Supervised reciprocal filter for OFDM radar signal processing

In this paper, we address the problem of the range-Doppler map evaluation in continuous wave radar exploiting OFDM signals. This stage is usually implemented by resorting to a suboptimal batches algorithm and a typical choice is to fragment the signal in batches with length equal to the OFDM symbol length and to apply at each batch an appropriate range compression strategy: typically, either Matched Filter (MF) or Reciprocal Filter (RF). The former provides the best performance against noise-limited scenarios, whereas the latter against clutter-limited scenarios, thanks to its high Peak SideLobe Level (PSL). Using “OFDM fragmentation” requires symbol synchronization and sets constraints on the coherent processing chain; moreover, we show that it provides a Signal-to-Noise Ratio (SNR) loss both when using MF and RF. Therefore, we investigate the case of “non-OFDM fragmentation”, which does not require synchronization and avoids setting constraints on the processing chain. Specifically, we address the case of batch lengths longer than a single OFDM symbol that can potentially reduce the SNR loss at long ranges. We find that this is effective for the MF, but causes an even higher SNR loss for the direct application of the RF filter, which still provides a low level of sidelobes. Aiming at preserving the potential benefits of the RF over the MF against the clutter-limited scenarios, we propose some modified versions of the RF for the non-OFDM fragmentation case, which are shown to offer a trade-off between SNR losses and sidelobes level control. The effectiveness of the proposed approaches is demonstrated both by providing theoretical performance prediction expressions and by using simulated analyses. To this purpose, a case study is considered for a passive radar exploiting DVB-T transmissions.