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

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

引用

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

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

引用

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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Improved Cardinalized Probability Hypothesis Density Filter for Multitarget Tracking Using Formation Priors

Improved Cardinalized Probability Hypothesis Density Filter ...

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IET International Radar Conference 2023, IRC 2023

作者： Jiang, Qi Zhang, Jichuan Ni, Na 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 Real-time Information Processing Technology of Embedded Beijing100081 China

ISBN: (纸本)9781839539954

Effective observation of group targets (bird flocks, etc.) has significant importance in aviation safety and ecological research. Closely spaced group targets with swarm intelligence can form huge and complex linear formations. Tracking radar must feature a narrow beam and high bandwidth to discriminate different targets within the formation. However, there are two major problems in formation target tracking. First, the number of targets within the beam may fluctuate with the change of radar-target geometry;second, false measurements may be detected from the distributed Doppler spectra. This paper proposes a cardinalized probability hypothesis density (CPHD) filter for multitarget tracking using the formation priors form a scanning radar. The model of false measurements is optimized based on the experimental data of birds. The densities of new targets and the probability of target death are set according to the formation priors of group structure and radar-target geometry. Finally, the effectiveness of the proposed method is verified by experimental results. © The Institution of Engineering & technology 2023.

关键词： Target tracking

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Remote Sensing Object Detection Based on Lightweight YOLO-V4 7

Remote Sensing Object Detection Based on Lightweight YOLO-V4

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7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering

作者： Li, Keng Cao, Yunfei Chen, He Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology 5 South Zhongguancun Street Haidian District Beijing China

ISBN: (纸本)9781510656437

The remote sensing object detection algorithms based on deep learning have high detection performances, but the network structures are too complexity to meet the real-time processing requirements in on-board remote sensing object detection. In order to solve this problem, we proposed a lightweight YOLO-v4 network, which is 76% smaller than the original YOLO-v4. As for the decrease of lightweight network's accuracy, we adopted the general instance distillation algorithm, which used the original YOLO-v4 network as the teacher network and whose detection accuracy achieved 2.1% mAP gain. © 2022 SPIE. All rights reserved.

关键词： Remote sensing

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SPACEBORNE SAR IMAGING SYSTEM WITH HIGH-PERFORMANCE POLYNOMIAL ENGINES

SPACEBORNE SAR IMAGING SYSTEM WITH HIGH-PERFORMANCE POLYNOMI...

引用

IET International Radar Conference 2023, IRC 2023

作者： Zhang, Zhihan Xu, Yinsheng Li, Yongrui Zhang, Ao Xie, Yizhuang 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 Shanghai Institute of Satellite Engineering Shanghai201109 China

ISBN: (纸本)9781839539954

In recent years, with the development of Synthetic Aperture Radar (SAR) technology, the required resolution and imaging bandwidth for spaceborne SAR have been continuously increasing, posing stringent requirements on real-time imaging systems. To address the issue of uneven computing power allocation in implementing the Chirp Scaling (CS) algorithm on an FPGA+DSP platform, a spaceborne SAR imaging system with high-performance polynomial engines was designed, which enables the mapping of the Taylor series-based Chirp Scaling algorithm onto a hardware platform. The system is implemented using Xilinx's XC7VX690T FPGA and TI's TMS320C6678 DSP. The high-performance polynomial engine is designed with a parallel pipeline structure, supporting computation of polynomial up to seventh order. It offers flexible configuration and high versatility. The spaceborne SAR imaging system with high-performance polynomial engines can achieve SAR imaging in 16K×16K resolution with a time of 15.64 seconds, meeting the requirements of real-time SAR imaging applications in large-scale data scenarios. © The Institution of Engineering & technology 2023.

关键词： Radar imaging

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Common Targets Polarimetric Calibration Technique for Long Blind Range Radar

Common Targets Polarimetric Calibration Technique for Long B...

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IET International Radar Conference 2023, IRC 2023

作者： Tan, Lijia Li, Weidong Wang, Rui Wang, Jiangtao Li, Muyang Hu, Cheng The Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China The Advanced Technology Research Institute Beijing Institute of Technology Jinan250300 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing100081 China

ISBN: (纸本)9781839539954

Many research indicates the importance of polarimetric information in radar systems for purposes such as detection, tracking, and parameter estimation. The calibration process is essential for obtaining precise polarimetric information. However, conducting calibration experiments for long blind range radars can be challenging in fields where ground clutter is prominent. For multi-pulse width switching radar, this paper introduces a polarimetric calibration algorithm by measuring common targets of short- and long-range waveforms. Firstly, we switch between various waveforms to measure the strong echo common targets in the overlapping detection range. The scattering matrices of common targets can be obtained by the short-range waveform calibrated by the conventional method. Then, the polarization error model is built based on the measured scattering matrices of long-range waveform, and the true values of the scattering matrices of common targets are used to estimate the polarization errors of long-range waveform. The effectiveness of the algorithm is validated through simulation results. © The Institution of Engineering & technology 2023.

关键词： Polarimeters

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The Optimal Partition Number Estimation Algorithm Based on Variational Inference

The Optimal Partition Number Estimation Algorithm Based on V...

