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作者： Lin, Jianzhi Li, Weixing Wang, Weihua Li, Gang Chen, Zengping Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781934142301

Compensation for amplitude and phase distortion in inverse synthetic aperture radar (ISAR) system is important for the system performance. People cannot help but take an active radar calibrator on a tower as an external test target to measure the distortion and carry out the compensation though it includes extraneous components and induces additional distortion. So a new method for distortion compensation is presented, which is based on the low signal-to-noise-ratio (SNR) echo from a spherical satellite. The technique of pulse compression based on matched filtering is used and then the target region is extracted and inverse matched filtering is applied to achieve the high SNR echo. Thus the amplitude and phase error coefficients can be calculated, which results in excellent compensation for the system distortion. Experimental results based on real radar data show the effectiveness of the proposed method. Comparison results with other scheme are also presented to prove the superiority of our approach.

关键词： Inverse problems

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Azimuth Calibration and Data Association for a Radar-Optical Multi-Sensor System 4

Azimuth Calibration and Data Association for a Radar-Optical...

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4th IEEE International Conference on Electronics technology, ICET 2021

作者： Yang, Ye Da, Kai Zhu, Yongfeng Xiang, Shengwen Fu, Qiang National University of Defense Technology National Key Laboratory of Science and Technology on Automatic Target Recognition College of Electronic Science Changsha China

ISBN: (纸本)9781728176734

Radar sensors have high false alarm rate in high density clutter and low angular measurement accuracy due to low angle resolution. This paper proposes an azimuth calibration and track association algorithm by utilizing both radar and optical sensor simultaneously to improve detection and estimation performance. First, based on 'azimuth-time' search algorithm, data calibration of radar and optical measurements is realized. Then, the nearest neighbor (NN) algorithm and the probability data association (PDA) algorithm are used to associate the calibrated data. Finally, the effectiveness of the algorithm is verified through processing and analysis of measured data. © 2021 IEEE.

关键词： Radar measurement

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Real-time processing technique for panoramic infrared imaging system

Real-time processing technique for panoramic infrared imagin...

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作者： Sun, G. Li, G. Wang, W.H. Fan, X.L. Chen, Z.P. Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781934142301

Panoramic infrared imaging system (PIIS) based on the long linear array long-wave detector is introduced. Due to the real-time processing and high-speed data transfer demanding, we propose a high-performance processing platform based on field programmable gate array (FPGA) + multicore digital signal processor (DSP) architecture. To reduce the platform's power consumption, dynamic power monitoring technology is used to provide variable core voltage management for DSP. Then mapping an application to the platform is illustrated, which is guided by parallel-task segmentation mechanism of multi cores system. We show that, the designed platform with the optimization strategies achieves powerful capabilities of data throughput and processing performance.

关键词： Digital signal processors

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A New target Detection Method for Noncooperative Bistatic Radar Based on Fractional Fourier Transform and Wavelet Transform 2

A New Target Detection Method for Noncooperative Bistatic Ra...

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2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

作者： Tang, Zejia Bao, Qinglong Chen, Zengping Lin, Caiyong Wang, Sen National University of Defense Technology Science and Technology on Automatic Target Recognition Laboratory Changsha China Shenzhen University Changsha China

ISBN: (纸本)9781538618035

A247 the template matching method is an effective way to acquire direct waves, there is a certain deviation in the acquisition and estimation of direct waves. The deviation of direct wave parameters directly affects the performance of subsequent related algorithms. In this paper, we mainly evaluate the performance of the pulse compression(PC) algorithm with non-cooperative radar parameters, and propose a direct detection method based on fractional Fourier and wavelet denoising. This paper gives the detection performance curve of this new method. The result shows that there is a certain gap between the proposed method and the ideal pulse compression method, but it has excellent performance with respect to the deviation of the direct wave parameters. Therefore, it is an excellent method to detect the target under a specific signal-to-noise ratio in the non-cooperative bistatic radar. © 2018 IEEE.

关键词： Wavelet transforms

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A Gaussian Mixture PHD Filter Based on Energy Accumulation 7

A Gaussian Mixture PHD Filter Based on Energy Accumulation

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7th International Conference on Signal and Image Processing, ICSIP 2022

作者： Guo, Liping Shen, Xinglin Xiao, Shanzhu Lu, Huanzhang National University of Defense Technology Key Laboratory of Automatic Target Recognition Changsha China

ISBN: (数字)9781665495639

ISBN: (纸本)9781665495639

Aiming at the problem that tracking performance of the Gaussian mixture probability hypothesis density (GM-PHD) filter is inaccurate under low signal-to-noise ratio (SNR), a GM-PHD filter based on energy accumulation of trajectory is proposed. Firstly, several constant frames are selected to be the input of the pipeline filter, remaining possible straight lines within the speed limit. Then, accumulate the pixel value of the possible straight paths as their energies to further reduce false alarms. Finally, the number and status of targets are obtained through the iterative update of the classic PHD filter. The simulation results show that the proposed method achieves a favourable tracking performance, especially in the accuracy of the target number and target state estimates. © 2022 IEEE.

关键词： Pipelines

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target detection and tracking algorithm based on improved Mask RCNN and LMB 10

Target detection and tracking algorithm based on improved Ma...

