ABSTRACT
Due to the flourishing development of vehicle-to-vehicle (V2V) communications and autonomous driving, interference between radar sensing and communication signals becomes a challenging issue. We propose a transmit beamforming based spectrum sharing scheme to achieve peaceful coexistence between automotive multiple-input multiple-out (MIMO) radar and communication systems. Our objective is to maximize the signal-to-interference-plus-noise ratio (SINR) of the automotive radar receiver subject to the communication capacity and the transmitted power budget constraints to optimize both the communication covariance matrix and the radar transmit precoder. The formulated optimization problem is non-convex, which is converted to convex by introducing a new slack variable and then solving it using the block coordinate descent, also called alternation optimization, approach. Additionally, the ellipsoid sub-gradient method is then employed to reduce the computational complexity. Simulation results demonstrate that our proposed scheme outperforms the conventional schemes.
ABSTRACT
In order to know the feasibility that the modern spectrum analysis ways are applied in wind profiler, the fast Fourier transform (FFT) and maximum entropy method (MEM) are contrasted by using simulation data and radar measurement data respectively. The result shows: (1) When the radar echo is strong, the effect of two methods are equivalent. But when the echo is weak, the MEM spectra are better than others. The MEM can powerfully remove the ground clutter contaminant. (2) The MEM spectra are smooth, so it can be used to reduce white noise influence also. (3) The iterative steps in MEM have some influence on the spectrum. The step calculated by final prediction error (FPE) rule is less. Using 15 steps in MEM can get a better result. The wind profiler radar echo is weak usually, so the conclusions of this paper can help improve the effect of spectrum analysis.