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Distributed multi-target tracking with labeled multi-Bernoulli filter considering efficient label matching

Frontiers of Information technology & Electronic Engineering 2025年第3期26卷 400-414页

作者： Changwen DING Chuntao SHAO Siteng ZHOU Di ZHOU Runle DU Jiaqi LIU School of Astronautics Harbin Institute of TechnologyHarbin 150001China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing 100076China

We propose a distributed labeled multi-Bernoulli(LMB)filter based on an efficient label matching *** distributed LMB filter fusion has the premise that the labels among local densities have already been ***,considering that the label space of each local posterior is independent,such a premise is not practical in many *** achieve distributed fusion practically,we propose an efficient label matching method derived from the divergence of arithmetic average(AA)mechanism,and subsequently label-wise LMB filter fusion is performed according to the matching *** with existing label matching methods,this proposed method shows higher performance,especially in low detection probability ***,to guarantee the consistency and completeness of the fusion outcome,the overall fusion procedure is designed into the following four stages:pre-fusion,label determination,posterior complement,and uniqueness *** performance of the proposed label matching distributed LMB filter fusion is demonstrated in a challenging nonlinear bearings-only multi-target tracking(MTT)scenario.

关键词： Distributed multi-sensor multi-target tracking Labeled multi-Bernoulli filter Arithmetic average fusion Label matching

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Characteristic Mode Design of Dual-Band Reconfigurable Frequency Selective Surface

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Chinese Journal of Electronics 2022年第6期31卷 1129-1137页

作者： NING Zihao LI Mengmeng DING Dazhi AI Xia LIU Jiaqi Department of Communication Engineering Nanjing University of Science and Technology National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics

In this paper, a characteristic mode design of dual-band reconfigurable frequency selective surface(RFSS) with transmission/reflection band is presented. Through the visualization of modal behavior, the theory of characteristic modes(TCM) is used to guide design from a physical perspective. At first, the dominant modes of two basic structures that have a major impact on reflection are clarified by observing the modal *** appropriate combination of the two structures forms an initial element with bandpass properties. Then, the positive-intrinsic-negative(PIN) diode is placed in the middle of the microstrip line and as the state shifts from ON to OFF, the dominant mode resonant frequency of the microstrip line shifts upward. Such a feature can be used to design the transmission/reflection RFSS. Experimentally, a dual-band RFSS operating at 8.8 GHz and 10.4 GHz is designed and fabricated. The measured results that agree with the full-wave simulation validate the proposed TCM-based design.

关键词： dual-band reconfigurable frequency selective surface dual-band RFSS positive-intrinsic-negative diode theory of characteristic modes characteristic mode design full-wave simulation transmission band p-i-n diodes modal behavior visualization bandpass properties microstrip lines microstrip line dominant mode resonant frequency PIN diode microwave filters frequency selective surfaces TCM-based design reflection band transmission RFSS microwave diodes band-pass filters microstrip filters reflection RFSS

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Electromagnetic Computational Modeling and Bistatic Scattering Characteristics Analysis of Spherical Jammer Group

Electromagnetic Computational Modeling and Bistatic Scatteri...

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2024 International Conference on Intelligent Communication, Sensing and Electromagnetics, ICSE 2024

作者： Xin, Wei Liu, Xin Wang, Weidong National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing187023 China

ISBN: (纸本)9798350354935

Bistatic radar is widely used in the military field with its good anti-jammer ability and accurate detection and identification ability. How to implement effective jammer for this kind of radar system has become a research hotspot at present. Due to the small scattering intensity and weak echo energy of j ammer monomer, it has no advantage in countering the bistatic radar. It is necessary to release multiple jammers to form a group to form strong scattering, so as to interfere with the bistatic radar to detect and recognize the target, so the study on the scattering characteristics of the jammer group is particularly important. Therefore, this paper takes the group composed of spherical monomer as an example, first of all, MATLAB and CST STUDIO SUITE (CST) are used for joint modeling, and then electromagnetic simulation calculation is carried out on the group of spherical jammer objects with different bands, different sphere sizes, different group densities and different group distributions to analyze the bistatic scattering characteristics under different parameters. The research results show that the four parameters will have different degrees of influence on the bistatic scattering characteristics of the spherical jammer group, which provides a theoretical basis and data support for parameter selection and airspace planning against the bistatic radar. © 2024 IEEE.