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10th International Conference on Control, Automation and Information sciences, ICCAIS 2021

作者： Liu, Zhuoqun Deng, Yingjie Ma, Feng Du, Jinming Xiong, Chao Hu, Moufa Zhang, Luping Ji, Xuhuan National University of Defense Technology National Key Laboratory of Science and Technology on Automatic Target Recognition College of Electronic Science and Technology Changsha China

ISBN: (纸本)9781665440295

This paper proposes an improved Mask RCNN and LMB algorithm for target detection and tracking in complex backgrounds, which follows the architecture of Detect-Before-Track. First, the novel algorithm adopts a two-stage neural network to improve the target positions' accuracy during the detection. Then, the label multi-Bernoulli filter, which is suitable for scenarios with an unknown number of targets and target intersection, is utilized to generate the multiple-target trajectories during the tracking stage. Experiments suggest the algorithm's effectiveness and superiority in complex backgrounds' infrared target detection and tracking. © 2021 IEEE.

关键词： Complex networks

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Narrow-beam radar clutter distortion correction method based on clutter pre-screening and beam pattern demodulation 6

Narrow-beam radar clutter distortion correction method based...

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6th International Conference on Information science, Electrical, and Automation Engineering, ISEAE 2024

作者： Xu, Yong Zhu, Yongfeng Song, Zhiyong National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Hunan Changsha410073 China

ISBN: (纸本)9781510682924

For a narrow-beam radar working in a down-looking view, the antenna pattern modulates the ground clutter apparently in the delay/range dimension, causing amplitude/intensity distortion of radar echoes and performance loss of target detection. This paper proposes a range-dimensional clutter distortion correction method based on clutter pre-screening and beam pattern demodulation. This method realizes the correction of clutter distortion, to improve the target detection performance of Narrow-beam radar. The effectiveness of the method is verified through simulations and experimental measurements. The pro-posed method demonstrates practical significance in improving the detection probability of radar targets under clutter distortion in narrow-beam broadband radar systems. © 2024 SPIE.

关键词： Radar clutter

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recognition of UAV Image Transmission Signal via Deep Learning Methods

Recognition of UAV Image Transmission Signal via Deep Learni...

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International Conference on Guidance, Navigation and Control, ICGNC 2022

作者： Zhang, Shunjie Wei, Wang Jun, Zhang National Key Laboratory of Science and Technology on Automatic Target Recognition College of Electronic Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789811966125

In the last decade, the rapid development of UAV (Unmanned Aerial Vehicle) enterprises has given rise to a great number of drones, and a part of them illegal flights. Due to their low threshold of entry into the air, it is difficult to monitor low and slow UAVs which threaten the airspace safety. Determining the behaviour of UAVs is a challenging area of airspace regulation. Nowadays, DL (Deep Learning) has become a key research component of radiation signal recognition in many regulatory applications. In order to facilitate the solution to illegal UAV intrusion into airspace without locating the perpetrators, we apply deep learning methods in radio signal recognition based on a real-world signal dataset. Further the model of CNN (Convolutional Neural Network) was pruned to obtain a lightweight network for efficient signal recognition. In this paper, we have verified the first time the effectiveness of DL in recognizing drone raw signals. Then, we also take a closer look at the performance of lightweight models and compare acan achieve 98.9% recognition accuracy, which is at least 1.59% higher than CNN. Finally, we discuss open issues in this field. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Drones

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Joint tracking and classification of extended targets with complex shapes

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Frontiers of Information technology & Electronic Engineering 2021年第6期22卷 839-861页

作者： Liping WANG Ronghui ZHAN Yuan HUANG Jun ZHANG Zhaowen ZHUANG National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense TechnologyChangsha 410073China

This paper addresses the problem of joint tracking and classification(JTC) of a single extended target with a complex shape. To describe this complex shape, the spatial extent state is first modeled by star-convex shape via a random hypersurface model(RHM), and then used as feature information for target classification. The target state is modeled by two vectors to alleviate the influence of the high-dimensional state space and the severely nonlinear observation model on target state estimation, while the Euclidean distance metric of the normalized Fourier descriptors is applied to obtain the analytical solution of the updated class probability. Consequently, the resulting method is called the "JTC-RHM method." Besides, the proposed JTC-RHM is integrated into a Bernoulli filter framework to solve the JTC of a single extended target in the presence of detection uncertainty and clutter, resulting in a JTC-RHM-Ber filter. Specifically, the recursive expressions of this filter are derived. Simulations indicate that:(1) the proposed JTC-RHM method can classify the targets with complex shapes and similar sizes more correctly, compared with the JTC method based on the random matrix model,(2) the proposed method performs better in target state estimation than the star-convex RHM based extended target tracking method,(3) the proposed JTC-RHM-Ber filter has a promising performance in state detection and estimation, and can achieve target classification correctly.

关键词： Extended target Fourier descriptors Joint tracking and classification Random hypersurface model Bernoulli filter

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A Joint Detection and State Estimation Algorithm for Pulse Doppler Radar 5

A Joint Detection and State Estimation Algorithm for Pulse D...

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5th IEEE Information technology, Networking, Electronic and Automation Control Conference, ITNEC 2021

作者： Dong, Wenhao Wang, Jingyi Song, Zhiyong Fu, Qiang National University of Defense Technology National Key Laboratory of Science and Technology on Automatic Target Recognition College of Electronic Science Changsha410073 China

ISBN: (纸本)9781665415989

In order to improve the detection sensitivity of pulse Doppler (PD) radar, a joint detection and state estimation algorithm based on random finite set is proposed. In the framework of formal Bernoulli filter, the state model and observation model of the algorithm are designed at the range-Doppler (RD) echo signal level when there is only a single target, which makes full use of the dynamic difference of phase and amplitude change between target and background. Since the state vector can be divided into linear and non-linear parts, Rao-Blackwellized particle filter (RB-PF) is used to realize the prediction and update of the state vector. The simulation results show that the algorithm can effectively improve the state estimation accuracy and detection sensitivity. © 2021 IEEE.

关键词： State estimation

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