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signal, Information and data processing (ICSIDP), IEEE International Conference on

作者： Huayu Fan Wenji Li Lixiang Ren Erke Mao Jian Yang Tsinghua University Beijing China Key Laboratory of Electronic and Information Technology in Satellite Navigation (Beijing Institute of Technology) Ministry of Education Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

The target micro-motion features contain unique structural information and motion information, which can be utilized as an important basis for target recognition. At present, the main constraints of micro-motion feature extraction for high-speed targets include that the translational compensation is inaccurate, the scattering points are difficult to distinguish, the micro-motion amplitude is small, the data rate is not high enough, and so forth. The phase-derived velocity measurement (PDVM) method based on wideband radar has phase-magnitude velocity measurement precision, which can accurately reconstruct the target motion while ensuring high data rate, and meet the micro-motion measurement requirements of high-speed targets. In this paper, a PDVM method for high-speed targets based on wideband direct sampling LFM radar is proposed. The high-precision velocity measurement performance and micro-motion measurement capability of the proposed method are verified by simulation.

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A three-dimensional image processing method based on data layered two-dimensional normalization

A three-dimensional image processing method based on data la...

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IEEE International Conference on signal processing, Communications and Computing

作者： Bibo Zhu Hanlei Jiang Weihua Cong Science and Technology on Sonar Laboratory Hangzhou Applied Acoustics Research Institute

ISBN: (纸本)9781728117096

Three-dimensional high-resolution imaging is a new technology for long-range detection of underwater small targets, This technology enables three-dimensional mapping of targets in water, sinking and buried environments. The three-dimensional imaging sonar adopts the ultra-wideband low-frequency emission array with large glancing angle and the two-dimensional acoustic array with wide directivity reception, which effectively acquires underwater target depth dimension, navigation dimension and azimuth dimension information. The pulse compression processing, synthetic aperture tomography processing, and anti-reverberation high-resolution array processing are used to realize three-dimensional high-resolution imaging of underwater targets. However, since the underwater echoes come from different azimuths, depths, and media environments, the significant difference causes the reverberation of the target image area to be severely unbalanced, which directly affects the background brightness and feature contrast of the target image area, and ultimately increases the artificial identify the risk of errors. In this paper, A three-dimensional image processing method based on data layered two-dimensional normalization is studied. Firstly, by tracking the three-dimensional seabed interface, the distribution law of seafloor reflection echo energy in different azimuths is statistically obtained. Then, the acoustic energy attenuation loss of different geological strata is compensated. After that, the dynamic range of the three-dimensional acoustic image and the target feature contrast are improved by the two-dimensional normalization processing of the layered water and the stratum. The method has been processed and verified by experimental data, so as to achieve stable and efficient realization of 3D acoustic image background equalization and target enhancement, which has strong robustness, certain innovation and good engineering use value.

关键词： Three-dimensional acoustic image Reverberation interference Layered media processing Background equalization Underwater Three-Dimensional Images telemetry Underwater targets targets Acoustic equipment normalization Pulse compression Reverberation target image High resolution imaging Dynamic range

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基于YOLO的交通信号灯检测算法

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数字技术与应用 2021年第6期39卷 97-99页

作者：毛涛安徽理工大学计算机科学与工程学院安徽淮南232000

交通信号灯的检测在无人驾驶以及辅助驾驶中起着至关重要的作用,然而传统的图像处理方法因为速度和检测质量的原因,往往不能达到应用于无人驾驶系统的程度。同时交通信号灯属于小目标,因此检测难度大。所以本文提出了一种基于单阶段目... 详细信息

交通信号灯的检测在无人驾驶以及辅助驾驶中起着至关重要的作用,然而传统的图像处理方法因为速度和检测质量的原因,往往不能达到应用于无人驾驶系统的程度。同时交通信号灯属于小目标,因此检测难度大。所以本文提出了一种基于单阶段目标检测算法,该算法对YOLOv5(You only look once)算法进行了改进,保留了YOLOv5检测速度快以及搭建简单的优点,结合注意力模型将检测的重点放在交通信号灯检测上,使得对交通信号灯的检测更加的快速准确。该实验在LISA交通信号灯数据集上取得了显著的效果,进一步证明了我们算法的有效性。

关键词：交通信号灯小目标目标检测 YOLOv5 注意力模型

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DDMA MIMO radar system for low, slow, and small target detection

DDMA MIMO radar system for low, slow, and small target detec...

