Joint DFT-ESPRIT Estimation for TOA and DOA in Vehicle FMCW Radars


This letter proposes a joint discrete Fourier remodel (DFT)-estimation of signal parameters via rotational invariance techniques (ESPRIT) estimator for time-of-arrival (TOA) and direction-of-arrival (DOA) in vehicle frequency-modulated continuous-wave (FMCW) radars. Since the vehicle FMCW radar ought to acknowledge vehicles within the side/rear space when the motive force initiates a lane amendment, the estimation of the joint TOA/DOA between the radar and targets is an important issue for solving complicated location tasks. However, standard joint estimation ways like 2D-ESPRIT and 2D-multiple signal classification (MUSIC) can't be adopted for real-time implementation due to their high computational hundreds. To satisfy the specified accuracy specifications and scale back complexity compared with the conventional estimator, we propose a low-complexity joint TOA and DOA estimator that uses the combined DFT-ESPRIT algorithm for FMCW radars. The performance of the proposed estimation in multitarget environments was derived and compared with the Monte Carlo simulation results. The root-mean-square error (RMSE) of the proposed technique was compared with that of 2D-ESPRIT with various parameters. To verify the performance of the proposed combination method, we tend to implemented the FMCW radar and verified its performance in an anechoic chamber setting.

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