计算机科学
雷达
脉冲响应
雷达成像
人工智能
匹配滤波器
波形
雷达跟踪器
模式识别(心理学)
滤波器(信号处理)
算法
计算机视觉
数学
电信
数学分析
作者
Caden J. Pici,Sastry Kompella,Ram M. Narayanan
出处
期刊:IEEE Transactions on Aerospace and Electronic Systems
[Institute of Electrical and Electronics Engineers]
日期:2023-02-01
卷期号:59 (1): 184-195
标识
DOI:10.1109/taes.2022.3187387
摘要
Waveform design is a commonly used approach to enhance target classification in high resolution radar systems. In the monostatic case of detecting some extended target, inherent to many of these system models is an assumption of a known target impulse or frequency response. A practical issue with this method is that for nonsimple target cases, such a response can change drastically for varying aspect or viewing angles. In this paper, we first develop a sparse regression method for classifying target class and aspect angle. Next, we derive matched filters tailored to dictionaries of target response profiles representing these variations in aspect angle. The desirable goal of real-time classification is met by suitably reducing the computational cost and not relying on a series of measurement and adaption cycles to achieve classification. The result is a series of filters matched to the target dictionary data and can be used in a hypothesis testing approach to classification. Results are shown for radar cross-sectional data generated from computer-aided design models of different targets.
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