On Binary Sequence Set Design With Applications To Automotive Radar
Ronghao Lin, Jian Li
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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.