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检索条件"机构=Beijing Key Laboratory of Embedded Real-time Information Processing Technology Radar Research Lab"

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real-time Remote Sensing Video Compression for On-orbit Heterogeneous Platform

Real-time Remote Sensing Video Compression for On-orbit Hete...

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2019 IEEE International Conference on Signal, information and Data processing, ICSIDP 2019

作者： Duan, Chenhui Tang, Linbo Li, Chen Wu, Chen Li, Cheng Zhao, Baojun Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China School of Computer Science North China University of Technology Beijing100144 China

ISBN: (纸本)9781728123455

With the rapid advancement of optical remote sensing (RS) satellites, RS video has replaced RS image as the main way to obtain information in orbit environment. However, the storage and transmission of on-orbit RS video faces enormous challenges: the contradiction between limited power, space and bandwidth and massive video data volume is becoming increasingly acute. To solve this problem, this paper proposes an effective implementation of spaceborne real-time RS video compression based on CPU+GPU heterogeneous framework. First, we propose a new rate control method based on HEVC for on-orbit RS video compression, which allocates less bitrate for low complexity code blocks (CBs) and more bitrate for high complexity CBs, which can improve the accuracy of rate control algorithm while ensuring compression quality. Then this paper makes full use of the CPU + GPU heterogeneous framework to speed up the whole compression processing. The experimental results show that the proposed compression framework realizes 200x real-time compression of 1080p spaceborne RS video with a PSNR greater than 38.7 dB. © 2019 IEEE.

关键词： Orbits

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SAR TOMOGRAPHY IN URBAN AREAS: AN APPROACH BASED ON SPARSE SPECTRUM FITTING

SAR TOMOGRAPHY IN URBAN AREAS: AN APPROACH BASED ON SPARSE S...

引用

IET International radar Conference 2023, IRC 2023

作者： Zhao, Jian Wang, Zhen Ding, Zegang Sun, Tao Chen, Zhizhou Chen, Haolong Zeng, Tao 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 Chongqing Innovation Center Beijing Institute of Technology Chongqing401331 China

ISBN: (纸本)9781839539954

Tomography Synthetic Aperture radar (TomoSAR) technology, as an extension of Interferometric SAR (InSAR), solves the inherent layover problem and provides three-dimensional (3D) imaging ability. Now, it is a promising technique in urban management and critical situation detection. However, in practical applications, the sparse and non-uniform distribution characteristics of the repeat-pass baselines make TomoSAR face the problem of low resolution and high sidelobes, which affect the 3D imaging effect. To address the above problems, a sparse spectrum fitting (SpSF) based TomoSAR processing approach is proposed in this paper. Compared with the traditional spatial spectrum estimation method, this method can achieve higher resolution and lower sidelobes, which is a significant advantage. The proposed method is also validated using computer simulation and the TerraSAR-X real data. © The Institution of Engineering & technology 2023.

关键词： radar imaging

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Deep forest for radar HRRP recognition

Deep forest for radar HRRP recognition

引用

IET International radar Conference 2018, IRC 2018

作者： Wang, Yanhua Bi, Xuejie Chen, Wei Li, Yang Chen, Qiao Long, Teng 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 Racobit Radar Technology Research Institute Co. Ltd. Beijing China

High-resolution range profile (HRRP) has received intensive attention in the radar automatic target recognition filed. Here, deep forest is applied to the recognition of HRRP. The deep forest is a deep learning method, which is a cascade of ensemble learners. In each layer, there are various ensemble learners. The input of each layer is the combination of the previous layer output and the original input data. The number of cascade levels can be adaptively determined such that the model complexity can be automatically set. Experiments based on measured data show that deep forest is feasible and achieves highly competitive performance for HRRP recognition. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Deep learning

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Modefied keystone processing algorithm for the space-based bistatic radar systems

Modefied keystone processing algorithm for the space-based b...

引用

IET International radar Conference 2015

作者： Feng, Wenling Wei, Wei Liu, Feifeng Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China No.203 Research Institute of China Ordnance Industries China

ISBN: (纸本)9781849199940

The bistatic keystone processing algorithm was presented in the paper to increase the coherent integration time of the echo signal scattered from the moving target in the space-based bistatic radar systems. The high speed of receiver has a severe impact on the target detection of the system. Therefore, the echo of the central target was selected as the reference signal to remove the undesired impact of receiver in the target detection of space-based bistatic radar systems. The simulation results validate the proposed algorithm.