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IET International Radar Conference 2023, IRC 2023

作者： Zhang, Jichuan Jiang, Qi Xu, Liang Wang, Rui Hu, Cheng The Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China The Advanced Technology Research Institute Beijing Institute of Technology Jinan250300 China The Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China

ISBN: (纸本)9781839539954

The partition of individual targets into proper clusters is crucial in tracking group targets with complex spatial structures. However, most of the current clustering methods suffer from heavy computation burdens and unfitting a priori knowledge, resulting in the degradation of robustness. This paper proposes an optimal estimate of partition number based on the variational inference for group targets. By maximizing the variational evidence lower bound, which serves as the model-selected criterion, the optimal partition number can be estimated. The K-means++ algorithm is used to initialize the variation iteration. The proposed algorithm does not require a priori information and has low computation complexity, which benefits from the deterministic approximation character of variational inference. The effectiveness of the proposed method is verified by simulation results. © The Institution of Engineering & technology 2023.

关键词： Consensus algorithm

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Research on Ground Clutter Polarization Suppression Algorithm Based on Prior information

Research on Ground Clutter Polarization Suppression Algorith...

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IET International Radar Conference 2023, IRC 2023

作者： Liu, Sheng Cai, Jiong Zhang, Jichuan Wang, Rui Hu, Cheng The Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China The Advanced Technology Research Institute Beijing Institute of Technology Jinan250300 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing100081 China

ISBN: (纸本)9781839539954

Low-altitude unmanned aerial vehicle (UAV) targets are challenging to detect by radar due to their low flight altitude, which exposes them to strong interferences from complex ground clutter. To address this, this paper proposes a ground clutter polarization suppression method based on prior information, facilitating the effective detection of low-altitude UAV targets. Initially, the method establishes a clutter prior information database and a clutter map according to the actual radar application environment, classifying different types of clutter. This serves as the prior information for clutter, supporting detection in the context of complex ground clutter backgrounds. Subsequently, a linear polarization filtering algorithm optimized based on maximizing the signal-to-clutter ratio (SCR) is proposed for specific clutter environments. A strong clutter point is selected from the clutter map, and the effectiveness of the algorithm proposed in this paper is analyzed and verified using real-world radar data collected from field measurements. The results indicate that the proposed algorithm improves the average signal-to-clutter ratio by 15.39 dB compared to single polarization channels. This method provides a reference for complex ground clutter polarization suppression and polarization detection. © The Institution of Engineering & technology 2023.

关键词： Unmanned aerial vehicles (UAV)

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Acceleration method for target HRRP generation based on DDPM 2

Acceleration method for target HRRP generation based on DDPM

引用

2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Shen, Xitai Zhou, Qiang Yu, Bingqian Zhang, Xin Wang, Yanhua Zhang, Liang Beijing Institute of Technology Zhengzhou Academy of Intelligent Technology Zhengzhou450000 China Beijing Institute of Technology Radar Technology Research Institute Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information: Processing Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

ISBN: (纸本)9798331515669

The target high resolution range profile (HRRP) is the sum of the vector projected on the radar line of sight of the target scatters, which can reflect the radial structure characteristics of the target and is one of the important means of radar target recognition. Existing HRRP-based target recognition methods adopt the idea of machine learning classification, which usually require sufficient training samples to obtain satisfactory recognition performance. To solve the dilemma of insufficient radar HRRP data caused by factors such as non-cooperative target and complexity of data acquisition process, this paper uses denoising diffusion probabilistic models (DDPM) to generate HRRP data. Furthermore, to solve the problem that the DDPM generation speed is too slow to meet the actual needs, this paper designs a fast DDPM HRRP (FDH) data generation method based on progressive knowledge distillation. Finally, the experimental results show that the generation speed is increased by about 25 times compared with the initial model under the premise of losing 7.6% similarity. © 2024 IEEE.

关键词： Radar target recognition

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Transductive Multi-Prototype Network for HRRP Recognition with Missing Aspects 2

Transductive Multi-Prototype Network for HRRP Recognition wi...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Yuan, Mingchen Liu, Jiaqi Wang, Xinyang Li, Yang Wang, Yanhua Zhang, Liang Beijing Institute of Technology Zhengzhou Academy Of Intelligent Technology Zhengzhou450000 China Radar Technology Research Institute Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information: Processing Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

ISBN: (纸本)9798331515669

The High-Resolution Range Profile (HRRP) plays a pivotal role in radar automatic target recognition. However, due to its aspect sensitivity, the absence of aspects within the training data can lead to a decline in recognition accuracy. To mitigate this issue, we introduce a novel Transductive Multi-Prototype Network (TMP-Net), leveraging the intrinsic similarity within test data to propagate labels along a manifold, thereby achieving classification. TMP-Net addresses the aspect sensitivity by utilizing multiple prototypes per class. Additionally, a loss function term is proposed to ensure the existence of the manifold. Experiments on the MSATR dataset demonstrate that TMP-Net outperforms existing methods by 10.22% in recognition accuracy even with only 10% of aspects represented in the training set. Furthermore, analysis reveals the advantages of employing multiple prototypes. © 2024 IEEE.

关键词： Automatic target recognition

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