This paper addresses the problem of channel estimation in 5G-enabled vehicular-to-vehicular (V2V) channels with high-mobility environments and non-stationary feature. Considering orthogonal frequency division multiplexing (OFDM) system, we perform extended Kalman filter (EKF) for channel estimation in conjunction with Iterative Detector Decoder (IDD) at the receiver to improve the estimation accuracy. The EKF is proposed for jointly estimating the channel frequency response and the time-varying time correlation coefficients. And the IDD structure is adopted to reduce the estimation errors in EKF. The simulation results show that, compared with traditional methods, the proposed method effectively promotes the system performance.