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

共 205 条记录，以下是51-60 订阅

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Generation scheme of chirp scaling phase functions based on floating-point CORDIC processor

Generation scheme of chirp scaling phase functions based on ...

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IET International radar Conference 2018, IRC 2018

作者： Fang, Linlin Xie, Yizhuang Li, Bingyi Chen, He 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

This study presents a chirp scaling (CS) phase function generation scheme based on CORDIC algorithm, it adopts single precision floating-point CORDIC processor to implement a variety of non-linear operations which are involved in CS synthetic aperture radar (SAR) imaging algorithm. We extend the range of convergence of CORDIC algorithm and reduce the data width in rotation unit module by adopting a hardware resource reduction scheme. We also adopt a unified CORDIC processor to achieve square root, multiplication, and division operation, which can substitute multiple single-function processors and simplify the complicate arithmetic in CS algorithm. As a proof of concept, we verify the performance of the proposed design scheme on Xilinx XC7VX690T FPGA platform, it is also applied to 16384 × 16384 points target SAR imaging system, the FPGA resource occupancy of the CS phase function generation module demonstrates that the usage of CORDIC processor can effectively save the consumption of hardware resources, and the maximum operating frequency is acceptable. The accuracy of phase functions can satisfy the engineering requirements. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Field programmable gate arrays (FPGA)

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Multi-sensor Image Stitching and Fusion Based Air Infrared Target Cooperative Detection

Multi-sensor Image Stitching and Fusion Based Air Infrared T...

引用

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

作者： Nan, Jinghong Zhao, Baojun Cui, Tingting Xie, Yongfeng 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 Institute of Aerospace Systems Engineering Beijing China

ISBN: (纸本)9781728123455

Robust and efficient air infrared small target detection is widely used in reconnaissance and early warning system. However, there exist two critical difficulties, i.e., the limited detection range and the poor detection performance of single infrared sensor. To overcome those difficulties, in this paper, we propose a novel cooperative detection method of multiple infrared sensors for air small target. Specifically, a multiscale block local contrast measurement method is introduced to achieve the target detection of each infrared sensor. Afterwards, a double-layer ring grid corner feature extraction method is proposed to achieve the image stitching accurately between multiple infrared sensors. In addition, the gray correlation analysis with position constraint based feature level fusion method is exploited to match targets in different sensors. Experimental results on testing image sequences demonstrate that the proposed method can improve the detection rate and reduce the false alarm rate effectively on the condition of limited detection range of each single sensor. © 2019 IEEE.

关键词： Image enhancement

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research on SAR Image Matching Based on SAR-Harris Detector and Adaptive Locally-Affine Matching

Research on SAR Image Matching Based on SAR-Harris Detector ...

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IET International radar Conference 2023, IRC 2023

作者： Wu, Guanghui Shi, Hao Chen, Fan Pan, Hongxin Chen, Liang 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 Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839539954

Synthetic aperture radar (SAR) image matching is an essential step in SAR image processing. The synthetic aperture radar-scale invariant feature transform (SAR-SIFT), which combines the ratio of exponentially weighted averages (ROEWA) operator with multiscale Harris detection and employs Random Sample Consensus (RANSAC) for matching and filtering, has shown promising results. However, SAR-SIFT suffers from low matching efficiency in specific scenarios, and RANSAC exhibits strong randomness and potential problems of non-convergence. To address these problems, this paper introduces an approach that combines scale-space layers reduction in the SAR-Harris detector with the efficient Adaptive Locally-Affine Matching (AdaLAM) to enhance SAR image matching performance. The proposed SAR-SIFT-AdaLAM method is experimentally evaluated on two sets of different SAR images for matching, and the results indicate an improvement of approximately 25% in the number of matching points compared to the SAR-SIFT, along with a reduction of about 30% in matching time, demonstrating its effectiveness. © The Institution of Engineering & technology 2023.

关键词： Synthetic aperture radar

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Performance Analysis of Sub-object Partition Method for Linear Formation Targets

Performance Analysis of Sub-object Partition Method for Line...

