Parameter estimation of non-uniform sampled polynomial-phase signals using the HOCPF-WD

Parameter estimation of non-uniformly sampled polynomial-phase signals (PPSs) is addressed in this paper. It is assumed that signals are sampled below the rate required by the sampling theorem. The recent advance in the field, based on combining the high-order cubic phase function (HO-CPF) and high-order Wigner distribution (HO-WD), has been applied for parameter estimation of such signals. Two cases of the sampling scheme are considered: (i) random sampling with symmetrically distributed samples around the middle point in the time interval and (ii) random sampling without the symmetry. A performance analysis is conducted showing high estimation accuracy even for large percentage of missing samples with the later case giving, as expected, slightly worse results than the former one.