Calibration Challenges for Future Radio Telescopes

Instruments for radio astronomical observations have come a long way. While the first telescopes were based on very large dishes and 2-antenna interferometers, current instruments consist of dozens of steerable dishes, whereas future instruments will be even larger distributed sensor arrays with a hierarchy of phased array elements. For such arrays to provide meaningful output (images), accurate calibration is of critical importance. Calibration must solve for the unknown antenna gains and phases, as well as the unknown atmospheric and ionospheric disturbances. Future telescopes will have a large number of elements and a large field of view. In this case the parameters are strongly direction dependent, resulting in a large number of unknown parameters even if appropriately constrained physical or phenomenological descriptions are used. This makes calibration a daunting parameter estimation task, that is reviewed from a signal processing perspective in this article.Comment: 12 pages, 7 figures, 20 subfigures The title quoted in the meta-data is the title after release / final editing

New receivers for DS-SS in time variant multipath channels based on the PN alignment concept

We present new combined blind equalization and detection schemes for a DS-SS system. The new proposed algorithms improve the bit error rate compared to traditional RAKE receivers in time-variant channels with multipath. This improvement is obtained in both simulated and a real ionospheric HF link. Its very low computational complexity makes them suitable to be implemented in real receivers.Peer ReviewedPostprint (published version

Space-time sampling strategies for electronically steerable incoherent scatter radar

Incoherent scatter radar (ISR) systems allow researchers to peer into the ionosphere via remote sensing of intrinsic plasma parameters. ISR sensors have been used since the 1950s and until the past decade were mainly equipped with a single mechanically steerable antenna. As such, the ability to develop a two or three dimensional picture of the plasma parameters in the ionosphere has been constrained by the relatively slow mechanical steering of the antennas. A newer class of systems using electronically steerable array (ESA) antennas have broken the chains of this constraint, allowing researchers to create 3-D reconstructions of plasma parameters. There have been many studies associated with reconstructing 3-D fields of plasma parameters, but there has not been a systematic analysis into the sampling issues that arise. Also, there has not been a systematic study as to how to reconstruct these plasma parameters in an optimum sense as opposed to just using different forms of interpolation. The research presented here forms a framework that scientists and engineers can use to plan experiments with ESA ISR capabilities and to better analyze the resulting data. This framework attacks the problem of space-time sampling by ESA ISR systems from the point of view of signal processing, simulation and inverse theoretic image reconstruction. We first describe a physics based model of incoherent scatter from the ionospheric plasma, along with processing methods needed to create the plasma parameter measurements. Our approach leads to development of the space-time ambiguity function, forming a theoretical foundation of the forward model for ISR. This forward model is novel in that it takes into account the shape of the antenna beam and scanning method along with integration time to develop the proper statistics for a desired measurement precision. Once the forward model is developed, we present the simulation method behind the Simulator for ISR (SimISR). SimISR uses input plasma parameters over space and time and creates complex voltage samples in a form similar to that produced by a real ISR system. SimISR allows researchers to evaluate different experiment configurations in order to efficiently and accurately sample specific phenomena. We present example simulations using input conditions derived from a multi-fluid ionosphere model and reconstructions using standard interpolation techniques. Lastly, methods are presented to invert the space-time ambiguity function using techniques from image reconstruction literature. These methods are tested using SimISR to quantify accurate plasma parameter reconstruction over a simulated ionospheric region

Tomographic imaging of ionospheric plasma bubbles based on GNSS and radio occultation measurements

Total electron content measurements given by the global navigation satellite system (GNSS) have successfully presented results to capture the signatures of equatorial plasma bubbles. In contrast, the correct reproduction of plasma depletions at electron density level is still a relevant challenge for ionospheric tomographic imaging. In this regard, this work shows the first results of a new tomographic reconstruction technique based on GNSS and radio-occultation data to map the vertical and horizontal distributions of ionospheric plasma bubbles in one of the most challenging conditions of the equatorial region. Twenty-three days from 2013 and 2014 with clear evidence of plasma bubble structures propagating through the Brazilian region were analyzed and compared with simultaneous observations of all-sky images in the 630.0 nm emission line of the atomic oxygen. The mean rate of success of the tomographic method was 37.1%, being more efficient near the magnetic equator, where the dimensions of the structures are larger. Despite some shortcomings of the reconstruction technique, mainly associated with ionospheric scintillations and the weak geometry of the ground-based GNSS receivers, both vertical and horizontal distributions were mapped over more than 30° in latitude, and have been detected in instances where the meteorological conditions disrupted the possibility of analyzing the OI 630 nm emissions. Therefore, the results revealed the proposed tomographic reconstruction as an efficient tool for mapping characteristics of the plasma bubble structures, which may have a special interest in Space Weather, Spatial Geodesy, and Telecommunications.Peer ReviewedPostprint (published version

Ionosphere Model Development using Regression Method

For earth survival an ionosphere is most important and utmost noteworthy for vital satellite communiqué for the navigation positioning exactness persistence. It encompasses different number of layers subject to the quantity of electron density based on distance. So many ionospheric models of its kind are available to guess electron density with temporal determinations based on different research done within this era. GPS data are habitually castoff in these models. Because of that the essentiality is, a required of progressing ionospheric models to cope up with dissimilar time period for low latitudes of nation. Apart from this, an ionospheric tomography is not a well-posed problem. Ionospheric TEC bring into being concurrently in copious locations, which can be determined by a number of methods to overcome electron density. This paper is projected for the research of developing a method to estimate of total electron density which cover entire Indian region. Largely we can utilized satellite data and placed together by number of calculations. The organization of massive figures are intended the usage of data mining algorithms, and artificial neural network algorithms intended to guesstimate. A thorough study on ionospheric model development using regression method and further proposed idea based on literature can be seen in current research paper