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IET International radar Conference 2023, IRC 2023

作者： Xu, Li'ang Jiang, Qi Zhang, Jichuan Wang, Rui Hu, Cheng Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Shandong Jinan China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

ISBN: (纸本)9781839539954

The structure of bird formation is complex and variable. Traditional sub-object partition methods cannot match different types of linear formations, leading to a degradation of performance. Recently, a new sub-object partition method applicable to different formations has been proposed. However, the performance of the method has not been analyzed and verified thoroughly. This paper analyses the effectiveness of the proposed method. The statistical rules are proposed to evaluate the performance of the sub-object partition. A series of simulations are conducted using the method of controlling variates, with several important parameters of the method and formation being chosen and discussed separately. And the quantitative results of partition accuracy are demonstrated and the impact of each parameter on partition performance is discussed. Based on the conclusion above, an empirical method for parameter initialization is proposed, which guides the practical applications. © The Institution of Engineering & technology 2023.

关键词： CLUSTERING FORMATION TARGET GROUP TARGET SUB-OBJECT PARTITION

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An Adaptive OS-CFAR detector for Dynamic group targets

An Adaptive OS-CFAR detector for Dynamic group targets

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IET International radar Conference 2023, IRC 2023

作者： Shi, Mengxin Jiao, Longxiang Jiang, Qi Wang, Rui Hu, Cheng Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Shandong Jinan China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

ISBN: (纸本)9781839539954

Effective detection of group targets is of great significance to people's livelihood and national security. Flocks of birds, UAV swarms and other group targets are closely spaced in the radar beam and have high dynamics, which can easily lead to the mismatch of the traditional detector parameters and missed detection. Therefore, in this paper, to solve this problem, we established the detection model of the corresponding scene, derived the probability density function expression of the threshold, and proposed the OS-CFAR detector parameter correction method with the expectation of the maximum number of detected targets as the optimization criterion. Taking the OSPA distance as the detection performance index, the detection performance under different detection parameters is compared to verify the effectiveness of this algorithm, and the experiments show that the algorithm proposed in this paper can effectively reduce the target missed detection in the group targets scene. © The Institution of Engineering & technology 2023.

关键词： Target tracking

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ROBUST JOINT ASSOCIATION AND REGISTRATION UNDER LARGE SENSOR BIAS

ROBUST JOINT ASSOCIATION AND REGISTRATION UNDER LARGE SENSOR...

引用

IET International radar Conference 2023, IRC 2023

作者： Ni, Na Jiang, Qi Mao, Huafeng Zhang, Jichuan Wang, Rui Hu, Cheng Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Shandong Jinan China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

ISBN: (纸本)9781839539954

radar observation of group targets has recently received much attention in the flight mechanism research and many other applications. Group targets are usually closely spaced with lots of missed detections and false alarms, making it difficult for spatial reconstruction. Multisensor systems make use of data from multiple radars to provide more accurate measurements and robust tracks than a single radar, playing an important role in the group targets observation. In the data fusion processes, multisensor measurements are associated after transformed into a global coordinate system. However, large sensor bias makes it difficult to associate measurements of closely spaced targets given outliers, and nonideal association further increase the sensor bias estimation error. In this paper, we proposed a robust joint association and registration method to simultaneously acquire sensor bias estimates and association results. A nonlinear least median of squares estimator is used to achieve better accuracy and robustness of sensor bias estimation. Simulation results show the better bias estimation and association performance of the proposed method compared to other algorithms. © The Institution of Engineering & technology 2023.

关键词： radar measurement

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Analysis of Formation UAV Targets' Angular Glint Characteristics Using Phase Gradient Method

Analysis of Formation UAV Targets' Angular Glint Characteris...

