The back propagation (BP) method consists of diffractive integrals computed over a trajectory path, projecting a signal to different planes. It unwinds the diffraction and multipath, resulting in minimum disturbance on the BP amplitude when the auxiliary plane coincides with the region causing the diffraction. The method has been previously applied in GNSS Radio Occultation (RO) measurements showing promising results in the location estimate of ionospheric irregularities but without complementary data to validate the estimation. In this study, we investigate with wave optics propagator (WOP) simulations of an equatorial C/NOFS occultation with scintillation signatures caused by an equatorial plasma bubble (EPB), which was parametrized with aid of collocated data. In addition, a few more test cases were designed to assess the BP method regarding size, intensity and placement of single and multiple irregularity regions. The results show a location estimate accuracy of 10 km (single bubble, reference case), where in multiple bubble scenarios only the strongest disturbance would be resolved properly. The minimum detectable disturbance level and the estimation accuracy depend on the receiver noise level, and in the case of several bubbles on the distance between them. The remarks of the evaluation supported the interpretation of results for two COSMIC occultations.

Global Navigation Satellite System (GNSS) Radio Occultation (RO) has provided high- quality atmospheric data assimilated in Numerical Weather Prediction (NWP) models and climatol- ogy studies for more than 20 years. In the satellite–satellite GNSS-RO geometry, the measurements are susceptible to ionospheric scintillation depending on the solar and geomagnetic activity, seasons, geographical location and local time. This study investigates the application of the Support Vector Machine (SVM) algorithm in developing an automatic detection model of F-layer scintillation in GNSS-RO measurements using power spectral density (PSD). The model is intended for future analyses on the influence of space weather and solar activity on RO data products over long time periods. A novel data set of occultations is used to train the SVM algorithm. The data set is composed of events at low latitudes on 15–20 March 2015 (St. Patrick’s Day geomagnetic storm, high solar flux) and 14–19 May 2018 (quiet period, low solar flux). A few conditional criteria were first applied to a total of 5340 occultations to define a set of 858 scintillation candidates. Models were trained with scintillation indices and PSDs as training features and were either linear or Gaussian kernel. The investigations also show that besides the intensity PSD, the (excess) phase PSD has a positive contribution in increasing the detection of true positives. 

Global Navigation Satellite System Radio Occultation (GNSS-RO) is a technique used to sound the atmosphere and derive vertical profiles of refractivity. Signals from GNSS satellites are received in a low-Earth orbit, and they are then processed to produce bending angle profiles, from which meteorological parameters can be retrieved. Generating two-dimensional images in the form of spectrograms from GNSS-RO signals is commonly done to, for instance, investigate reflections or estimate signal quality in the lower troposphere. This is typically implemented using, e.g., the Short-Time Fourier Transform (STFT) to produce a time-frequency representation that is subsequently transformed to bending angle (BA) and impact height (IH) coordinates by non-linear mapping. In this paper, we propose an alternative method based on a straightforward extension of the Phase Matching (PM) operator to produce two-dimensional spectral images in the BA-IH domain by applying a sliding window. This Sliding Window Phase Matching (SWPM) method generates the spectral amplitude on an arbitrary grid in BA and IH, e.g., along the coordinate axes. To illustrate, we show both SWPM and STFT methods applied to operational MetOp-A data. For SWPM we use a constant window in the BA-dimension, whereas for STFT we use a conventional constant time window. We show that the SWPM method produces the same result as STFT when the same window length is used for both methods. The sample points in impact parameter and bending angle are those generated by and the main advantage is that SWPM offers the user a convenient way to freely sample the BA-IH space. The cost for this is processing time that is somewhat longer than implementations based on the Fast Fourier Transform, such as the STFT method.

Like any other system relying on trans-ionospheric propagation, GNSS Radio Occultation (GNSS-RO) is affected by ionospheric conditions during measurements. Regions of plasma irregularities in F-region create abrupt gradients in the distribution of ionized particles. Radio signals propagated through such regions suffer from constructive and destructive contributions in phase and amplitude, known as scintillations. Different approaches have been proposed in order to model and reproduce the wave propagation through ionospheric irregularities. We present simulations considering an one-component inverse power-law model of irregularities integrated with Multiple Phase Screen (MPS) propagation. In this work, the capability of the scintillation model to reproduce features in the signal amplitude of low latitude MetOp measurements in the early hours of DOY 76, 2015 (St. Patrick’s Day geomagnetic storm) is evaluated. Power spectral density (PSD) analysis, scintillation index, decorrelation time and standard deviation of neutral bending angle are considered in the comparison between the simulations and RO measurements. The results validate the capability of the simulator to replicate an equivalent total integrated phase variance in cases of moderate to strong scintillation.

