Model-Based Joint Delay-Doppler Estimation for ICAS with Sparse OFDM Resources

Studies have shown that OFDM waveforms are promising candidates for dual functionality radar and communication networks. However, when the transmitted OFDM frame contains sparsely and arbitrarily allocated resources, periodogram based target estimation suffers from high side-lobes and poor multi-path resolution. We propose an iterative multi-path joint delay-Doppler estimator for OFDM waveforms with sparse and possibly unstructured Frequency-Time resources. We show through simulations that model-based methods achieve greater than Rayleigh resolution without the need for additional interpolation of the sampled channel transfer function. Furthermore, the estimation error as function of delay and Doppler separation is studied and shown to approach the CRB. To address issues of computational complexity, we simplify the exhaustive search step commonly found in Maximum-Likelihood based estimators and propose the use of Fischer-scored gradient optimization that requires only a small number of updates to enhance estimation accuracy.