关键词： Phase space methods

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Lightweight convolutional neural network for false alarm elimination in SAR ship detection 5

Lightweight convolutional neural network for false alarm eli...

引用

IET International radar Conference 2020, IET IRC 2020

作者： Zheng, Xingfei Feng, Yangkai Shi, Hao Zhang, Bocheng Chen, Liang Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Shanghai Institute of Satllite Engineering Shanghai China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839535635

SAR ship detection is an important task of SAR image interpretation and plays a significant role in global marine surveillance. However, since there are usually many false alarms in the detection results, a desirable performance is rarely achieved. Aiming at this problem, this paper proposes an improved method for the ship detection process, using the lightweight convolutional neural network EfficientNet-B0 as a false alarm elimination network, cascaded after the detection stage, to reduce the false alarm rate in the detection results and improve the overall detection accuracy. The results on the MSTAR data set show that EfficientNet-B0 has a good classification effect, and the experiments on the custom data set also verify the effectiveness of the network. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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Cascaded Kalman filter for target tracking in automotive radar

Cascaded Kalman filter for target tracking in automotive rad...

引用

IET International radar Conference 2018, IRC 2018

作者： Li, Yang Liang, Can Lu, Man Hu, Xueyao Wang, Yanhua 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 China Beijing Racobit Electronic Information Technology Co. Ltd. Beijing China

In automotive anti-collision radar system, the accuracy of velocity is one of the key indicators to measure radar performance. For frequency modulation continuous wave radar with chirp sequence, which is commonly used in automotive radar, there are two problems that are velocity ambiguity and measurement error. In order to address these problems, a cascaded Kalman filter algorithm is proposed in this article, which is able to overcome velocity ambiguity and improve the accuracy of measurements. In addition, the problem of velocity ambiguity can be solved just in the data processing and it avoids transmitting staggered or multiple pulse repetition frequency signal. The simulation results show that this algorithm can effectively improve the tracking performance. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Data handling

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A Quantitative Estimation Method of Migrating Insects Using Weather radar by High Resolution radar Joint Observation

A Quantitative Estimation Method of Migrating Insects Using ...

引用

IET International radar Conference 2023, IRC 2023

作者： Li, Jiayi Cui, Kai Hu, Cheng Wang, Rui Mao, Huafeng Radar Research Laboratory School of Information and Electronics Beijing Institute of Technology Beijing100081 China Key Laboratory of Embedded Real-time Information Processing Technology Radar Research Laboratory School of Information and Electronic Beijing Institute of Technology Beijing100081 China School of Computer Sciences Beijing Institute of Technology Beijing100081 China Advanced Technology Research Institute Beijing Institute of Technology Jinan250300 China

ISBN: (纸本)9781839539954

The main migration animals in China are insects, and a large number of large-scale seasonal migration insects have a great impact on ecology. The establishment of a comprehensive early warning system for migratory insects necessitates the implementation of large-scale macro monitoring. Among the array of methodologies available, weather radar stands out as an efficacious tool for facilitating extensive macro-level monitoring. Nonetheless, several unresolved challenges persist in accurately quantifying the density of vast insect populations on a large scale. This article introduces an innovative method for insect quantification through the collaborative use of weather radar and high-resolution phased array radar for insect target observation and joint data analysis. This novel method harnesses the collective observational data derived from both weather radar and high-resolution radar systems, harmonizing the temporal and spatial dimensions of these datasets. By establishing a nuanced mapping correlation between insect density and weather radar reflectivity, this method enables the determination of insect density within specific geographical regions. In the final part of this article, joint observation experiments were conducted to examine the experimental data collected from operating weather radar and specialized phased array radar systems. A total of 244 days of data were analysed, and the proposed method was rigorously validated. © The Institution of Engineering & technology 2023.

关键词： radar reflection

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research on a Method of realizing High Performance Ultra-Long Pulse Compression Processor Based on FPGA

Research on a Method of Realizing High Performance Ultra-Lon...

