Designing OFDM radar waveform for target detection using multi-objective optimization

We propose a multi-objective optimization (MOO) technique to design an orthogonal frequency division multiplexing (OFDM) radar signal for detecting a moving target in the presence of multipath reflections. We employ an OFDM signal to increase the frequency diversity of the system, as different scattering centers of a target resonate variably at different frequencies. Moreover, the multipath propagation increases the spatial diversity by providing extra looks at the target. First, we develop a parametric OFDM measurement model for a particular range cell under test, and convert it to an equivalent sparse-model by considering the target returns over all the possible signal paths and target velocities. Then, we propose a constrained MOO problem to design the spectral-parameters of the transmitting OFDM waveform by simultaneously optimizing three objective functions: maximizing the Mahalanobis distance to improve the detection performance, minimizing the weighted trace of the Cramér-Rao bound matrix for the unknown parameters to increase the estimation accuracy, and minimizing the upper bound on the sparse-recovery error to improve the performance of the equivalent sparse-estimation approach.