关键词： Spheres

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Predicting Electromagnetic Response of Electromagnetic Metasurface using Deep Learning 15

Predicting Electromagnetic Response of Electromagnetic Metas...

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15th International Conference on Signal Processing Systems, ICSPS 2023

作者： Yang, Bingyan Wang, Qiong Mu, Lei School of Electronic Science and Engineering Nanjing University China Key Laboratory of Science and Technology on Test Physics & Numerical Mathematical Beijing100076 China

ISBN: (纸本)9781510675056

Digitally coded metasurface(DMS) is a novel class of electromagnetic materials that possess the ability to manipulate electromagnetic waves at scales significantly smaller than the wavelength. They hold great potential for a wide range of applications, including wireless communication, millimeter-wave imaging, data storage, and sensing. However, the conventional full-wave simulation methods currently employed often require precise geometric modeling, grid planning, and consideration of complex physical models such as material parameters and boundary conditions. These time-consuming and costly approaches face significant challenges in large-scale electromagnetic response studies. Therefore, there is an urgent need to explore more efficient and cost-effective methods to address these issues. In this paper, we propose a deep learning-based approach for predicting the electromagnetic response of individual units in a DMS. We construct a convolutional neural network (CNN) model that can accurately and real-time predict the electromagnetic response based on the input coding pattern. To train and validate the model, we utilize a substantial amount of electromagnetic simulation data and incorporate amplitude constraints into the loss function for model optimization. A way to abandon the dual network structure and achieve simultaneous prediction of dual parameters with smaller computational requirements. Experimental results demonstrate that our model achieves highly accurate predictions of both amplitude and phase responses of DMS, surpassing traditional numerical methods in terms of efficiency and scalability. The proposed deep learning approach offers a promising solution for efficient and low-cost prediction of electromagnetic responses in DMS. © 2024 SPIE.

关键词： Neural network models

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Characteristic Mode Analysis for Thin Dielectric Sheets with Alternative Surface Integral Equation

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Chinese Journal of Electronics 2022年第6期31卷 1181-1188页

作者： JIA Chunlai HE Zi DING Dazhi GUAN Ling AI Xia LIU Jiaqi CHEN Xuewen Department of Communication Engineering Nanjing University of Science and Technology Science and Technology on Electromagnetic Scattering Laboratory Beijing Institute of Environmental Features National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics School of Physics and Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology

When the dielectric sheet is electrically thin in the normal direction, the conventional volume integral equation(VIE) can be approximately simplified to the surface one. On this basis, a novel surface integral equation-based formulation is presented for analyzing characteristic mode(CM) of thin dielectric sheets. The resultant CMs are expressed with tangential and normal components of electric volume currents, which are more intuitive than the conventional VIE-based one. Due to the application of volume equivalence principle, the proposed formulation is immune to non-physical modes. The CMs of typical thin dielectric bodies, including the dielectric substrate and radome, are analyzed to show that the proposed formulation is computationally efficient with encouraging accuracy.

关键词： normal components alternative surface integral equation thin dielectric sheets normal direction electric volume currents dielectric sheet radome radomes dielectric bodies surface integral equation-based formulation volume equivalence principle thin dielectric bodies tangential components nonphysical modes electromagnetic wave scattering conventional volume integral equation integral equations characteristic mode analysis dielectric substrate

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Multiple model PHD filter for tracking sharply maneuvering targets using recursive RANSAC based adaptive birth estimation

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Journal of Systems Engineering and Electronics 2024年第3期35卷 780-792页

作者： DING Changwen ZHOU Di ZOU Xinguang DU Runle LIU Jiaqi School of Astronautics Harbin Institute of TechnologyHarbin 150001China School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing 100076China

An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as drones and agile *** probability hypothesis density (PHD) filter, which propagates only the first-order statistical moment of the full target posterior, has been shown to be a computationally efficient solution to multitarget tracking problems. However, the standard PHD filter operates on the single dynamic model and requires prior information about target birth distribution, which leads to many limitations in terms of practical applications. In this paper,we introduce a nonzero mean, white noise turn rate dynamic model and generalize jump Markov systems to multitarget case to accommodate sharply maneuvering dynamics. Moreover, to adaptively estimate newborn targets’information, a measurement-driven method based on the recursive random sampling consensus (RANSAC) algorithm is proposed. Simulation results demonstrate that the proposed method achieves significant improvement in tracking multiple sharply maneuvering targets with adaptive birth estimation.