引用

IET International radar Conference 2023, IRC 2023

作者： Wu, HongHao Qiao, TingTing Chen, He Xie, YiZhuang Li, YongRui 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 Yangtze Delta Region Academy of Beijing Institute of Technology Zhejiang Jiaxing314019 China

ISBN: (纸本)9781839539954

Pulse compression plays a vital role in radar signal processing. With the rapid development of synthetic aperture radar (SAR) imaging technology, the demand for spaceborne SAR imaging processing is becoming more and more urgent, especially the need to support the real-time application of ultra-long pulse compression accelerators. However, limited on-chip resources and memory access bandwidth have always been key bottlenecks restricting the design of ultra-long pulse compression processing. FPGA is widely regarded as a processor that is both highly parallelized and has excellent computing speed. Therefore, this research is committed to proposing a new processor design method based on FPGA to cope with ultra-long point pulse compression processing. First, to be able to effectively handle ultra-long sequence pulse compression up to 1M points, we propose an architecture with careful optimization. Secondly, in order to improve processing efficiency and reduce resource overhead, we propose a fixed-point data fitting implementation strategy. Finally, this study also explores an on-chip storage optimization method for reference function spectrum for linear frequency modulation (LFM) signals, which not only effectively reduces the cost of on-chip resources, but also saves storage transmission bandwidth. These innovative designs and optimization strategies will provide strong support for further development in the field of ultra-long-point pulse compression processing. © The Institution of Engineering & technology 2023.

关键词： Bandwidth compression

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An Improved Method for Rockfall Detection and Tracking Based on Video Stream

An Improved Method for Rockfall Detection and Tracking Based...

引用

IET International radar Conference 2023, IRC 2023

作者： Wang, Longyue Wang, Songge Xie, Xin Deng, Yunkai Tian, Weiming Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Chongqing Innovation Center Beijing Institute of Technology Chongqing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Jinan China

ISBN: (纸本)9781839539954

Rockfall events occur frequently in mountainous areas. To address the problems of missed detection, false detection, and trajectory interruption when using the deep learning-based online multiple object tracking methods to detect rockfalls, this paper proposes a rockfall detection and tracking method based on video streams. In the detection stage, three-frame difference method is utilized to obtain the moving targets from the video streams, and they are combined with the detection results of the rock detector obtained by the offline-trained YOLOX model. In the tracking stage, data association is firstly performed based on the rockfall detection results. For the existing trajectories that are not matched at the current moment, re-matching is performed by combining the moving object detection results to achieve accurate tracking of rockfalls. Simulations and field experiments prove that the detection method proposed in this paper can effectively separate the rockfalls in the video, and the detected rockfalls have high precision. Besides, it significantly improves the accuracy of rockfall tracking, effectively suppressing phenomena such as trajectory interruption during tracking. © The Institution of Engineering & technology 2023.

关键词： Rock bursts

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Airfield detection based on JPEG2000 compressed domain

Airfield detection based on JPEG2000 compressed domain

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IET International radar Conference 2018, IRC 2018

作者： Duan, Chenhui Zhao, Baojun Tang, Linbo Li, Cheng Li, Chen Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China Information Security Laboratory School of Information North China University of Technology Beijing100093 China

With the rapid increase of optical remote sensing (RS) images, on-orbit specific target detection has been facing more and more challenges: limited processing environment, wireless bandwidth, space, power and storage. To resolve this issue, visual characteristics in the compressed domain are exploited to represent and recognise specific objects. In this study, a new saliency method and an airfield detection framework in the JPEG2000 compressed domain is proposed. First, the authors exploit the header information in raw JPEG2000 code streams to generate structural saliency map, and a great deal of nonstructural regions in RS images are eliminated. Second, airfield candidates are extracted from low frequency wavelet sub-bands using line segment detection and the parallel density model. Finally, the geometrical properties of airfield candidates are represented by the speed-up robust features descriptor, and the support vector machine classifier is utilised to gain the final detection results. The proposed framework is evaluated on self-made dataset. Compared with the existing relevant state-of-the-art approaches, the proposed method reduces the processing time by 60% while guaranteeing the detection rate. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Optical remote sensing

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