{"title":"论分布式雷达网络:信号模型、分析和信号处理","authors":"Vinzenz Janoudi;Pirmin Schoeder;Timo Grebner;Nils Appenrodt;Juergen Dickmann;Christian Waldschmidt","doi":"10.1109/JMW.2024.3414471","DOIUrl":null,"url":null,"abstract":"A key aspect of the imaging capability of radar systems is the angular resolution, which is determined by the aperture size of the antenna array. Therefore technologies such as MIMO and especially radar networks consisting of multiple independent MIMO radar sensors seek to maximize the virtual aperture size. Depending on the range and velocity resolution of the MIMO radar network, multistatic aspects must be accounted for. So far, those multistatic effects were seen as errors, which must be compensated for in order to restore the classical DoA properties of the virtual aperture, described by the narrowband beam pattern. This paper shows that new virtual aperture designs with larger antenna spacings are possible while still preserving the angular ambiguity range of smaller antenna spacings, as long as the multistatic effects of distributed radar networks, namely radar networks whose virtual aperture is large in comparison to the range resolution, are correctly accounted for. The larger antenna element spacing enables larger aperture sizes leading to higher angular resolution. This paper illustrates that the well-known, Fourier Tranformation-based signal processing is unable to exploit this potential of distributed radar networks, and an computationally efficient approximated matched filter is proposed. This article presents a signal model for distributed radar networks, suitable signal processing, and a comparison to the well-known Fourier Transformation-based signal processing for compact radar networks. Both the signal model and the proposed signal processing are verified by measurements with a radar sensor network composed of 2 MIMO radar sensors operating in the automotive frequency range of \n<inline-formula><tex-math>$76 \\,\\mathrm{G}\\mathrm{Hz}\\,\\mathrm{to}\\, 81 \\,\\mathrm{G}\\mathrm{Hz}$</tex-math></inline-formula>\n providing 64 virtual channels with a range resolution of \n<inline-formula><tex-math>$0.03 \\,\\mathrm{m}$</tex-math></inline-formula>\n. 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Therefore technologies such as MIMO and especially radar networks consisting of multiple independent MIMO radar sensors seek to maximize the virtual aperture size. Depending on the range and velocity resolution of the MIMO radar network, multistatic aspects must be accounted for. So far, those multistatic effects were seen as errors, which must be compensated for in order to restore the classical DoA properties of the virtual aperture, described by the narrowband beam pattern. This paper shows that new virtual aperture designs with larger antenna spacings are possible while still preserving the angular ambiguity range of smaller antenna spacings, as long as the multistatic effects of distributed radar networks, namely radar networks whose virtual aperture is large in comparison to the range resolution, are correctly accounted for. The larger antenna element spacing enables larger aperture sizes leading to higher angular resolution. This paper illustrates that the well-known, Fourier Tranformation-based signal processing is unable to exploit this potential of distributed radar networks, and an computationally efficient approximated matched filter is proposed. This article presents a signal model for distributed radar networks, suitable signal processing, and a comparison to the well-known Fourier Transformation-based signal processing for compact radar networks. Both the signal model and the proposed signal processing are verified by measurements with a radar sensor network composed of 2 MIMO radar sensors operating in the automotive frequency range of \\n<inline-formula><tex-math>$76 \\\\,\\\\mathrm{G}\\\\mathrm{Hz}\\\\,\\\\mathrm{to}\\\\, 81 \\\\,\\\\mathrm{G}\\\\mathrm{Hz}$</tex-math></inline-formula>\\n providing 64 virtual channels with a range resolution of \\n<inline-formula><tex-math>$0.03 \\\\,\\\\mathrm{m}$</tex-math></inline-formula>\\n. 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引用次数: 0
摘要
雷达系统成像能力的一个关键方面是角度分辨率,它由天线阵列的孔径大小决定。因此,MIMO 等技术,特别是由多个独立 MIMO 雷达传感器组成的雷达网络,都在寻求最大化虚拟孔径尺寸。根据 MIMO 雷达网络的测距和速度分辨率,必须考虑多静态因素。迄今为止,这些多静态效应被视为误差,必须对其进行补偿,以恢复窄带波束模式所描述的虚拟孔径的经典 DoA 特性。本文表明,只要正确考虑到分布式雷达网(即虚拟孔径与测距分辨率相比较大的雷达网)的多静态效应,就有可能采用较大天线间距的新虚拟孔径设计,同时仍能保持较小天线间距的角模糊范围。天线元件间距越大,孔径也就越大,角度分辨率也就越高。本文说明了众所周知的基于傅立叶变换的信号处理无法利用分布式雷达网络的这一潜力,并提出了一种计算效率高的近似匹配滤波器。本文介绍了分布式雷达网络的信号模型、合适的信号处理方法,并与著名的基于傅里叶变换的紧凑型雷达网络信号处理方法进行了比较。该信号模型和所提出的信号处理方法都通过一个雷达传感器网络的测量得到了验证,该雷达传感器网络由2个MIMO雷达传感器组成,工作在汽车频率范围为76 \ \mathrm{G}\mathrm{Hz} \ \mathrm{to}\, 81 \ \mathrm{G} \mathrm{Hz}$ ,提供64个虚拟信道,量程分辨率为0.03 \ \mathrm{m}$ 。雷达网络的虚拟孔径大小为${\sim }0.5 \mathrm{m}$ ,虚拟天线间距为波长的两倍,但拟议的信号处理仍可在 180 \mathrm{^{\circ }}$ 的完整范围内进行明确的 DoA 估计。
On Distributed Radar Networks: Signal Model, Analysis, and Signal Processing
A key aspect of the imaging capability of radar systems is the angular resolution, which is determined by the aperture size of the antenna array. Therefore technologies such as MIMO and especially radar networks consisting of multiple independent MIMO radar sensors seek to maximize the virtual aperture size. Depending on the range and velocity resolution of the MIMO radar network, multistatic aspects must be accounted for. So far, those multistatic effects were seen as errors, which must be compensated for in order to restore the classical DoA properties of the virtual aperture, described by the narrowband beam pattern. This paper shows that new virtual aperture designs with larger antenna spacings are possible while still preserving the angular ambiguity range of smaller antenna spacings, as long as the multistatic effects of distributed radar networks, namely radar networks whose virtual aperture is large in comparison to the range resolution, are correctly accounted for. The larger antenna element spacing enables larger aperture sizes leading to higher angular resolution. This paper illustrates that the well-known, Fourier Tranformation-based signal processing is unable to exploit this potential of distributed radar networks, and an computationally efficient approximated matched filter is proposed. This article presents a signal model for distributed radar networks, suitable signal processing, and a comparison to the well-known Fourier Transformation-based signal processing for compact radar networks. Both the signal model and the proposed signal processing are verified by measurements with a radar sensor network composed of 2 MIMO radar sensors operating in the automotive frequency range of
$76 \,\mathrm{G}\mathrm{Hz}\,\mathrm{to}\, 81 \,\mathrm{G}\mathrm{Hz}$
providing 64 virtual channels with a range resolution of
$0.03 \,\mathrm{m}$
. The virtual aperture size of the radar network is
${\sim }0.5 \,\mathrm{m}$
with virtual antenna spacing of twice the wavelength, but the proposed signal processing still allows unambiguous DoA estimation within the full
$180 \,\mathrm{^{\circ }}$
range.