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IET International Radar Conference 2018, IRC 2018

作者： Yang, Fawei Xu, Feng Yang, Xiaopeng Liu, Quanhua Key Laboratory of Electronic and Information Technology in Satellite Navigation Beijing Institute of Technology Ministry of Education Beijing100081 China

The low, slow, and small (LSS) target detection has always been a problem for both ground-based and air-borne radar systems. The factors such as weak target reflection energy, ground clutter, and random Doppler component will have a severe impact on radar detection performance. In recent years, researches on multiple-input multiple-output (MIMO) radar system have achieved great progress. By utilising multi-channel and multi-waveform technology, MIMO radar can form equivalent phase centres and virtual apertures to provide more system freedom and enhance detection performance. To address the LSS target-detection problem, the authors propose a novel Doppler division multiple access (DDMA) MIMO radar system, which employ DDMA waveform to ensure the orthogonality of the transmit signal and avoid some of the problems in the application of frequency division multiple access (FDMA) and code division multiple access (CDMA) for the actual radar system. The sparse array is employed to supress the grating lobe of the beam pattern and improve the angle estimation performance by optimising the position of the antenna array elements. Finally, the architecture of the designed radar system is introduced and the results of the detection performance to LSS targets based on real measured data is given. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： MIMO systems

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Moving Target Tracking in SAR data Using Combined Exo- and Endo-Clutter processing

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2018年第1期56卷 251-263页

作者： Henke, Daniel Dominguez, Elias Mendez small, David Schaepman, Michael E. Meier, Erich Univ Zurich Remote Sensing Labs Dept Geog CH-8057 Zurich Switzerland

Detecting and tracking moving targets in synthetic aperture radar (SAR) data is a challenging task, demanding state-of-the-art processing methods and advanced SAR systems. Current approaches concentrate on the problem of either endo-clutter moving target tracking or exo-clutter moving target tracking, neglecting the advantages of a joint tracking framework. We present an approach relying on a combined exo-and endo-clutter processing scheme using SAR data with a high pulse repetition frequency. The main processing chain is subdivided into four major steps: 1) focusing of temporal and spatial overlapping SAR images;2) extracting image statistics for each of these subaperture images in the endo-and exo-clutter domains;3) subsequent tracking of both endo-and exo-clutter observations using multitarget unscented Kalman filtering;and 4) calculating real-world speeds and positions from the SAR image space coordinates using a road network. The results of this approach are validated and compared with ground-based measurements, and it is found that 100% of the vehicles were detected correctly with an accuracy in speed of 0.02 +/- 0.31 m/s and an average tracking time of similar to 28 s.

关键词： Ground moving target indication (GMTI) Kalman filtering moving target tracking radar signal analysis radar velocity measurement refocusing synthetic aperture radar (SAR) tracking filters

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Optimal-Dual-Based l₁ Analysis for Speckle Reduction of SAR data

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2018年第11期56卷 6674-6685页

作者： Gleich, Dusan Univ Maribor Lab Signal Proc & Remote Control Fac Elect Engn & Comp Sci Maribor 2000 Slovenia

Synthetic aperture radar (SAR) images are affected by a speckle noise, which is a consequence of random fluctuations in the return signal from an object that is no bigger than a single image processing element and it is caused by coherent processing of backscattered signals from multiple distributed targets. Speckle within SAR images can be reduced using filtering methods. To preserve features within the SAR images, this paper proposes a noise removal based on scene and SAR data modeling. The proposed method is a model-based total variational optimization with the minimization of a cost function. The cost function consisted of enera and data fidelity terms. The energy term was modeled using optimal-dual-based l(1) analysis. The data fidelity term modeled the amplitude of the SAR data, which was approximated using a Nakagami distribution. The minimization of the cost function was solved using a quasi-Newton approach. The experimental results showed good results in SAR feature preservation. The proposed method was evaluated numerically using quality metrics for synthetic generated data and real amplitude SAR data.

关键词： Image enhancement image filtering noise reduction radar imaging synthetic aperture radar

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Comparison of Sparse signal Separation Algorithms for Maritime Radar Target Detection

Comparison of Sparse Signal Separation Algorithms for Mariti...

