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检索条件"机构=Beijing Key Laboratory of Real-Time Information Processing Technology of Embedded"

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Uncertainty-Aware Dynamic Learning for Cross-Domain Few-Shot Scene Classification from Remote Sensing Imagery

Uncertainty-Aware Dynamic Learning for Cross-Domain Few-Shot...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Can Li He Chen Yin Zhuang Shanghang Zhang Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing China School of Computer Science Peking University Beijing China

Cross-domain few-shot scene classification (CDFSSC) is devoted to transferring knowledge from the source domain to the target domain and facilitating few-shot classification for the target domain. However, due to the domain shifts between source and target domains, high uncertainty would be generated in the knowledge transfer process, leading to unreliable cross-domain learning, which degenerates classification performance on the target domain severely. Thus, in this paper, aiming to reduce the interference of high uncertainty and improve the reliability of cross-domain knowledge transfer, a novel uncertainty-aware dynamic learning (UDL) framework is proposed for CDFSSC from remote sensing imagery. First, a mean-teacher architecture combining pseudo-labeling and consistency regularization is utilized to achieve cross-domain learning. Second, a UDL strategy is proposed to divide data into positive and negative samples based on a well-designed uncertainty-aware dynamic threshold, conducting positive and negative learning respectively, to advance a more reliable knowledge transfer. Third, to further improve cross-domain capability, a self-entropy loss is designed to reduce the epistemic uncertainty of the model. Extensive experiment results indicate the superiority of our proposed methods.

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Robust Adaptive OS-CFAR Detector for Maneuvering Group Target Based on Formation Prior Knowledge

Robust Adaptive OS-CFAR Detector for Maneuvering Group Targe...

引用

Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Mengxin Shi Qi Jiang Rui Wang Radar Technology Research Institute School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Real-Time Information Processing Technology of Embedded Beijing China The Advanced Technology Research Institute Beijing Institute of Technology Jinan China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Detecting the individuals such like the bird flocks or a UAV swarm is a great challenge for radar systems. The lack of prior knowledge about the characteristics of dynamic group targets leads to the performance degradation of conventional detectors. In this study, we present a robust adaptive OS-CFAR detector for maneuvering group targets, leveraging prior knowledge of their formation. The group target’s state is updated and predicted using the random matrix approach. The projection length of the group target in the radar beam direction is computed using the predicted information during the group target tracking process. Using the projection length, the number of reference units occupied by the group target within the reference window is determined, and this prior knowledge is applied to update the detection parameters of the OS-CFAR detector. The simulation result shows that the algorithm can update the detection parameters timely and avoid target missed detection.

关键词： Target tracking Simulation Radar detection Detectors Radar Radar tracking Prediction algorithms time measurement real-time systems Motion measurement

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Improved Clutter Suppression Method for Bridge Vibration Measurement Based on GB-MIMO Radar 2

Improved Clutter Suppression Method for Bridge Vibration Mea...

引用

2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Gao, Jiake Wang, Jian Wang, Siqi Qu, Xinran Li, Wenyu Deng, Yunkai Radar Technology Research Institute Bejing Institute of Technology Beijing China Beijing Building Research Institute Corporation Limited Cscec Beijing China Beijing Key Laboratory of Embedded Realtime Information Processing Technology Radar Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9798331515669

Ground based multi-input multi-output (GB-MIMO) radar has been gradually applied in the field of bridge vibration monitoring. During measurement, the interference of static clutter on the vibrating target signal in the same azimuth and range resolution severely affects the vibration measurement. The traditional method of removing static clutter is to estimate static clutter by fitting a circular curve to a complex signal point set, that is, fitting the vector of the circular curve center deviating from the origin of the polar coordinate system. Due to the clustered distribution of vibration points during non vibration time, the trajectory of complex sequence point sets will be distorted, resulting in poor clutter suppression effect. This article proposes an improved method for measuring the dynamic deflection of bridges by suppressing clutter. Firstly, obtain the vibration time period of the vibration candidate points through time-frequency analysis. Secondly, extract the complex sequence of each pixel during the vibration time period, and use the circular trace fitting method to estimate the stationary clutter. Then, based on outlier degree and outlier rate evaluation indicators, select vibration measurement pixels that can achieve effective clutter suppression. The effectiveness of this method was preliminarily verified by comparing the dynamic deflection curves of millimeter wave radar and laser vibrometer through model bridge experiments. In addition, the method was also validated through a high-speed railway bridge experiment. © 2024 IEEE.

