Broadband Meter-Wavelength Observations of Ionospheric Scintillation

Intensity scintillations of cosmic radio sources are used to study astrophysical plasmas like the ionosphere, the solar wind, and the interstellar medium. Normally these observations are relatively narrow band. With Low Frequency Array (LOFAR) technology at the Kilpisj\"arvi Atmospheric Imaging Receiver Array (KAIRA) station in northern Finland we have observed scintillations over a 3 octave bandwidth. ``Parabolic arcs'', which were discovered in interstellar scintillations of pulsars, can provide precise estimates of the distance and velocity of the scattering plasma. Here we report the first observations of such arcs in the ionosphere and the first broad-band observations of arcs anywhere, raising hopes that study of the phenomenon may similarly improve the analysis of ionospheric scintillations. These observations were made of the strong natural radio source Cygnus-A and covered the entire 30-250\,MHz band of KAIRA. Well-defined parabolic arcs were seen early in the observations, before transit, and disappeared after transit although scintillations continued to be obvious during the entire observation. We show that this can be attributed to the structure of Cygnus-A. Initial results from modeling these scintillation arcs are consistent with simultaneous ionospheric soundings taken with other instruments, and indicate that scattering is most likely to be associated more with the topside ionosphere than the F-region peak altitude. Further modeling and possible extension to interferometric observations, using international LOFAR stations, are discussed.Comment: 11 pages, 17 figure

On point sources and near field measurements in inverse acoustic obstacle scattering

Abstract The dissertation considers an inverse acoustic obstacle scattering problem in which the incident field is generated by a point source and the measurements are made in the near field region. Three methods to solve the problem of reconstructing the support of an unknown sound-soft or sound-hard scatterer from the near field measurements are presented. Methods are modifications of Kirsch factorization and modified Kirsch factorization methods. Numerical examples are given to show the practicality of one of the methods

EISCAT_3D final report of work package 11

Deliverable D11.2 of Work Package 11: Software Theory and Implementation of the European Commission 7th Framework Programme project EISCAT_3D: A European three-dimensional imaging radar for atmospheric and geospace research (Preparatory Phase) Project number: 26196

Transmission code optimization method for incoherent scatter radar

When statistical inversion of a lag profile is used to determine an incoherent scatter target, the posterior variance of the estimated target can be used to determine how well a set of transmission codes perform. In this work we present an incoherent scatter radar transmission code optimization search method suitable for different modulation types, including binary phase, polyphase and amplitude modulation. We found that the combination of amplitude and phase modulation provides better performance than traditional binary phase coding, in some cases giving better accuracy than alternating codes

Optimal true time delay filter with application to FPGA firmware-based phased array radar signal processing

Abstract The European Incoherent Scatter‐3D phased array radar system will be largely based on field‐programmable gate array (FPGA) firmware electronics that carry out the signal processing by using different digital filters. In this paper we have presented a method of designing an optimal true time delay finite impulse response filter with applications to an FPGA firmware‐based multichannel signal processing system. The method provides an optimal true time delay finite impulse response filter with the desired responses at both band pass and stopband. This is possible by finding a mathematical minimization solution for the total power of all filter coefficients longer than a prespecified half‐length. The analysis is based on freely choosing the responses in the transition band until user‐specified desired responses are achieved. We have investigated the performance of these optimal digital filters in terms of the required digital signal processing (DSP) resources in GMACs (giga multiply accumulates per second) by considering both all‐in‐one stage filtering and cascaded solutions for ion and plasma line incoherent scatter radar measurements. We have shown that the cascaded solution provides more efficient utilization of DSP resources and hence represents the optimal choice for processing the proposed European Incoherent Scatter‐3D phased array radar signals. An example is demonstrated in which 906.88 GMACs are required to process 208 ion line beams with 2×4‐bit resolution in all‐in‐one stage processing, as compared to the 79.16 GMACs needed for a similar task in a cascaded solution

Lag profile inversion method for EISCAT data analysis

The present standard EISCAT incoherent scatter experiments are based on alternating codes that are decoded in power domain by simple summation and subtraction operations. The signal is first digitised and then different lagged products are calculated and decoded in real time. Only the decoded lagged products are saved for further analysis so that both the original data samples and the undecoded lagged products are lost. A fit of plasma parameters can be later performed using the recorded lagged products. In this paper we describe a different analysis method, which makes use of statistical inversion in removing range ambiguities from the lag profiles. An analysis program carrying out both the lag profile inversion and the fit of the plasma parameters has been constructed. Because recording the received signal itself instead of the lagged products allows very flexible data analysis, the program is constructed to use raw data, i.e. IQ-sampled signal recorded from an IF stage of the radar. The program is now capable of analysing standard alternating-coded EISCAT experiments as well as experiments with any other kind of radar modulation if raw data is available. The program calculates the ambiguous lag profiles and is capable of inverting them as such but, for analysis in real time, time integration is needed before inversion. We demonstrate the method using alternating code experiments in the EISCAT UHF radar and specific hardware connected to the second IF stage of the receiver. This method produces a data stream of complex samples, which are stored for later processing. The raw data is analysed with lag profile inversion and the results are compared to those given by the standard method

Gaussian Markov random field priors in ionospheric 3D multi-instrument tomography

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

Gaussian Markov random field priors in ionospheric 3-D multi-instrument tomography

Abstract 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