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On Binary Sequence Set Design with Applications to Automotive Radar

机译:二元序列集设计及其在汽车雷达中的应用

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We consider herein the case of two vehicles equipped with multi-input multi-output (MIMO) automotive radars driving next to each other. We assume that 5G communications allow us to coordinate the radar probing waveforms for the vehicles. Then the binary sequence sets transmitted by different vehicles should meet the requirement that the cross-correlations of the sequence sets between vehicles are as low as possible for all time lags, while the auto-correlation sidelobes and cross-correlations within a low correlation zone (LCZ) of the binary sequence sets transmitted by each vehicle are lower than a desired level. We establish an optimization problem to realize these goals. We consider the coordinate-descent (CD) framework and we solve the optimization problem efficiently by taking full advantage of the fast Fourier transforms (FFTs) and introducing computationally efficient updating procedures within the CD iterations. Numerical examples are provided to demonstrate that the proposed algorithms can be used to effectively and efficiently design binary sequence sets, including long sequence sets, useful for MIMO automotive radar applications.
机译:我们在这里考虑两辆配备有多输入多输出(MIMO)汽车雷达彼此相邻行驶的车辆的情况。我们假设5G通信可以使我们协调车辆的雷达探测波形。然后,不同车辆传输的二进制序列集应满足以下要求:在所有时滞中,车辆之间的序列集的互相关关系应尽可能低,而低相关区域内的自相关旁瓣和互相关关系(每个车辆发送的二进制序列集的LCZ都低于所需水平。我们建立优化问题以实现这些目标。我们考虑了协调下降(CD)框架,并充分利用了快速傅立叶变换(FFT)并在CD迭代中引入了计算有效的更新过程,从而有效地解决了优化问题。提供了数值示例,以证明所提出的算法可用于有效和高效地设计二进制序列集,包括长序列集,可用于MIMO汽车雷达应用。

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