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IET International radar Conference 2023, IRC 2023

作者： Dou, Libin Jiang, Qi Zhang, Wenyuan Wang, Rui Hu, Cheng Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Shandong Jinan China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

ISBN: (纸本)9781839539954

Detection of group targets is of great significance to social and national security. Due to the large individual number, obvious fluctuations, and dense distribution of group targets, angular glint phenomena may occur during radar detection of group targets. Angular glint is an inherent error generated by the superposition of individual echoes of group targets, which is an important factor affecting the tracking accuracy of group targets. This paper analyzes the mechanism of angular glint of group targets, calculates the angular glint of a typical UAV group targets using the phase gradient method. The amplitude-phase fluctuation characteristics of an individual UAV target is modelled. The statistical characteristics of UAV angular glint is analysed using the Q-Q plot. The simulation results show that the phase gradient method is capable of analyzing the angular glint characteristics of group targets. © The Institution of Engineering & technology 2023.

关键词： Target tracking

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An improved dem reconstruction method based on shortest sub-interval in MF-InSAR

An improved dem reconstruction method based on shortest sub-...

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IET International radar Conference 2015

作者： Liu, Tiandong Ge, Shiqi Ding, Zegang Zhang, Qi Long, Teng Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Radar Research Lab. School of Information and Electronics Beijing Institute of Technology Beijing100081 China Nanjing Research Institute of Electronics Technology Nanjing210039 China

ISBN: (纸本)9781849199940

Interferometric synthetic aperture radar (InSAR) can realize the elevation extraction of the target. Through increasing the degree of freedom (DOF) during the topography calculation, multi-frequency InSAR technology can further achieve high-accuracy elevation reconstruction in steep terrain. Although the maximum likelihood estimation (MLE) method is widely used in the signal processing of multi-frequency InSAR, its performance can be influenced by phase noise. This paper proposes a creative algorithm which combines the maximum likelihood elevation estimation with the shortest sub-interval seeking operator (SSIS-MLE). It statistically averages the elevation estimation results of the MLE with class histogram, so that efficiently excludes the error estimation. Simulation results verify that this method not only maintains the high calculation efficiency of traditional MLE method, but also guarantees the high accuracy of elevation estimation.

关键词： Maximum likelihood estimation

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A modified SPECAN algorithm based on Chirp Scaling principle

A modified SPECAN algorithm based on Chirp Scaling principle

引用

IET International radar Conference 2015

作者： Zhou, Zhichao Yang, Wenfu Feng, Dongbo Ding, Zegang Zeng, Tao Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Radar Research Lab. School of Information and Electronics Beijing Institute of Technology Beijing100081 China China Academy of Launch Vehicle Technology Beijing100076 China

ISBN: (纸本)9781849199940

When synthetic aperture radar (SAR) works at the squint mode with a large grazing angle, the range walk varies obviously with the slant range. The traditional SPECAN algorithm corrects the range walk only based on the central slant range. Thus there are residual range walks at range edges of the swath, which finally leads to the defocus of the image. In order to solve this problem, a modified SPECAN algorithm based on the Chirp Scaling principle is proposed in this paper. First, the received data is multiplied by Chirp Scaling factor in the two-dimension time domain to eliminate the range variation of the range walk. Then the traditional SPECAN algorithm is applied to accomplish the two-dimension focus of the image. Simulation results confirm the validity of the proposed algorithm.

关键词： Synthetic aperture radar

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FPGA implementation of SAR bi-channel synthesis based on inverse filtering 5

FPGA implementation of SAR bi-channel synthesis based on inv...

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IET International radar Conference 2020, IET IRC 2020

作者： Shao, Xin Shi, Hao Chen, Liang Zhang, Na 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 Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839535635

In a multi-channel synthetic aperture radar (MSAR) system, non-uniform azimuth sampling is an important factor affecting imaging. If it is not processed and then imaged directly, it will inevitably lead to deterioration of imaging performance. The channel synthesis algorithm based on inverse filtering is a method to solve this problem. However, in actual applications, it is necessary to perform specific optimization processing on the algorithm to meet real-time requirements. This paper designs a new architecture for efficient implementation of channel synthesis algorithms. The design makes full use of the parallel characteristics of FPGA to improve the speed of the algorithm. By optimizing the DDR read-write control logic, the data transfer rate is improved. Finally, the Modelsim software is used to obtain the simulation results. At 150 MHz, the processing speed could reach 461.6MSamples/s (64bit/sample). © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Data transfer

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