Computer databases in Information Management Systems 24

Application of Computer Databases in Information Management ...

引用

2nd international conference on Artificial Intelligence, Systems and Network Security, AISNS 2024

作者： He, Dandan Zeng, Weijia Wang, Congwen Dalian University of Science and Technology Liaoning Dalian China People?s Liberation Army No. 91524 Liaoning Dalian China

ISBN: (纸本)9798400711237

This paper discusses the core features of computer database technology and elaborates on its practical strategies in the field of information management. It aims to optimize information management processes, enhance the application efficiency of computer database technology, ensure the accuracy and efficiency of data processing, and promote the overall optimization and upgrading of information management systems. © 2024 Copyright held by the owner/author(s).

关键词： data accuracy

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2D Resolution Coherent Enhancement of Distributed Spaceborne SAR 2

2D Resolution Coherent Enhancement of Distributed Spaceborne...

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

作者： Yi, Feng Chen, Jianlai Jiang, Nan Central South University School of Automation Changsha China

ISBN: (纸本)9798331515669

Distributed spaceborne synthetic aperture radar (SAR) can discern the intricate details of target structures and precisely characterize them. It uniquely excels in fields like ultra-high-resolution imaging, multi-view coherent fusion, moving target detection, and target recognition. This paper investigates the coherent enhancement of the two-dimensional resolution of SAR in both azimuth and range under distributed spaceborne platforms. In the multi-sub-band distribution pattern of overlapping frequency spectra along the range direction, the joint channel error from overlapping frequency bands is employed to estimate and compensate for inter-sub-band errors, and the bandwidth is synthesized to enhance range resolution coherently. Subsequently, for multi-aperture distribution patterns with azimuthal gaps, a method based on compressive sensing is proposed for sparse recovery of the gap data. This approach effectively elevates azimuth resolution and suppresses spurious targets in the azimuth direction. © 2024 IEEE.

关键词： Compressed sensing

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A Corpus System Study of Oral English Ability Improvement Based on Big data Analysis 2

A Corpus System Study of Oral English Ability Improvement Ba...

引用

2nd IEEE international conference on Image processing and Computer Applications, ICIPCA 2024

作者： Zhang, Hui School of International Education Chengdu Agricultural College Chengdu China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350360240

This paper presents a project that utilizes the WECCL (Chinese learners' oral English level) and COCA (native English speakers' corpus) datasets. Focusing on Chinese English learners and native English speakers, the project combines the SELL corpus with virtual reality to create an English learning and communication network platform. The system's hardware employs an ARM chip as the control center and TDA7498ETR in the sensor component for sound amplification. NRF24L01 is used for reading and writing language data to enrich the database. The platform establishes different output channels for sound signal output through retrieval and editing layers. Experimental results indicate that the developed deep neural network exhibits higher speech diversity, more accurate simulated speech, and stronger generalization in practice. The system facilitates AI character communication in various scenarios, enhancing learners' oral ability and language knowledge. © 2024 IEEE.

关键词： Adversarial machine learning

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Modulation Mode Recognition Method with Multi-feature Fusion under a Complex Noise Floor 2

Modulation Mode Recognition Method with Multi-feature Fusion...

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

作者： Su, Haoran Zhou, Fan Lv, Pengfei Shenyang Ligong University School of Information Science and Engineering Shenyang China

ISBN: (纸本)9798350368888

Increasing the accuracy of modulation signal recognition in a generalized noise environment is an important problem nowadays. To address this problem, a deep neural network-based modulation mode recognition method FF-net (Feature Fusion net) is proposed in a generalized noise environment. The method firstly extracts and fuses the constellation map features and time domain features of the signal, which increases the diversity of feature extraction;then the Res2Net module and SENet module are used to realize the extraction of channel attention and spatial multi-scale features, which improves the validity and versatility of the feature extraction, and thus improves the recognition accuracy of the modulation mode recognition system in different noise environments. The experimental results show that its average recognition rate reaches 99.5% under the condition of α=0 signal-to-noise ratio of 0~10dB, and 86.1% under the condition of α=2 signal-to-noise ratio of 0~10dB, which is better than other existing algorithms under the same conditions. © 2024 IEEE.

关键词： signal modulation

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Detecting and Classifying the Vehicles in Traffic signal Using Transfer Learning 2nd

Detecting and Classifying the Vehicles in Traffic Signal Usi...

引用

2nd international conference on signal and data processing, icsdp 2022

作者： Valli, Shaik Kumar, K. Nithin Sai Nath, K. Kartheek Prabhakaran, K. Manoj Amrita School of Engineering Chennai Campus Chennai India

ISBN: (纸本)9789819914098

In existing methods, there are different machine learning techniques carried out for detecting and classifying the vehicles. But in real world scenario, their validation performance is not that good. Also, the vehicles are not detected accurately, and detection rate is slow in real time implementation. To overcome this issue, we used a deep learning technique to speed up the process of detecting the vehicles and classifications. Moreover, different deep learning techniques are used for the vehicle’s detection and classifications. Some of the two major techniques include one stage object detector like YOLO V4, SSD, Detect Net, Retina Net, and 2 stage object detectors like RCNN, Fast RCNN, and Faster RCNN. Among all these YOLO V4 is a recent super-fast model and is best for real time applications for object detections. In this paper, we implemented the transfer learning techniques as YOLO V4 for detecting and classifies the huge numbers of vehicles at traffic signals. Using this technique, we achieved 80.01% accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Object detection

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Deep MVDR: A High Resolution DoA Estimation Method against Array Gain-Phase Error 2

Deep MVDR: A High Resolution DoA Estimation Method against A...

