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Spectrum Recovery for Clutter Removal in Penetrating Radar Imaging

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2019年第9期57卷 6650-6665页

作者： Li, Yinchuan Wang, Xiaodong Ding, Zegang Zhang, Xu Xiang, Yin Yang, Xiaopeng Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China Columbia Univ Dept Elect Engn New York NY 10027 USA

Penetrating radar systems are widely employed to scan the objects that are placed behind or buried inside mediums (such as walls, ground, and so on). As the clutter is much stronger than the target echo, clutter removal must be performed before imaging. The moving average subtraction, spatial notch filtering, and singular value decomposition methods are commonly used to remove clutter. However, the drawback is that these methods eliminate some of the target spectrum information, which causes target energy losses and generates side lobes. To solve this problem, two spectrum recovery methods are proposed in this paper. The first method recovers the spectrum magnitude and phase via sinc interpolation and linear fitting, respectively, which is fast and suitable for real-time processing. Although the second method recovers the spectrum based on matrix completion with prior information, which is more accurate and more computational expensive. Extensive simulations and experiments are presented to validate the proposed methods. The results show that the proposed methods can improve various traditional clutter removal methods, the side lobes are clearly suppressed, and the signal-to-clutter ratio is significantly improved.

关键词： Clutter removal ground-penetrating radar (GPR)/wall-penetrating radar (WPR) interpolation linear fitting matrix completion (MC) prior information spectrum recovery through-the-wall radar (TWR)

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Multidimensional Spectral Super-Resolution With Prior Knowledge With Application to High Mobility Channel Estimation

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2020年第12期38卷 2836-2852页

作者： Li, Yinchuan Wang, Xiaodong Ding, Zegang Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Columbia Univ Dept Elect Engn New York NY 10027 USA Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China

The problem of estimating high-mobility channels is a special case of the general problem of recovering multi-dimensional (MD) complex sinusoids. This paper is concerned with estimation of multiple frequencies with prior knowledge from incomplete and/or noisy samples. Suppose that it is known a priori that the frequencies lie in some given intervals, we develop efficient super-resolution estimators by exploiting such prior knowledge based on frequency-selective (FS) atomic norm minimization. We study the MD Vandermonde decomposition of block Toeplitz matrices in which the frequencies are restricted to lie in given intervals. We then propose to solve the FS atomic norm minimization problems for the low-rank spectral tensor recovery by converting them into semidefinite programs based on the MD Vandermonde decomposition. We also develop fast solvers for solving these semidefinite programs via the alternating direction method of multipliers (ADMM), where each iteration involves a number of refinement steps to utilize the prior knowledge. Extensive simulation results are presented to illustrate the high performance of the proposed methods.

关键词： 5G mobile communication Frequency estimation Minimization Channel estimation Matrix decomposition Multi-dimensional super-resolution high mobility channel estimation low-rank tensor frequency-selective Vandermonde decomposition atomic norm prior knowledge ADMM

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Improved Two-Probe Approach for In-Circuit Measurement Based on Three-Port Network Pre-Calibration

Improved Two-Probe Approach for In-Circuit Measurement Based...

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2015 Asia Pacific Symposium on Electromagnetic Compatibility (APEMC)

作者： Li, Xing-Ming Hu, Shan-Qing See, Kye-Yak Li, Kang-Rong Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing Peoples R China Nanyang Technol Univ Singapore Singapore

ISBN: (纸本)9781479966707

In high-speed electrical designs, the in-circuit characteristics of the components are usually obtained from in-circuit measurements as the references for designers. The two-probe approach (TPA) is one of in-circuit measurement approaches by adopting the inductive coupling effects of the current probes, and it gains good accuracy below 30MHz. In this paper, we propose an improved two-probe approach (ITPA) by introducing network parameters. Rather than modeling the measurement setup using equivalent circuits in the TPA, the proposed ITPA models it by using a three-port network, and precalibrates it before real measurements. By comparing the results measured from ITPA with those from the impedance analyzer (IA), it is proven that, the ITPA extends the highest measurement frequency to 100MHz from 30MHz (with the TPA), while maintaining allowable accuracy;besides, the ITPA avoids the trial-error pre-calibrations required in the TPA.

关键词： Probes

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Optimizing the Capacitor Placement Based on 2D Charge-Delivery Model of Power Delivery Network

Optimizing the Capacitor Placement Based on 2D Charge-Delive...

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2015 Asia Pacific Symposium on Electromagnetic Compatibility (APEMC)

作者： Li, Xing-Ming Hu, Shan-Qing See, Kye-Yak Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing Peoples R China Nanyang Technol Univ Singapore Singapore

ISBN: (纸本)9781479966707

In high-speed electrical systems, power distribution network (PDN) with power ground planes (PGP) is widely used to gain effective high-speed decoupling. Rather than modelling such PDN from conventional steady-state analysis in the frequency domain, we propose its two-dimension (2-D) charge delivery model from charge delivery perspective in the time domain, which correlates better with the PDN real operations. With the model, by taking the synthesized effects from the interactions of the charge providers (such as voltage regulator module (VRM) and capacitors) into account, we propose two design rules to optimize the placement of the capacitors in preliminary PDN design.