关键词： Vibration measurement

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An Adaptive Estimation Method for Group Target Number Based on information Theoretic Criterion

An Adaptive Estimation Method for Group Target Number Based ...

引用

Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Libin Dou Qi Jiang Rui Wang Mengxin Shi Jichuan Zhang Radar Technology Research Institute School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Real-Time Information Processing Technology of Embedded Beijing China The Advanced Technology Research Institute Beijing Institute of Technology Jinan China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

The number of individuals within a group is crucial information for the correct association, robust tracking, and situation awareness. Traditional methods using the range profile’s peaks are not suitable when targets are densely distributed. The target number estimation algorithms based on monopulse systems have high computational complexity, while those based on array systems require additional sensor resources. To address these issues, this paper proposes a method based on multiple incoherent observations using one monopulse radar. By combining multiple incoherent observations from a single sensor with information theoretic criterion, this approach can estimate the number of targets even when the resolution of a single sensor is insufficient. The effectiveness of the algorithm is verified through simulations, and the algorithm's performance is analyzed.

关键词： Analytical models Target tracking Estimation Radar Radar tracking Data processing Adaptive estimation Computational complexity Signal resolution Sensor arrays

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Labeled Random Finite Sets-Based Group Target Tracking with Multi-Detection Model

Labeled Random Finite Sets-Based Group Target Tracking with ...

引用

Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Longxiang Jiao Qi Jiang Rui Wang Radar Technology Research Institute School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Real-Time Information Processing Technology of Embedded Beijing China The Advanced Technology Research Institute Beijing Institute of Technology Jinan China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

In radar tracking applications for low-altitude group targets (such as bird flocks or drone swarms), the traditional point target measurement model is often unsuitable due to the complex micro-Doppler signatures and multipath effects. Algorithms based on labeled random finite sets (RFS) challenges with multi-detection problems. This paper presents a new method for tracking low-altitude group targets using labeled RFS in radar systems. To mitigate the disturbance from multi-detection, we propose modified assignment cost matrices in the update process, which reduces the number of false associations, and thus achieves quality enhancement of trajectory estimations. The effectiveness of the proposed method is validated through simulation results.

关键词： Radio frequency Target tracking Costs Simulation Estimation Radar Radar tracking Trajectory Reliability Standards

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An improved 3-D reconstruction method based on deep neural network 14

An improved 3-D reconstruction method based on deep neural n...

引用

14th European Conference on Synthetic Aperture Radar, EUSAR 2022

作者： Zhang, Tianyi Ding, Zegang Liu, Siyuan Wei, Yangkai Wang, Guanxing Zhang, Yan Guo, Xin Gao, Yongpeng Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China DFH Satellite Co. Ltd Beijing China

ISBN: (纸本)9783800758234

Current three-dimensional (3-D) reconstruction methods based on two-dimensional (2-D) inverse synthetic aperture (ISAR) image sequences usually consist of some sequential nonlinear steps, and they face with the error accumulation and transmission inevitably. To realize precise target reconstruction, an improved 3-D reconstruction method based on motion parameters and deep neural network (DNN) is proposed. The proposed method could realize the end-To-end transformation from the motion parameters to the 3-D target via DNN, and the error transmission and accumulation can be avoided. Results based on the synthetized data set validate the proposed method. © 2022 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Deep neural networks

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Improved multiple hypothesis tracking using incomplete measurements for group targets

Improved multiple hypothesis tracking using incomplete measu...

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Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Na Ni Qi Jiang Cheng Hu Radar Technology Research Institute School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Real-Time Information Processing Technology of Embedded Beijing China The Advanced Technology Research Institute Beijing Institute of Technology Jinan China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Tracking targets within a group has received much attention in the radar field recently years. Group targets are usually closely spaced with similar velocity, making it hard to distinguish multiple targets. For precise target tracking, the tracking radar usually employs a narrow beam to achieve the high range-angular resolution. However, targets may enter and exit the narrow beam frequently during the observation, bringing difficulty for stable tracking. Moreover, it is also hard to distinguish different targets when their tracks intersect on the range-doppler plane. These kinds of incomplete measurements increase the difficulty of group targets' association and tracking. Therefore, this paper proposes an improved multiple hypothesis tracking method using incomplete measurements. The adaptive detection probability model and track intersecting probability are combined in the multiple hypothesis tracking framework to reduce false associations and improve tracking performance. Finally, simulation and experiment results verified the effectiveness of the proposed method.

