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检索条件"任意字段=Conference on Adaptive Optical Systems Technology"

共 2006 条记录，以下是21-30 订阅

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Robust adaptive Beamforming based on Reconstruction of Interference Covariance Matrix and Estimation of Steering Vector 16

Robust Adaptive Beamforming based on Reconstruction of Inter...

引用

16th International conference on Signal Processing systems, ICSPS 2024

作者： Zhao, Yan Wang, Yahe Zhang, Haoxuan Xiao, Mengxuan Xue, Wen Hu, Taiyang Xiao, Zelong School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China

ISBN: (纸本)9781510689251

An innovative beamforming strategy, which integrates the reconstruction of the interference-plus-noise covariance matrix (INCM) with the estimation of the steering vector (SV), is proposed in this study. By employing Capon spectral search techniques, the algorithm preliminarily identifies the directions of the signal of interest (SOI) and interfering signals. Considering the uncertainty of array calibration, an annular uncertainty set has been used in this paper to constrain the interference signal's nominal and actual errors of the SV, and Capon spectral integration is performed over this high-dimensional annular surface area. Given the complexity of integral calculations in high-dimensional areas, a discrete summation method has been adopted in this study to approximate the solution of the integral, thereby obtaining the INCM without the SOI. Furthermore, by utilizing subspace characteristics, vertical error vectors are constructed and a neighborhood table of SV errors for the SOI is created in this paper. This table is then used further to optimize the precise estimation of the SOI's SV. Ultimately, the weight vector for robust adaptive beamforming (RAB) is calculated using the corrected SV and the reconstructed INCM. The main advantage of this method lies in its robustness against various unknown mismatches, and it avoids solving the quadratically constrained quadratic programming (QCQP) problem, significantly reducing the complexity and computational demands of the algorithm. Simulation results validate the effectiveness and robustness of the strategy. © 2025 SPIE.

关键词： Vectors

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A Meta-learning-based Online adaptive Fine-tuning VAE for Industrial Process Data Streams 16

A Meta-learning-based Online Adaptive Fine-tuning VAE for In...

引用

16th International conference on Signal Processing systems, ICSPS 2024

作者： Gao, Yu Yu, Wangyang Jin, Huaiping Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Wuhan Maritime Communication Research Institute Wuhan430223 China Yunnan Kunshi Expressway Co. Ltd. Kunming650100 China

ISBN: (纸本)9781510689251

Data-driven deep learning soft sensor has been recognized as an efficient industrial modeling technique for addressing high-dimensional nonlinear problems. However, when confronted with industrial process data streams that simultaneously exhibit high nonlineality and strong time-varying characteristics, offline deep learning models with poor adaptability struggle to achieve accurate quality parameter predictions. To address these challenges, this paper proposes a meta-learning-based online adaptive VAE method for data streams. Specifically, this method introduces a variational autoencoder regression (VAER) model, which incorporates Gaussian distribution constraints into latent variable learning, thereby alleviating the adverse effects of complex variable distributions on predictions. Additionally, a meta-learning algorithm is incorporated into model pre-training to obtain the meta-parameters, thereby enhancing generalization capabilities. Finally, a just-in-time learning fine-tuning update process based on meta-parameters of VAER is completed in online test phase. The effectiveness and practicality of the proposed method are validated through a case study on substrate concentration prediction in the penicillin fermentation process. © 2025 SPIE.

关键词： Just in time production

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An adaptive Pulse Compression SNR Improvement Method based on Single-pulse and Phase Encoded Secondary Measurements 16

An Adaptive Pulse Compression SNR Improvement Method based o...

引用

16th International conference on Signal Processing systems, ICSPS 2024

作者： Jiao, Meijing Gao, Linxing Jiang, Lizhong Yang, Mingyuan Lv, Ruiheng Zhao, Xin Shanghai Radio Equipment Research Institute China Huazhong University of Science and Technology China Shanghai Electro-Mechanical Engineering Institute China

ISBN: (纸本)9781510689251

The Doppler shift in the target echo signal significantly affects the pulse compression effect of the phase-encoded signal, which in turn affects measurements such as distance and velocity. In order to improve the pulse compression signal-to-noise ratio (SNR) of phase-encoded signals in practical applications, a two-stage pulse compression algorithm is proposed in this paper. Firstly, Doppler shift in echo signal is estimated through single-pulse velocimetry, and NCO that subtracts the effect of the Doppler shift is obtained. The phase-coded signal after Doppler signal compensation has higher pulse compression gain, which effectively benefit the radar system. © 2025 SPIE.