关键词： Voltage regulators

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Integrated Test System of Infrared and Laser Data Based on USB 3.0 9

Integrated Test System of Infrared and Laser Data Based on U...

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9th International Conference on Digital Image processing (ICDIP)

作者： Fu, Hui Quan Tang, Lin Bo Zhang, Chao Zhao, Bao Jun Li, Mao Wen Beijing Inst Technol Sch Informat & Elect Inst Radar Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China

ISBN: (纸本)9781510613058;9781510613041

Based on USB3.0, this paper presents the design method of an integrated test system for both infrared image data and laser signal data processing module. The core of the design is FPGA logic control, the design uses dual-chip DDR3 SDRAM to achieve high-speed laser data cache, and receive parallel LVDS image data through serial-to-parallel conversion chip, and it achieves high-speed data communication between the system and host computer through the USB3.0 bus. The experimental results show that the developed PC software realizes the real-time display of 14-bit LVDS original image after 14-to-8 bit conversion and JPEG2000 compressed image after decompression in software, and can realize the real-time display of the acquired laser signal data. The correctness of the test system design is verified, indicating that the interface link is normal.

关键词： USB 3.0 FPGA high speed host computer display

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real-time target tracking and locating system for UAV 9

Real-Time target tracking and locating system for UAV

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9th International Conference on Digital Image processing (ICDIP)

作者： Zhang, Chao Tang, Linbo Fu, Huiquan Li, Maowen Beijing Inst Technol Sch Informat & Elect Inst Radar Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China

ISBN: (纸本)9781510613058;9781510613041

In order to achieve real-time target tracking and locating for UAV, a reliable processing system is built on the embedded platform. Firstly, the video image is acquired in real time by the photovoltaic system on the UAV. When the target information is known, KCF tracking algorithm is adopted to track the target. Then, the servo is controlled to rotate with the target, when the target is in the center of the image, the laser ranging module is opened to obtain the distance between the UAV and the target. Finally, to combine with UAV flight parameters obtained by BeiDou navigation system, through the target location algorithm to calculate the geodetic coordinates of the target. The results show that the system is stable for real-time tracking of targets and positioning.

关键词： UAV KCF algorithm target location algorithm BeiDou navigation system

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Data Augmentation for Imbalanced HRRP Recognition Using Deep Convolutional Generative Adversarial Network

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IEEE ACCESS 2020年 8卷 201686-201695页

作者： Song, Yiheng Li, Yang Wang, Yanhua Hu, Cheng Beijing Inst Technol Sch Informat & Elect Radar Res Lab Beijing 100081 Peoples R China Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China Beijing Inst Technol Chongqing Innovat Ctr Chongqing 401120 Peoples R China

In radar high-resolution range profile (HRRP) recognition, the recognition accuracy will decline when the training samples in some classes (majority classes) greatly outnumbers other classes (minority classes). To alleviate the above imbalanced problem, an HRRP data augmentation framework is proposed. A one-dimensional (1-D) deep convolutional generative adversarial network (DCGAN) is developed to generate artificial HRRPs. The fidelity of the generated HRRPs is evaluated subjectively in the raw data domain and quantitatively by the similarity in the feature domain. The experimental results show that the generated data are similar to the true HRRPs and demonstrate that the proposed framework outperforms the state-of-the-art oversampling methods when handling the imbalanced problem.

关键词： Generative adversarial networks Gallium nitride Generators Feature extraction Scattering Training Radar High resolution range profile (HRRP) imbalanced problem data augmentation 1-D deep convolutional generative adversarial network (DCGAN)

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A Multi-Carrier-Frequency Random-Transmission Chirp Sequence for TDM MIMO Automotive Radar

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2019年第4期68卷 3672-3685页

作者： Hu, Xueyao Li, Yang Lu, Man Wang, Yanhua Yang, Xiaopeng Beijing Inst Technol Radar Res Lab Sch Informat & Elect Beijing 100081 Peoples R China Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China Beijing Racobit Elect Informat Technol Co Ltd Beijing 100081 Peoples R China

The collocated time-division multiplexing (TDM) multiple-input multiple-output (MIMO) technique and frequency-modulated continuous-wave (FMCW) chirp sequence are widely used in automotive radar because of the low hardware complexity and the high-accurate range and velocity measurements. In conventional TDM chirp sequences, the transmitters are switched according to their natural spatial order (referred to as a fixed sequential order), thereby inducing space-Doppler frequency coupling and a relatively low unambiguous Doppler interval. In this paper, a new FMCW chirp sequence and corresponding signal processing method for TDM MIMO automotive radar are proposed. The novel waveform adopts the concept of random transmission to distort the linear phase relationship between space and Doppler, therefore, overcoming the coupling problem. Then, via compressed sensing processing, the scheme can suppress the sidelobe pedestal arisen in the conventional matched filter for targets detection. Besides, based on multiple-frequency observations of the same targets, the velocity ambiguity can be adequately resolved. Compared with conventional chirp sequence, the proposed scheme simultaneously overcomes the typical TDM MIMO chirp sequence problems, thereby avoiding a reduction in the data rate. Also, the scheme significantly reduces the mutual interference between adjacent systems. The simulations and experimental results demonstrate the effectiveness of the proposed chirp sequence scheme.