引用

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

作者： Luo, Yiwei Yang, Chengzhu Jiao, Yuchen Xu, Lijun Beijing Institude of Technology School of Information and Electronics Beijing China

ISBN: (纸本)9798331515669

Direction of Arrival (DoA) estimation is a critical issue in array signal processing, and several classical methods such as Minimum Variance Distortionless Response (MVDR) and Multiple signal Classification (MUSIC), have been proposed to solve this problem and have achieved remarkable results. However, these DoA estimation methods suffer performance degradation under model mismatches such as gain-phase errors. Deep learning (DL) methods have strong capability to learn the mapping from received data to true angles directly, achieving notable performance in model mismatches scenarios, but their performance tends to degrade in different SNRs or snapshots scenarios. To address these issues, a high-resolution DoA estimation method named Deep MVDR is proposed in this paper, which consists of covariance-enhanced autoencoder, DoA estimator and super resolution modules. These modules can utilize the feature extraction capabilities of neural networks to improve performance and refine spatial spectrum. Simulation results demonstrate the correctness and effectiveness of the proposed method across various target numbers, SNRs and snapshots with gain-phase errors, and show that Deep MVDR outperforms other existing methods in terms of spatial resolution. © 2024 IEEE.

关键词： signal to noise ratio

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Multi-scale Feature Extraction Channel Equalization Method Based on Res2net Module 2

Multi-scale Feature Extraction Channel Equalization Method B...

引用

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

作者： Wang, Yi Zhou, Fan Su, Heng Shenyang Ligong University School of Information Science and Engineering Shenyang110159 China

ISBN: (纸本)9798350368888

Under the condition of time-varying multi-path channel, to address traditional channel equalization methods cannot effectively eliminate Inter Symbol Interference, a multi-scale feature extraction channel equalization method based on Res2net module is proposed. The method adopts Res2net network technology, firstly, multi-scale feature extraction is carried out in the high dimensional space for the components of the received signal that are subject to ISI, then the reconstruction of the interference signal is completed by the extracted multi-scale features, and finally, based on the idea of residual difference, the reconstructed interference signal is used to correct and compensate the received signal in order to achieve the channel equalization, which reduces the bit error rate of the communication system and improves the reliability of the transmission of the communication system. Simulation results show that, compared with the traditional channel equalization method, the proposed method reduces the bit error rate by 6% in the Gaussian white noise channel environment and 3% in the colored noise channel environment under the multi-path Rayleigh channel. © 2024 IEEE.

关键词： Bit error rate

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A Simulation-Based Post-processing for Layover Unmixing Using 2d Range-Elevation Spectrum 2

A Simulation-Based Post-Processing for Layover Unmixing Usin...

引用

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

作者： Yu, Lei Hu, Fengming Shanghai China

ISBN: (纸本)9798331515669

SAR is an active microwave imaging system, known for its unique ability to provide high-resolution images under various weather conditions. Geometric distortion is a significant factor affecting the application of SAR, particularly in complex terrains or densely built-up areas. TomoSAR utilizes multi-baseline acquisitions to eliminate layover and achieve accurate three-dimensional reconstruction of the scene. However, the performance of TomoSAR heavily depends on the number of acquisitions, which can be a limiting factor. In this paper, we proposes a new way for layover unmixing with limited single-pass SAR acquisitions. The method involves simulating typical layover scenarios to generate a range-elevation spectrum, followed by layover mitigation processing. Specifically, point targets overlapped in a single pixel are separated by applying linear fitting to the data. Experimental results demonstrate that the proposed method can separate layover targets and reconstruct their 3D point clouds in various layover scenarios. This method providing a new solution for improving the quality of 3D reconstruction in complex scenarios. © 2024 IEEE.

关键词： Miocene

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Improvement of reconstruction accuracy for hardware systems with Finite Rate of Innovation 2

Improvement of reconstruction accuracy for hardware systems ...

引用

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

作者： Wang, Jingyu Ding, Li Zhou, Tao University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai China

ISBN: (纸本)9798331515669

In classical Finite Rate of Innovation (FRI) theory, signal reconstruction is initially achieved with precision using the zeroing filter algorithm on noiseless pulse signals. However, with the introduction of noise, the zeroing filter algorithm exhibits reduced robustness when handling signals with low signal-to-noise ratios (SNR). This paper introduces the TLS-ESPRIT algorithm, which enhances robustness against noise to some extent. Additionally, building on the development of an FRI reconstruction system based on C-TEM sampling, this work innovatively proposes a cascaded filter phase compensation method. This method mitigates the nonlinear phase effects of analog filters, thereby improving reconstruction accuracy. Ultimately achieving a reduction in sampling rate while improving reconstruction accuracy. © 2024 IEEE.

关键词： signal to noise ratio

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