Performance analysis of joint range and velocity estimation in OFDM-IM-based RadCom system

Modulation symbol domain (MSD) method is usually applied in range and velocity estimation for the radarcommunication (RadCom) shared system based on orthogonal frequency-division multiplexing with index modulation (OFDM-IM). Nevertheless, the deterioration of sidelobe characteristics significantly impairs the efficacy of both range and velocity estimation. In this paper, we propose a modulation symbol domain-spatial sparsity-compressed sensing (MSD-SS-CS) method to realize super resolution joint range and velocity estimation for the RadCom shared system based on OFDM-IM. The compressed sensing theory is used in MSD method to solve the problem of detection targets that meet spatial sparsity application scenarios. Simulation outcomes illustrate that the bit error rate (BER) performance of the RadCom shared system, leveraging OFDM-IM, surpasses that of the RadCom shared system relying solely on OFDM. The proposed MSD-SS-CS method not only solves the degradation of sidelobe caused by blank sub-carriers in the RadCom shared system based on OFDM-IM, but also achieves good super resolution joint range and velocity estimation.