The Impact of Interference on GNSS Receiver Observables – A Running Digital Sum Based Simple Jammer Detector

A GNSS-based navigation system relies on externally received information via a space-based Radio Frequency (RF) link. This poses susceptibility to RF Interference (RFI) and may initiate failure states ranging from degraded navigation accuracy to a complete signal loss condition. To guarantee the integrity of the received GNSS signal, the receiver should either be able to function in the presence of RFI without generating misleading information (i.e., offering a navigation solution within an accuracy limit), or the receiver must detect RFI so that some other means could be used as a countermeasure in order to ensure robust and accurate navigation. Therefore, it is of utmost importance to identify an interference occurrence and not to confuse it with other signal conditions, for example, indoor or deep urban canyon, both of which have somewhat similar impact on the navigation performance. Hence, in this paper, the objective is to investigate the effect of interference on different GNSS receiver observables in two different environments: i. an interference scenario with an inexpensive car jammer, and ii. an outdoor-indoor scenario without any intentional interference. The investigated observables include the Automatic Gain Control (AGC) measurements, the digitized IF (Intermediate Frequency) signal levels, the Delay Locked Loop and the Phase Locked Loop discriminator variances, and the Carrier-to-noise density ratio (C/N0) measurements. The behavioral pattern of these receiver observables is perceived in these two different scenarios in order to comprehend which of those observables would be able to separate an interference situation from an indoor scenario, since in both the cases, the resulting positioning accuracy and/or availability are affected somewhat similarly. A new Running Digital Sum (RDS) -based interference detection method is also proposed herein that can be used as an alternate to AGC-based interference detection. It is shown in this paper that it is not at all wise to consider certain receiver observables for interference detection (i.e., C/N0); rather it is beneficial to utilize certain specific observables, such as the RDS of raw digitized signal levels or the AGC-based observables that can uniquely identify a critical malicious interference occurrence

PhosFox: a bioinformatics tool for peptide-level processing of LC-MS/MS-based phosphoproteomic data

Background: It is possible to identify thousands of phosphopeptides and -proteins in a single experiment with mass spectrometry-based phosphoproteomics. However, a current bottleneck is the downstream data analysis which is often laborious and requires a number of manual steps.Results: Toward automating the analysis steps, we have developed and implemented a software, PhosFox, which enables peptide-level processing of phosphoproteomic data generated by multiple protein identification search algorithms, including Mascot, Sequest, and Paragon, as well as cross-comparison of their identification results. The software supports both qualitative and quantitative phosphoproteomics studies, as well as multiple between-group comparisons. Importantly, PhosFox detects uniquely phosphorylated peptides and proteins in one sample compared to another. It also distinguishes differences in phosphorylation sites between phosphorylated proteins in different samples. Using two case study examples, a qualitative phosphoproteome dataset from human keratinocytes and a quantitative phosphoproteome dataset from rat kidney inner medulla, we demonstrate here how PhosFox facilitates an efficient and in-depth phosphoproteome data analysis. PhosFox was implemented in the Perl programming language and it can be run on most common operating systems. Due to its flexible interface and open source distribution, the users can easily incorporate the program into their MS data analysis workflows and extend the program with new features. PhosFox source code, implementation and user instructions are freely available from https://bitbucket.org/phintsan/phosfox.Conclusions: PhosFox facilitates efficient and more in-depth comparisons between phosphoproteins in case-control settings. The open source implementation is easily extendable to accommodate additional features for widespread application use cases

Quantifying hail size distributions from the sky - Application of drone aerial photogrammetry