关键词： Phase modulation

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Finite-time adaptive command filtering control for manipulators based on disturbance observer 2

Finite-time adaptive command filtering control for manipulat...

引用

2nd International conference on Big Data, Computational Intelligence, and Applications, BDCIA 2024

作者： Liu, Yifan Zhao, Ziyang Zhu, Wenjun Hao, Chongjun College of Mechanical Engineering Taiyuan University of Technology Shanxi Taiyuan China

ISBN: (纸本)9781510689053

In this research, we propose an innovative adaptive command filter control strategy tailored for manipulator systems, incorporating a disturbance observer enhanced by a Radial Basis Function Neural Network (RBFNN). The primary objective is to address the challenges posed by lumped disturbances within the system, which can significantly affect the precision and stability of the manipulator's operation. Initially, the adaptive disturbance observer, augmented with RBFNN, is designed to accurately estimate and compensate for the combined effects of external disturbances and model uncertainties. This integration leverages the non-linear approximation capabilities of RBFNN to capture the complex dynamics of the disturbances, thereby enhancing the robustness of the control system. Subsequently, to further refine the control performance, we introduce a command filter alongside a filter error compensation signal. The command filter is employed to smooth the virtual control signal, mitigating the impact of high-frequency noise and ensuring a more stable control process. Meanwhile, the filter error compensation signal is designed to correct any discrepancies introduced by the filtering process, allowing for the precise computation of the differential signal of the virtual control input. This dual approach not only improves the accuracy of the control signals but also enhances the overall dynamic response of the manipulator system. The theoretical foundation of the proposed control scheme is grounded in Lyapunov stability theory. Through rigorous mathematical analysis, it is demonstrated that the tracking error of the manipulator system converges to zero within a finite time frame. This ensures that the system maintains stable and accurate performance even under varying operating conditions and in the presence of disturbances. To validate the effectiveness of the proposed adaptive command filter control scheme, extensive simulations were conducted. The results clearly indicate

关键词： adaptive filters

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Research on Strain Extraction Method Based on BOTDR Scattering Spectrum 2

Research on Strain Extraction Method Based on BOTDR Scatteri...

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2nd International conference on Engineering of optical systems and Precision Instruments, ICEOP 2024

作者： Xu, Hua Yi, Wensuo Ding, Ruiyang Pang, Qiongjia College of Intelligence Science and Technology National University of Defense Technology Hunan Changsha410073 China College of Optoelectronic Engineering Changchun University of Science and Technology Changchun130022 China Dongfang Jia’ an Environmental Protection Co. Ltd Dongfang China

This study explores a novel signal detection method for a stress-strain sensing system based on the principle of Brillouin backscattering. Currently, signal detection methods in this field face challenges such as high computational load, low accuracy, and poor consistency. This paper proposes the use of the adaptive Gradient Descent Algorithm (Adam) for fitting calculations on Brillouin scattering signals, and it establishes a Brillouin strain measurement system for heterodyne coherent detection. Experimental results indicate that the strain error after applying the Adam method to fit the scattering spectrum curve is 27.60, representing only 59% of the strain error obtained using the Gauss-Newton method, while the error from the Levenberg-Marquardt method is even higher. Additionally, the signal processing time of the Adam algorithm is 18.5 ms, outperforming the other two methods. This approach holds significant practical value for enhancing the precision of data feature extraction in Brillouin scattering sensing technology. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Brillouin scattering

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Optimizing phase parameterization with dynamic pupil size in multi-frame blind deconvolution 4

Optimizing phase parameterization with dynamic pupil size in...

