Differential evolution algorithm to jointly estimate the target parameters in a MIMO OFDM DFRC system

When dealing with dual-function Radar and communication systems equipped with multiple antennas and based on orthogonal frequency division multiplexing, the target parameters, i.e., the direction of arrival (DOA), the range and the velocity have to be estimated. In some approaches like those based on the Fourier transform, the estimations of the range and the velocity require the DOA estimates beforehand. This can be problematic if the DOA estimation is not accurate enough. In others like those based on subspace methods, the target parameters can be estimated independently, but a posteriori pairing of the parameter estimates for each target is required along with constraints on the data to be transmitted. In this paper, to avoid the above issues, we suggest analyzing the relevance of the joint estimation of the target parameters by using an evolutionary algorithm like a differential-evolution based method. In that case, various aspects must be addressed such as the definition of the loss function, the selection of the stopping criterion and the tuning of the control parameters. However, a question remains: to what extent can we have confidence in the solution obtained after convergence of the algorithm? For this reason, we selected a loss function allowing us to add a final step to check whether the parameter estimation can be relevant or not. Finally, we present some results of the proposed method and discuss its limitations related to the number of targets in relation to the number of observations available.