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A novel OFDM-MIMO radar with non-equidistant subcarrier interleaving and compressed sensing

机译:具有非等距子载波交织和压缩感知的新型OFDM-MIMO雷达

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A novel concept of orthogonal frequency division multiplexing (OFDM) multiple input multiple output (MIMO) radar for automotive applications is presented in this paper. Multiple transmit antennas are multiplexed via OFDM subcarrier interleaving. Such a multiplexing enables a simultaneous operation of transmit antennas, while the complete bandwidth is utilized by each of them. Whereas the known OFDM-MIMO radar concepts perform multiplexing via equidistant subcarrier interleaving, we propose the use of non-equidistant subcarrier interleaving for multiplexing of transmit antennas. The advantage of this approach over the equidistant interleaving is the full unambiguously measurable distance range, not reduced through the subcarrier interleaving. To cope with the increased sidelobes in distance estimation due to the non-equidistant subcarrier interleaving, we propose a novel two-dimensional distance-velocity estimation algorithm based on compressed sensing that incorporates the radar images from all antennas. The proposed algorithm is able to detect weak targets, originally masked by the sidelobes of more dominant ones.
机译:本文提出了一种用于汽车应用的正交频分复用(OFDM)多输入多输出(MIMO)雷达的新颖概念。多个发射天线通过OFDM子载波交织进行复用。这种多路复用使得发射天线能够同时工作,而每个天线都利用了完整的带宽。尽管已知的OFDM-MIMO雷达概念是通过等距子载波交织来执行复用的,但我们建议使用非等距子载波交织来进行发射天线的复用。与等距交织相比,这种方法的优势在于可以完整地测量整个距离范围,而不会通过子载波交织而减小。为了应对由于非等距子载波交织而导致的距离估计中增加的旁瓣,我们提出了一种基于压缩感测的新型二维距离-速度估计算法,该算法结合了来自所有天线的雷达图像。所提出的算法能够检测到较弱的目标,该目标最初被更具优势的目标的旁瓣掩盖。

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