关键词： Adaptation models Target tracking Accuracy Radar Radar tracking Data processing Data models

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A Long-Term Joint Multi-Image Computerized Ionospheric Tomography Method Based on GEO SAR System

A Long-Term Joint Multi-Image Computerized Ionospheric Tomog...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Yi Sui Xichao Dong Yuanhao Li Zhiyang Chen Cheng Hu Beijing Key Laboratory of Embedded Real-Time Information Processing Technology (Beijing Institute of Technology) Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China Advanced Technology Research Institute Beijing Institute of Technology Jinan China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Computerized Ionospheric Tomography (CIT) serves as a crucial method for ionospheric monitoring, playing a significant role in space environment surveillance and earthquake prediction. Existing CIT techniques are mostly based on the Global Navigation Satellite System (GNSS) system, constrained by the distribution of receivers. CIT based on geosynchronous SAR (GEO SAR) presents a solution by leveraging Persistent Scatterer (PS) points within the scene. However, current CIT techniques using GEO SAR typically utilize PS points from a single SAR image. This paper introduces a novel approach – a GEO SAR-based long-term joint multi-image CIT method. This method enhances the exploitation of satellite data, offers a broader range of observation angles, and improves tomography accuracy. Finally, through a CIT experiment involving three GEO SAR images, the electron density distribution is derived with a time resolution of 10 minutes. The results align with the International Reference Ionosphere (IRI) data, validating the feasibility and advantages of the proposed method. It is noteworthy that the proposed method caters to the tomography observation mode of a single satellite and is adaptable to each satellite within a satellite formation.

关键词： Global navigation satellite system Satellites Accuracy Surveillance Receivers Tomography Radar polarimetry

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An improved ISAR imaging method under low SNR 14

An improved ISAR imaging method under low SNR

引用

14th European Conference on Synthetic Aperture Radar, EUSAR 2022

作者： Gao, Yongpeng Ding, Zegnag Zhang, Tianyi Liu, Shujiang Guo, Xin Li, Pucheng Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401147 China DFH Satellite Co. Ltd Beijing100094 China

ISBN: (纸本)9783800758234

Current inverse synthetic aperture radar (ISAR) imaging methods cannot perform well when the signal-To-noise ratio (SNR) is low. In this paper, an improved ISAR imaging method based on generalized Radon-Fourier transform (GRFT) and relaxation (RELAX) technique is proposed. Through the proposed method, a well-focused radar image of moving target under low SNR condition can be obtained. Further, the estimation error caused by off-grid points as well as the unnecessary side lobe and main lobe values introduced by GRFT based ISAR imaging can be solved. Simulations are conducted to verify the effectiveness of the proposed method. © 2022 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Inverse synthetic aperture radar

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Fast processing Techniques for Ground-Based Differential Interferometric Radar Based on embedded GPU 2

Fast Processing Techniques for Ground-Based Differential Int...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Qi, Jingshuang Wang, Jian Li, Xiaoxiao Wang, Longyue Deng, Yunkai Tian, Weiming Bejing Institute of Technology Radar Technology Research Institute Beijing China Corporation Limited of Cscec Beijing Building Research Institute Beijing China Beijing Key Laboratory of Embedded Realtime Information Processing Technology Radar Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China Beijing Institute of Technology Advanced Technology Research Institute Jinan China

ISBN: (纸本)9798331515669

For ground-based differential interferometric radar systems, aiming at the problems of low operation-speed performance, a rapid processing technology was studied based on embedded GPU. To achieve effective processing of high-speed data streams, an architecture design based on message queues is adopted in this paper, enabling parallel data transmission and processing. Message queue, as an efficient middleware technology, not only ensure reliable data transmission but also enable decoupling of data reception and processing through an asynchronous communication mechanism. This significantly enhances the system's throughput and response speed. To further optimize performance, condition variables are introduced to control the concurrency strategy in the message queue. When there is data to be processed in the message queue, the condition variable wakes up waiting threads to start processing messages;when there is no data to be processed, it suspends the threads. This mechanism ensures the maximization of system resource utilization. Parallel reduction techniques based on shared memory are adopted to achieve rapid selection of persistent scatterer. Shared memory reduces data access times, and the use of parallel reduction techniques is particularly effective when handling large-scale datasets. The results show that for 200 images with dimensions of 634 by 100 pixels, the method presented in this paper improves the processing speed by 16% compared to traditional methods, effectively enhancing the processing efficiency of ground-based differential interferometric radar systems. © 2024 IEEE.

关键词： Concurrency control

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