引用

4th International Computational Imaging conference, CITA 2024

作者： Zhang, Haoran Liu, Jin Yang, Huizhe Liang, Yonghui College of Advanced Interdisciplinary Studies National University of Defense Technology Hunan Changsha410073 China Nanhu Laser Laboratory National University of Defense Technology Hunan Changsha410073 China

ISBN: (纸本)9781510688834

Large ground-based telescopes are essential for advancing astronomical observations, as they can capture high-resolution images of distant celestial objects. However, atmospheric turbulence significantly degrades the image quality of these telescopes, introducing distortions that are challenging to correct. While adaptive optics systems are employed to mitigate these effects, their effectiveness diminishes under moderate to strong turbulence, particularly when the ratio of the telescope aperture to the Fried parameter (D/r0) exceeds 20. This limitation underscores the necessity for robust image post-processing techniques, with multi-frame blind deconvolution (MFBD) being one of the most widely used methods. MFBD combines information from multiple blurred frames to restore a clearer image, but the large solution space can make the iterative optimization process unstable. To address this issue, various constraints are often applied, with phase parameterization at the telescope's pupil plane being a common approach for representing the point spread function (PSF). This introduces bandwidth limitations and non-negativity constraints, providing stability. However, traditional phase parameterization methods are prone to getting trapped in local minima during early iterations and require highly accurate initial phase estimates, leading to suboptimal performance under complex conditions. This paper proposes a novel approach to enhance the robustness of MFBD by dynamically adjusting the pupil size during the iterative process. Initially, the algorithm employs a smaller pupil diameter, which is gradually increased as iterations progress. This progressive scaling strategy improves convergence by controlling the PSF bandwidth, reducing the likelihood of the optimization process becoming trapped in local minima, and decreasing the algorithm's sensitivity to initial phase estimates. Experimental results under simulated atmospheric turbulence conditions demonstrate that this dynam

关键词： adaptive optics

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OFDM/OQAM adaptive Pulse Shaping

OFDM/OQAM Adaptive Pulse Shaping

引用

2024 International conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Li, Shiming Zhao, Wenjun Fan, Wanhua Xu, Kangheng Yang, Yuan Li, Tianyu Shanghai Aerospace Electronic Technology Institute Shanghai201108 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Orthogonal frequency division multiplexing (OFDM) capitalizes on the orthogonal properties inherent in various subcarriers to optimize spectral efficiency within the system. This technique stands as the foundational technology for forthcoming wireless communication transmission and multiple access methodologies. Although conventional OFDM systems effectively mitigate multipath interference through the addition of cyclic prefixes (CPs), CP-OFDM systems are not without their limitations: 1) OFDM systems inherently exhibit high sidelobes in the sinc function, rendering them susceptible to frequency offsets;and 2) while this characteristic aids in interference elimination, it concurrently diminishes the system's spectrum utilization. Exploring enhanced multi-carrier modulation schemes has emerged as a paramount research focus within the realm of fifth-generation (5G) mobile communication technology. Instead of limiting themselves to the traditional CP-OFDM design idea of using rectangular functions as prototype pulse filters for pulse shaping, many researchers have introduced waveforms with good time-frequency focusing to improve the subcarrier spectral structure of OFDM systems in terms of the basic structure of the system. Simultaneously, they embarked on a fresh investigation aimed at adjusting the orthogonality conditions of subcarriers and the temporal grid point spacing. Existing studies have shown that the IOTA algorithm has good focusing characteristics in both the time and frequency domains, however, the IOTA function only satisfies the condition of orthogonality in the real domain, which makes it necessary to use the offset quadrature amplitude modulation (OQAM) modulation method for the IOTA function based OFDM system, i.e., pulse-forming based OFDM/OQAM system. In the realm of wireless communication systems, the optimal shaping filter should ideally exhibit rapid roll-off characteristics in both the time and frequency domains. This attribute is crucial for m

关键词： Quadrature amplitude modulation

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Dynamic self-adaptive segmentation of wind speed interval prediction based on fuzzy information granulation 5

Dynamic self-adaptive segmentation of wind speed interval pr...

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5th International conference on Signal Processing and Computer Science, SPCS 2024

作者： Lv, Guanjun Chen, Liangchao Dou, Zhan An, Zhicong College of Mechanical and Electrical Engineering Beijing University of Chemical Technology Beijing100029 China High-Tech Research Institute Beijing University of Chemical Technology Beijing100029 China Zhejiang Academy of Special Equipment Science Hangzhou310000 China Key Laboratory of Special Equipment Safety Testing Technology of Zhejiang Province Hangzhou310000 China

