Communication-Aided Target State Estimation in a Cooperative Radar-Communication System

Abstract

In recent years, the research community has gained more interest in spectral cooperation between radar and communication systems. This article introduces a communication-aided radar measurement model as a function of transmitted waveforms in a cooperative radar-communication system (CRCS). For this investigation, a linear frequency-modulated (LFM) pulse radar waveform, a nonlinear frequency-modulated pulse radar waveform, and a quadrature amplitude-modulated (QAM) communication waveform are considered, and the target state estimation performance is analyzed. At a given epoch, the target’s position is estimated by considering the range and the range rate as measurements in an iterative least-squares (ILS) framework. After that, the Kalman filter (KF) is used to estimate the target dynamics using converted measurements. In addition, the error in the estimated position of the target is quantified with the root-mean-square error (RMSE) and the posterior Cramér-Rao lower bound (PCRLB). Eventually, the simulated results convey that the combination of the nonlinear frequency modulation (NLFM) radar waveform and the QAM communication waveform is more suitable for the estimation of the target state than the other combination (LFM radar waveform and QAM communication waveform).