Object Detection and Tracking Based on OFDM Communication Waveform

Abstract

In this paper, the application of the orthogonal frequency division multiplexing (OFDM) waveform in integrated radar and communication (ISAC) scenario is considered. With realization of precise tracking with less bandwidth, it is regarded as significant application value. For an object moving in a 2-dimension plane, a detecting and tracking model with minimized position error is designed. By analyzing OFDM waveforms and their reflected waveforms by fast Fourier transform (FFT), the position of the measured object can be measured. In linear 1-demision systems, Kalman filter (KF) is used to eliminate the errors in OFDM measurement. In nonlinear 2-dimension scenario, the measured results are optimized by extended Kalman filter (EKF) after the system is linearized by Taylor expansion. Simulation results verify the reliability of this approach combined by OFDM waveform and EKF in a certain range of signal to noise ratio.