关键词： Automotive radar time-division multiplexing multiple-input multiple-output (TDM-MIMO) frequency-modulated continuous-wave (FMCW) chirp sequence compressed sensing (CS) multiple carrier frequencies

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A Ship ISAR Imaging Algorithm Based on Generalized Radon-Fourier Transform With Low SNR

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2019年第9期57卷 6385-6396页

作者： Ding, Zegang Zhang, Tianyi Li, Yong Li, Gen Dong, Xichao Zeng, Tao Ke, Meng Beijing Inst Technol Radar Res Lab Sch Informat & Elect Beijing 10081 Peoples R China Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China Beijing Inst Technol Radar Res Lab Sch Informat & Elect Beijing 10081 Peoples R China

Existing ship inverse synthetic aperture radar (ISAR) imaging algorithms are not applicable, when the signal-to-noise ratio (SNR) is low, for the translational motion that cannot be well compensated by existing algorithms. To achieve ship ISAR imaging with low SNR, a ship ISAR imaging algorithm based on the generalized radon-Fourier transform (GRFT) is proposed in this paper. Considering not only the rotational motion but also the translational motion between the radar and the ship, the proposed algorithm uses the GRFT to simultaneously compensate the time-variant range envelopes and the Doppler phase. Thus, the signal coherence is fully utilized, and the coherent integration of the ship's multicomponent echo signal is realized. Subsequently, to overcome the problem of the heavy computational load and improve the efficiency of the proposed algorithm, the scheme of cascaded GRFTs that consists of the coarse GRFT and the subsequent fine GRFT is adopted. The coarse GRFT with large search ranges and intervals is aimed at obtaining the real ranges of ship scatter points' motion parameters. Based on the coarse GRFT result, the fine GRFT with small search ranges and intervals is performed to efficiently obtain the coherent integration result. Then, based on the coherent integration result, the constant false alarm rate (CFAR) detection is performed to obtain the desired scatter points and their amplitudes and motion parameters, and the multicomponent signal is reconstructed. Finally, based on the reconstructed multicomponent signal, the high-quality instantaneous ship ISAR image can be obtained. Computer simulations and experiment results validate the effectiveness of the proposed algorithm.

关键词： Generalized radon-Fourier transform (GRFT) inverse synthetic aperture radar (ISAR) imaging low signal-to-noise ratio (SNR) noncooperative ship

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Geometric Boundary Guided Feature Fusion and Spatial-Semantic Context Aggregation for Semantic Segmentation of Remote Sensing Images

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IEEE TRANSACTIONS ON IMAGE procESSING 2023年 32卷 6373-6385页

作者： Wang, Yupei Zhang, Haoran Hu, Yongkang Hu, Xiaoxing Chen, Liang Hu, Shanqing Beijing Inst Technol Beijing 100081 Peoples R China Beijing Inst Technol Chongqing Innovat Ctr Chongqing 401135 Peoples R China Beijing Key Lab Embedded Real Time Informat Proc T Beijing 100081 Peoples R China

Semantic segmentation of remote sensing images aims to achieve pixel-level semantic category assignment for input images. This task has achieved significant advances with the rapid development of deep neural network. Most current methods mainly focus on effectively fusing the low-level spatial details and high-level semantic cues. Other methods also propose to incorporate the boundary guidance to obtain boundary preserving segmentation. However, current methods treat the multi-level feature fusion and the boundary guidance as two separate tasks, resulting in sub-optimal solutions. Moreover, due to the large inter-class difference and small intra-class consistency within remote sensing images, current methods often fail to accurately aggregate the long-range contextual cues. These critical issues make current methods fail to achieve satisfactory segmentation predictions, which severely hinder downstream applications. To this end, we first propose a novel boundary guided multi-level feature fusion module to seamlessly incorporate the boundary guidance into the multi-level feature fusion operations. Meanwhile, in order to further enforce the boundary guidance effectively, we employ a geometric-similarity-based boundary loss function. In this way, under the explicit guidance of boundary constraint, the multi-level features are effectively combined. In addition, a channel-wise correlation guided spatial-semantic context aggregation module is presented to effectively aggregate the contextual cues. In this way, subtle but meaningful contextual cues about pixel-wise spatial context and channel-wise semantic correlation are effectively aggregated, leading to spatial-semantic context aggregation. Extensive qualitative and quantitative experimental results on ISPRS Vaihingen and GaoFen-2 datasets demonstrate the effectiveness of the proposed method.

关键词： Semantic segmentation multi-level feature fusion contextual cues

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