An efficient near-optimal approach to incoherent scatter radar parameter estimation

We present a computationally efficient, near-optimal approach to the estimation of ionospheric parameters from incoherent scatter radar measurements. The method consists of removing the range smearing of ionospheric autocorrelation function via a set of 1-D deconvolutions and performing nonlinear least squares fitting on the deconvolved autocorrelation functions. To stabilize the solution in the presence of noise, we incorporate regularization techniques. The computational cost is reduced significantly by estimating the ionospheric parameters at individual altitudes, in comparison to full-profile-type analysis, which attempts to estimate ionospheric parameters at all altitudes simultaneously. The performance of the new technique is evaluated in a numerical example and is shown to give estimates of almost equal quality as the full-profile technique but at a 95% reduction in computation.