ISBN: (数字)9781510686731

ISBN: (纸本)9781510686724

The accurate prediction of wind speed is of central importance in numerous engineering and environmental disciplines. The reliability of such predictions is of paramount importance in ensuring the safety of building structures and the stability of energy systems. However, traditional wind speed prediction methods are constrained in their ability to handle nonlinear and unstable wind speed data. In light of these considerations, this study proposes a dynamic adaptive segmented wind speed interval prediction method based on fuzzy information granulation, with the objective of enhancing the precision of wind speed prediction and the quality of interval estimation. In light of the nonlinear and non-stationary nature of wind speed data, a FIG-MSS model that integrates fuzzy logic and dynamic time window adjustment is proposed. The model is capable of adaptively capturing the fluctuating characteristics of wind speed data, while the constructed intervals are modeled using LSSVM. The FIG-MSS-LSSVM demonstrates superior performance in PICP, PINAW, and CWC evaluation metrics at confidence levels of 0.9 and 0.95, effectively addressing extreme variations in wind speed data, and providing satisfactory PIs at different confidence levels. The experimental results indicate that the proposed method outperforms the traditional method at varying confidence levels, and is capable of effectively reducing the volatility and uncertainty of the PIs with high prediction stability and accuracy. © 2025 SPIE.

关键词： Wind forecasting

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Optimization technology of ship real-time automation control system based on edge computing 2

Optimization technology of ship real-time automation control...

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2nd International conference on Big Data, Computational Intelligence, and Applications, BDCIA 2024

作者： Wang, Guangfu Wei, Jian CSSC System Engineering Research Institute Beijing100094 China

ISBN: (纸本)9781510689053

The rapid advancements in edge computing have opened new avenues for optimizing real-time control systems in maritime environments. Traditional centralized systems face challenges such as high latency, limited scalability, and dependency on stable network connections, which are particularly critical for ship automation systems. To address these challenges, this study proposes an innovative optimization framework for real-time ship automation control systems based on edge computing. The framework employs a multi-layered architecture, integrating edge, fog, and cloud layers to ensure efficient data processing and task execution. A dynamic task scheduling algorithm is developed to prioritize critical operations, reduce latency, and optimize energy consumption. Additionally, the framework incorporates fault-tolerant mechanisms, including predictive fault detection and redundancy strategies, to enhance system reliability. Scalability is achieved through adaptive resource allocation, allowing the system to handle increasing complexity without significant performance degradation. Experimental results demonstrate the framework's effectiveness in reducing task latency by up to 30%, improving energy efficiency by over 25%, and maintaining high task success rates even under fault conditions. These findings highlight the potential of the proposed framework to improve operational efficiency, reliability, and sustainability in real-time ship automation systems, addressing the unique demands of dynamic and resource-constrained maritime environments. © 2025 SPIE.

关键词： Edge computing

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Range Ambiguous Clutter Suppression and Moving Target Indication for Side-looking Airborne Radar with Vertical Coherent FDA 16

Range Ambiguous Clutter Suppression and Moving Target Indica...

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16th International conference on Signal Processing systems, ICSPS 2024

作者： Lu, Jiahao Zhang, Mengdi Li, Shiyin School of Information and Control Engineering China University of Mining and Technology China

ISBN: (纸本)9781510689251

Under the high pulse repetition frequency (PRF) regime, a serious range ambiguity problem arises in the moving target indication (MTI) radar, leading to a degradation in the performance of traditional space-time adaptive processing (STAP). To address this issue, a range ambiguous clutter suppression and MTI method based on vertical coherent frequency diverse array (FDA) is proposed in this paper. The space-frequency coupling characteristic of vertical coherent FDA is revealed, and a series of two-dimensional (2-D) matched filters are designed to separate range ambiguous clutter and resolve the range ambiguity of targets. After matched filtering, clutter in the desired range region may be contaminated by sidelobes or even mainlobes of clutter from other range regions. To eliminate residual clutter, the azimuth phase coding (APC) technique is applied to induce different Doppler frequency shifts for different range regions. Subsequently, the residual clutter can be eliminated through orthogonal subspace projection (OSP) technique. However, APC also induces a Doppler shift to the target, affecting the accurate acquisition of target information. To this end, Doppler compensation is applied to the echo after the elimination of residual clutter. Finally, traditional STAP is performed on the echoes corresponding to different range regions. Additionally, due to the use of coherent waveforms, it prevents unreal orthogonal waveform assumption in multi-input multi-output (MIMO) framework. Simulation results are provided to validate the effectiveness of the proposed method, demonstrating its capability to enhance the performance of MTI radar under high PRF conditions. © 2025 SPIE.

关键词： Space time adaptive processing

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