Efficient Frequency Response Restoration of Electromagnetic Scattering Characters for Swarm Targets

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Jia Liu;Qun Yu Xu;Min Su
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引用次数: 0

Abstract

Swarm formulations are new derivations of uncrewed aerial vehicles (UAVs) applications with more extensive application potentials. Radar signature characters of noncooperative UAV swarm targets require a more comprehensive understanding. The multimodality property of dynamic swarm targets proposes new challenges to restudy their electromagnetic scattering signatures. A larger number of unknowns make it difficult for existing full-wave numerical solvers to model their frequency response of radar cross section (RCS). This article introduces a solution to restore swarm target electromagnetic scattering signatures efficiently under sweep-frequency conditions. Swarm targets are first modeled by equivalent principle analysis (EPA) as compositions of multiple uniform equivalent surfaces enclosing each swarm unit. Variational formulations of EPA models extract frequency-dependent terms for computation redundancy reduction. The reduced-basis method (RBM) calculates reduced-basis functions from training solution datasets. Frequency responses of electromagnetic scatterings at an arbitrary frequency point are restored as a linear composition of reduced-basis functions. Unknown transformations from surface currents to expansion coefficients elevate the solution restoration efficiency prominently. Numerical results for three representative low-altitude noncooperative swarm targets verify the RCS restoration accuracy and efficiency. More discussions are addressed to explore factors that influence reduced-basis numbers. Existing results indicate that the proposed method is applicable to study swarm target frequency responses at an arbitrary modality. Limitations and future works are discussed with respect to restoration efficiency and accuracy optimization.
群目标电磁散射特性的有效频率响应恢复
蜂群配方是无人机应用的新衍生产品,具有更广泛的应用潜力。非合作无人机群目标的雷达特征需要更全面的认识。动态群目标的多模态特性为重新研究其电磁散射特征提出了新的挑战。由于未知量较多,现有的全波数值求解方法难以对其雷达横截面(RCS)的频率响应进行建模。本文介绍了一种在扫频条件下有效恢复群目标电磁散射特征的方法。首先利用等效原理分析(EPA)将群体目标建模为包围每个群体单元的多个均匀等效曲面的组成。EPA模型的变分公式提取频率相关项以减少计算冗余。约简基方法(RBM)从训练解数据集计算约简基函数。电磁散射在任意频率点的频率响应被还原为约基函数的线性组合。从表面电流到膨胀系数的未知转换显著提高了溶液恢复效率。对三个具有代表性的低空非合作群目标进行了数值仿真,验证了RCS恢复的精度和效率。进一步探讨了影响约基数的因素。已有结果表明,该方法适用于研究任意模态下的群目标频率响应。讨论了修复效率和精度优化方面的局限性和未来的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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