It is well-known that in the presence of super-refractive layers in the lower-tropospheric inversion of GNSSradio occultation (RO) measurements using the Abel trans-form yields biased refractivity profiles. As such it is problem-atic to reconstruct the true refractivity from the RO signal.Additional information about this lower region of the atmo-sphere might be embedded in reflected parts of the signal. Toretrieve the bending angle, the phase matching operator canbe used. This operator produces a complex function of theimpact parameter, and from its phase we can calculate thebending angle. Instead of looking at the phase, in this paperwe focus on the function’s amplitude. The results in this pa-per show that the signatures of surface reflections in GNSSRO measurements can be significantly enhanced when usingthe phase matching method by processing only an appropri-ately selected segment of the received signal. This signatureenhancement is demonstrated by simulations and confirmedwith 10 hand-picked MetOp-A occultations with reflectedcomponents. To validate that these events show signs of re-flections, radio holographic images are generated. Our resultssuggest that the phase matching amplitude carries informa-tion that can improve the interpretation of radio occultationmeasurements in the lower troposphere.

Global Navigation Satellite System Radio Occultation (GNSS-RO) is an important technique used to sound the Earth's atmosphere and provide data products to numerical weather prediction (NWP) systems as well as toclimate research. It provides a high vertical resolution and SI-traceability that are both valuable complements toother Earth observation systems. In addition to direct components refracted in the atmosphere, many received RO signals contain reflected components thanks to the specular and relatively smooth characteristics of the ocean. These reflected components can interfere the retrieval of the direct part of the signal, and can also contain meteorological information of their own, e.g., information about the refractivity at the Earth's surface. While the conventional method to detect such reflections is by using radio-holographic methods, it has been shown that it is possible to see reflections using wave optics inversion, specically while inspecting the amplitude of the output of phase matching (PM). The primary objective of this paper is to analyze the appearance of these reflections in the amplitude output from another wave optics algorithm, namely the much faster full spectrum inversion (FSI). PM and FSI are closely related algorithms - they both use the method of stationary phase to derive the bending angle from a measured signal. We apply our own implementation of FSI to the same GNSS-RO measurements that PM was previously applied to and show that the amplitudes of the outputs again indicate reflection in the surface of the ocean. Our results show that the amplitudes output from the FSI and PM algorithms are practically identical and that the reflection signatures thus appear equally well.

High accuracy of impact height is important to get reliableRadio Occultation (RO) measurements of the atmosphere refractivity.We have made an investigation on how accuratelywe can measure the impact height at ground level using waveoptics simulations, realistic refractivity profiles, a realisticsimulator for an advanced RO instrument including noise,and using phase matching for the inversion. The idea of theinvestigation is to increase the measurement accuracy of impactheight at low altitudes and to give reliable measurementseven in cases of super-refractive layers. We present statisticson the accuracy and precision of the determination of theimpact height at ground, as well as the resulting accuracy andprecision in the measured refractivity.

GPUs in embedded platforms are reaching performance levels comparable to desktop hardware, thus it becomes interesting to apply Computer Vision techniques. We propose, implement, and evaluate a novel feature detector and descriptor combination, i.e., we combine the Harris-Hessian detector with the FREAK binary descriptor. The implementation is done in OpenCL, and we evaluate the execution time and classification performance. We compare our approach with two other methods, FAST/BRISK and ORB. Performance data is presented for the mobile device Xperia Z3 and the desktop Nvidia GTX 660. Our results indicate that the execution times on the Xperia Z3 are insufficient for real-time applications while desktop execution shows future potential. Classification performance of Harris-Hessian/FREAK indicates that the solution is sensitive to rotation, but superior in scale variant images.

Graphics processing units (GPUs) in embedded mobile platforms are reaching performance levels where they may be useful for computer vision applications. We compare two generations of embedded GPUs for mobile devices when run- ning a state-of-the-art feature detection algorithm, i.e., Harris- Hessian/FREAK. We compare architectural differences, execu- tion time, temperature, and frequency on Sony Xperia Z3 and Sony Xperia XZ mobile devices. Our results indicate that the performance soon is sufficient for real-time feature detection, the GPUs have no temperature problems, and support for large work-groups is important.