A new technique, named "HailPixel", is introduced for measuring the maximum dimension and intermediate dimension of hailstones from aerial imagery. The photogrammetry procedure applies a convolutional neural network for robust detection of hailstones against complex backgrounds and an edge detection method for measuring the shape of identified hailstones. This semi-automated technique is capable of measuring many thousands of hailstones within a single survey, which is several orders of magnitude larger (e.g. 10 000 or more hailstones) than population sizes from existing sensors (e.g. a hail pad). Comparison with a co-located hail pad for an Argentinian hailstorm event during the RELAMPAGO project demonstrates the larger population size of the HailPixel survey significantly improves the shape and tails of the observed hail size distribution. When hail fall is sparse, such as during large and giant hail events, the large survey area of this technique is especially advantageous for resolving the hail size distribution.Fil: Soderholm, Joshua S.. Universitat Bonn; AlemaniaFil: Kumjian, Matthew R.. State University of Pennsylvania; Estados UnidosFil: McCarthy, Nicholas. University of Queensland; AustraliaFil: Maldonado, Paula Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Wang, Minzheng. Northraine Pty. Ltd.; Australi

A Radar-Based Hail Climatology of Australia

In Australia, hailstorms present considerable public safety and economic risks, where they are considered the most damaging natural hazard in terms of annual insured losses. Despite these impacts, the current climatological distribution of hailfall across the continent is still comparatively poorly understood. This study aims to supplement previous national hail climatologies, such as those based on environmental proxies or satellite radiometer data, with more direct radar-based hail observations. The heterogeneous and incomplete nature of the Australian radar network complicates this task and prompts the introduction of some novel methodological elements. We introduce an empirical correction technique to account for hail reflectivity biases at C-band, derived by comparing overlapping C- and S-band observations. Furthermore, we demonstrate how object-based hail swath analysis may be used to produce resolution-invariant hail frequencies, and describe an interpolation method used to create a spatially continuous hail climatology. The Maximum Estimated Size of Hail (MESH) parameter is then applied to a mixture of over fifty operational radars in the Australian radar archive, resulting in the first nationwide, radar-based hail climatology. The spatiotemporal distribution of hailstorms is examined, including their physical characteristics, seasonal and diurnal frequency, and regional variations of such properties across the continent.Comment: Revision 1 of manuscript submitted to Monthly Weather Revie

Reconstructing annual inflows to the headwater catchments of the Murray River, Australia, using the Pacific Decadal Oscillation

The Pacific Decadal Oscillation (PDO) is a major forcing of inter-decadal to quasi-centennial variability of the hydroclimatology of the Pacific Basin. Its effects are most pronounced in the extra-tropical regions, while it modulates the El Nino Southern Oscillation (ENSO), the largest forcing of global inter-annual climate variability. PalaeoPDO indices are now available for at least the past 500 years. Here we show that the \u3e500 year PDO index of Shen et al. (2006) is highly correlated with inflows to the headwaters of Australia\u27s longest river system, the Murray-Darling. We then use the PDO to reconstruct annual inflows to the Murray River back to A.D. 1474. These show penta-decadal and quasi-centennial cycles of low inflows and a possible 500 year cycle of much greater inflow variability. Superimposed on this is the likely influence of recent anthropogenic global warming. We believe this may explain the exceptionally low inflows of the past decade, the lowest of the previous 529 years

The Effects of Spatial Interpolation on a Novel, Dual-Doppler 3D Wind Retrieval Technique

Three-dimensional wind retrievals from ground-based Doppler radars have played an important role in meteorological research and nowcasting over the past four decades. However, in recent years, the proliferation of open-source software and increased demands from applications such as convective parameterizations in numerical weather prediction models has led to a renewed interest in these analyses. In this study, we analyze how a major, yet often-overlooked, error source effects the quality of retrieved 3D wind fields. Namely, we investigate the effects of spatial interpolation, and show how the common practice of pre-gridding radial velocity data can degrade the accuracy of the results. Alternatively, we show that assimilating radar data directly at their observation locations improves the retrieval of important dynamic features such as the rear flank downdraft and mesocyclone within a simulated supercell, while also reducing errors in vertical vorticity, horizontal divergence, and all three velocity components.Comment: Revised version submitted to JTECH. Includes new section with a real data cas