Accurate Reconstruction of the Radiation of Sparse Sources from a Small Set of Near-Field Measurements by Means of a Smooth-Weighted Norm for Cluster-Sparsity Problems

The aim of this contribution is to present an approach that allows to improve the quality of the reconstruction of the far-field from a small number of measured samples by means of sparse recovery using a relatively coarse grid for source positions (with sample spacing of the order of λ/8) compared to the grid usually required. In particular, the iterative method proposed employs a smooth-weighted constrained minimization, that guarantees a better probability of correct estimate of the sparse sources and an improved quality in the reconstruction, with a similar computational effort respect to the standard ℓ1 re-weighted minimization approach.

Muon Tracker with Unsegmented Plastic Scintillator Panels

A muon tracker was developed using three polyvinyl toluene scintillator panels instrumented with photomultiplier tubes (PMTs) mounted at the corners. Panels are mounted in parallel on an aluminum frame which allows for simple adjustment of angle, orientation and separation distance between the panels. The responses of all PMTs in the system are digitized simultaneously at sub-nanosecond sample spacing. Software was developed to adjust settings and implement event rejection based on the number of panels that detected a scintillation event within a 400-nanosecond record. The relative responses of the PMTs are used to calculate the position of scintillation events within each panel. The direction of the muons through the system can be tracked using the panel strike order. Methods for triangulation by both time-of-flight (TOF) and PMT magnitude response are reported. The time triangulation method is derived and experimentally demonstrated using parallel cables of differing length. The PMTs used in this experiment are only optimized for amplitude discrimination, not for time spread jitter as would be required to implement TOF methods into the scintillator panels. A Gaussian process regression machine learning tool was implemented to learn the relationship between PMT response features and positions from a calibration dataset. Resolution is analyzed using different numbers of PMTs and low-versus-high PMT sensitivities. Muons traveling in forward and reverse directions through the detector system were counted in all six axis orientations. The muon detector was deployed for 28 days in an underground tunnel and vertical muon counts were recorded.

Reconstruction of the Far-Field Pattern of Volumetric AUTs from a Reduced Set of Near-Field Samples Collected along a Planar Spiral with a Uniform Step

An efficient near-to-far-field transformation (NTFFT) technique, wherein the near-field (NF) measurements are acquired along a planar spiral with a uniform step to make the control of the involved positioners easier, is developed in this article. Such a technique is tailored for quasi-spherical, i.e., volumetric, antennas under test and makes use of a reduced number of NF data. An effective two-dimensional sampling interpolation algorithm, allowing the accurate reconstruction of the input NF data for the standard NTFFT with plane-rectangular scan, is obtained by setting the spiral step equal to the sample spacing required for interpolating along a radial line according to the spatial bandlimitation properties of electromagnetic fields, and by properly developing a non-redundant representation along such a spiral. Tests results are reported to demonstrate that the proposed NTFFT technique retains the same accuracy as the standard plane-rectangular one.

Behavior of Soil Chemical Attributes in Field-Forest Succession in Southern Amazonas

The use of geostatistical methods in the identification of the size and structure of the spatial variability of soil chemical attributes has been a very important tool in the evaluation and behavior of soil attributes. This research aimed to evaluate the spatial variability of chemical attributes in natural field and forest areas, in the Humaitá region (AM). In these areas, meshes with dimensions of 70 m x 70 m were established at regular intervals of 10 minutes in the 0.0-0.2 m layers, totaling 64 samples per layer. It was determined: soil pH, phosphorus (P), potassium (K+), calcium (Ca2+), magnesium (Mg2+), aluminum (Al3+) and potential acidity (H++Al3+). Base saturation (V%) and sum of bases (SB) were calculated. The data were evaluated by descriptive statistics and spatial dependence analysis, based on the best models and semivariograms adjustment. The chemical attributes are spatially dependent, they present random distribution of ideal sample spacing, considering that the variables that showed dependence were adjusted to the exponential and spherical model. Geostatistic was presented as an appropriate tool, providing information that allows the understanding of the spatial distribution. The degree of dependence was strong and moderate. The highest reaches were recorded in the natural field area.

ESTIMATION OF SAMPLE SPACING IN STOCHASTIC PROCESSES

Motivated by applications in electron microscopy, we study the situation where a stationary and isotropic random field is observed on two parallel planes with unknown distance. We propose an estimator for this distance. Under the tractable, yet flexible class of Lévy-based random field models, we derive an approximate variance of the estimator. The estimator and the approximate variance perform well in two simulation studies.