关键词： multitarget tracking probability hypothesis density(PHD)filter sharply maneuvering targets multiple model adaptive birth intensity estimation

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Online Tuning of Pre-trained Deep Neural Network for Guidance Against Non-cooperative Pursuer

Online Tuning of Pre-trained Deep Neural Network for Guidanc...

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2022 IEEE International Conference on Aerospace Electronics and Remote Sensing technology, ICARES 2022

作者： Du, Runle Shu, Yi Liu, Jiaqi Chen, Yang National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (数字)9781665461917

ISBN: (纸本)9781665461917

In the astronautics, it is widely acknowledged as a hard problem that using neural network to handle the intelligent observation and guidance when dealing with non-cooperative pursuing vehicles. Due to the difficulty of obtaining training data set from non-cooperative vehicles, the inconsistency between training data and utilization data, application of neural network controller is by far very limited. In order to tackle this problem, an online tuning scheme of neural network is proposed in this paper aiming to boost the observation and counter action abilities against non-cooperative pursuer. In the proposed methodology, the deep neural network controller is pre-trained through dataset from generative network before deployment, and fine-tuned online through real time observations data set. In this way, the calculation pressure is alleviated for onboard computer and the contribution of real time observation data set is utilized more correctly, thus guaranteeing the efficiency and effectiveness of online tuning. Simulation results suggested that, both in the observation ability and counteractive guidance to avoid the pursuer, the proposed method all trumped traditional networks without online tuning, which resulting a higher chance to survive the pursuit. © 2022 IEEE.

关键词： Deep neural networks

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An Absorptive/Transmissive Frequency Selective Surface with Wide Transmission Band and Low Insertion Loss

An Absorptive/Transmissive Frequency Selective Surface with ...

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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Song, Hang Liu, Jiaqi Zhang, Shengjun National Key Laboratory of Science & Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (纸本)9781665452366

The Absorptive/transmissive Frequency Selective Surface (ATFSS) is a multi-layer composite periodic structure with out-of-band absorption and in-band transmission characteristics, usually composed of a lossy resistive sheet (RS) and a lossless bandpass FSS. In this paper, an equivalent circuit method based on transmission line theory was used to design the ATFSS with idea of higher frequencies for transmission and lower frequencies for absorption, as well as the impedance conditions for satisfying wave transmission and absorption. Furthermore, the S-parameters was fitted, which verifies the design concept. Finally, the simulation was performed with numerical method. It is shown from the simulation that the broadband absorption of the ATFSS ranges from 2.00 GHz to 6.29 GHz, and the broadband transmission ranges from 8.46 GHz to 11.32 GHz with an insertion loss of less than 1 dB. © 2022 IEEE.

关键词： Frequency selective surfaces

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Simulation and analysis of repeater deceptive jamming to SAR based on shift-frequency

Simulation and analysis of repeater deceptive jamming to SAR...

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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Li, Daixuan Liu, Jiaqi Li, Jianhua Gao, Lu Zheng, Pei He, Zhonghang National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (纸本)9781665452366

With the change of battlefield form, the pressure jamming requires the jammer to have large power, and the jamming efficiency is low, so the spoofing jamming comes into being. In this paper, the linear frequency modulation signal and fuzzy function are analyzed to verify the feasibility of using frequency shift forwarding to generate virtual images, and the two-dimensional frequency shift method is used to generate virtual images at specific locations to deceive local radar. © 2022 IEEE.

关键词： Synthetic aperture radar

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Semantic Segmentation Algorithm of Street View Image Via Deep Learning

Semantic Segmentation Algorithm of Street View Image Via Dee...

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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Zhu, Zihui Cai, Wenlin Li, Jianhua Xue, Feng Gao, Lu Liu, Jiaqi National Key Laboratory Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (纸本)9781665452366

Real-time semantic segmentation of street view images can be used as a visual aid system during autonomous driving. This paper proposes a multi-branch cross-layer fusion network (MCFNet). The model uses a multi-branch network to extract features, fuses the features of different stages of multiple branches for prediction, and uses a lightweight depthwise separable convolution to reduce the amount of computation. We use the Cityscapes dataset to train and evaluate the algorithm and get 61.6% mIoU and 115.3 fps. © 2022 IEEE.

关键词： Convolution

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