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International Conference on Radar (RADAR)

作者： Ng, Brian Rosenberg, Luke Berry, Paul Univ Adelaide Adelaide SA Australia Def Sci & Technol Grp Edinburgh SA Australia

ISBN: (纸本)9781538672174

Due to the non-stationary nature of sea clutter, traditional maritime radar detection schemes utilise non-coherent processing. To further enhance the detection performance, one alternative is to use sparse signal separation. This is an alternative paradigm, whereby the different spatio-temporal characteristics of the radar signal are exploited to separate targets from the background interference. In previous work, the sparse signal separation problem has been posed in a compressive sensing framework so as to improve detection of small maritime targets. This paper investigates the performance of three different algorithms for solving the signal separation problem. These include the Split Augmented Lagrangian Shrinkage Algorithm (SALSA), adaptive Complex Approximate Message Passing (CAMP) and the Fast Sparse Functional Iteration Algorithm (FSFIA). The first contribution is to reformulate the CAMP algorithm to the framework of sparse signal separation. The suitability of each algorithm is then assessed using real data from the Ingara radar, and is based on the quality of the solutions obtained, the computational speed and the robustness to the user's choice of 'tuning' parameters.

关键词： Sea clutter detection sparse signal processing

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An Infrared small Target Detection Method Based on Block Compressed Sensing 13th

An Infrared Small Target Detection Method Based on Block Com...

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13th International Conference on Intelligent Information Hiding and Multimedia signal processing (IIH-MSP)

作者： Yang, Jingli Cui, Zheng Jiang, Shouda Harbin Inst Technol Dept Automat Test & Control Xidazhistr 92 Harbin 150080 Heilongjiang Peoples R China

ISBN: (纸本)9783319638560;9783319638553

Aiming at improving the real-time performance of infrared weapon systems, a method based on block compressed sensing is proposed to detect infrared small target, which is also easy to be implemented with hardware. The proposed method can detect and locate small infrared targets by classifying compressed results of blocks. In addition, in order to solve the low detection accuracy caused by using uniform block, the proposed method uses overlapping blocks to reduce the maximum distance between the center of the test sample block and that of the target. Experiments show that the proposed method can effectively improve the detection accuracy of infrared small targets.

关键词： Compressed sensing Infrared target detection Overlapping blocks

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相控阵雷达增程扩容系统设计与实现

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测控技术 2020年第5期39卷 86-90页

作者：张景东葛页赵明旭刘帆郭倩倩中国人民解放军63615部队新疆库尔勒841001

针对某型相控阵雷达对远距离小目标的检测与跟踪性能不足,波束内跟踪目标数量较少的问题,设计了一种增程扩容系统。该系统采用脉冲能量积累和扩展波束内目标数量技术,结合点迹提取和航迹建立方法,实现远距离小目标的检测跟踪以及目标跟... 详细信息

针对某型相控阵雷达对远距离小目标的检测与跟踪性能不足,波束内跟踪目标数量较少的问题,设计了一种增程扩容系统。该系统采用脉冲能量积累和扩展波束内目标数量技术,结合点迹提取和航迹建立方法,实现远距离小目标的检测跟踪以及目标跟踪数量的扩容功能。软件部分,在原有工作方式基础上,利用滤波检测技术,增加增程扩容系统工作方式。在硬件上设计了以DSP阵列信号处理板和GPU卡为核心的功能模块,实现超高速数据处理。实际测试表明,该系统能有效扩展雷达跟踪远距离小目标能力,增加雷达跟踪目标数量,航迹建立连续性好,达到了系统设计的目的和实际应用的要求。

关键词：相控阵雷达增程扩容技术能量积累远距离小目标

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Separation of small targets in Multi-Wavelength Mixtures Based on Statistical Independence 27

Separation of Small Targets in Multi-Wavelength Mixtures Bas...

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Conference on signal processing, Sensor/Information Fusion, and Target Recognition XXVII

作者： Mowakeaa, Rami Emge, Darren K. Univ Maryland Baltimore Cty 1000 Hilltop Circle Baltimore MD 21228 USA US Army Edgewood Chem Biol Ctr RDCB DRC P Aberdeen Proving Ground MD 21010 USA

ISBN: (数字)9781510618046

ISBN: (纸本)9781510618046

small target detection is a problem common to a diverse number of fields such as radar, remote sensing, and infrared imaging. In this paper, we consider the application of feature extraction for detection of small hazardous materials in multiwavelength imaging. Since various materials may exist in the area of study each with varying degrees of reflectivity and absortion at different wavelengths of light, flexible, data-driven methods are needed for feature extraction of relevant sources. We propose the use of independent component analysis (ICA), a widely-used blind source separation method based on the statistical independence of the underlying sources. We compare 3 different prominent flavors of ICA on simulated data in a variety of environments. Then, we apply ICA to 2 multi-wavelength imaging datasets with results that suggest that features extracted are useful.

关键词： small-target detection ICA BSS multi-wavelength machine learning

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