In ionospheric tomography, the atmospheric electron density is reconstructed from different electron density related measurements, most often from ground-based measurements of satellite signals. Typically, ionospheric tomography suffers from two major complications. First, the information provided by measurements is insufficient and additional information is required to obtain a unique solution. Second, with necessary spatial and temporal resolutions, the problem becomes very high dimensional, and hence, computationally infeasible. With Bayesian framework, the required additional information can be given with prior probability distributions. The approach then provides physically quantifiable probabilistic interpretation for all model variables. Here, Gaussian Markov random fields (GMRFs) are used for constructing the prior electron density distribution. The use of GMRF introduces sparsity to the linear system, making the problem computationally feasible. The method is demonstrated over Fennoscandia with measurements from global navigation satellite system (GNSS) and low Earth orbit (LEO) satellite receiver networks, GNSS occultation receivers, LEO satellite Langmuir probes, and ionosonde and incoherent scatter radar measurements.

The Kilpisjärvi Atmospheric Imaging Receiver Array (KAIRA) is a dual array of omnidirectional VHF radio antennas located near Kilpisjärvi, Finland. It is operated by the Sodankylä Geophysical Observatory. It makes extensive use of the proven LOFAR antenna and digital signal-processing hardware, and can act as a stand-alone passive receiver, as a receiver for the European Incoherent Scatter (EISCAT) very high frequency (VHF) incoherent scatter radar in Tromsø, or for use in conjunction with other Fenno-Scandinavian VHF experiments. In addition to being a powerful observing instrument in its own right, KAIRA will act as a pathfinder for technologies to be used in the planned EISCAT_3-D phased-array incoherent scatter radar system and participate in very long baseline interferometry experiments. This paper gives an overview of KAIRA, its principal hardware and software components, and its main science objectives. We demonstrate the applicability of the radio astronomy technology to our geoscience application. Furthermore, we present a selection of results from the commissioning phase of this new radio observatory.

Matched filtering of quadriphase coded radar signals creates unwanted sidelobes, which may mask important information. This correspondence presents a method of eliminating these sidelobes in aperiodic quadriphase codes. This is done by using a mismatched filter. The signal-to-noise ratio (SNR) at the output of the mismatched filter is less than the SNR at the output of the corresponding matched filter. A thorough computer search has been carried out to find quadriphase code-mismatched filter pairs with minimum possible SNR losses by considering a point target in the presence of white Gaussian noise. The phase patterns of the optimal codes, which were chosen from a total number of 1.466 times 1012investigated codes, are shown. It turned out that the mismatched filter of a quadriphase Barker code with 15 elements (1, 1, 1,j,j, 1, -j, -j,j, -1, -j,j, 1, -1, 1) has a loss in SNR of only 6.7% when compared with the corresponding matched filter. The mismatched filter of the well known 13-element Barker code, which has a loss in SNR of 4.8%, outperforms this filter. Finally, using numerical experiment it is shown that a randomly selected long code will most likely have very large SNR losses.