Online: 16 June 2021 (08:50:03 CEST)
The application of signal-to-noise ratio (SNR) observations from ground-based GNSS Reflectometry is becoming an operational tool for coastal sea-level altimetry. As in all data analyses, systematic influences must be reduced here too, to achieve reliable results. A prominent influence results from atmospheric refraction. Different approaches exist to describe or to correct for this influence. In our contribution we will revise the latest developments and suggest a simple atmospheric interferometric delay model that takes into account ray bending as well as along-path propagation delay. The model takes into account a spherical reflector and can therefore be applied for data from very low elevation angles, too. The findings are double-checked by numerical experiments based on a step-by-step raytracing procedure.
ARTICLE | doi:10.20944/preprints201904.0081.v1
Online: 8 April 2019 (10:41:17 CEST)
The signal-to-noise ratio (SNR) data is part of the global navigation satellite systems (GNSS) observables. In a marine environment, the oscillation of the SNR data can be used to derive reflector heights. Since the attenuation of the SNR oscillation is related to the roughness of the sea surface, the significant wave height (SWH) of the water surface can be calculated from the analysis of the attenuation. The attenuation depends additionally on the relation between the coherent and the incoherent part of the scattered power. The latter is a function of the correlation length of the surface waves. Because the correlation length changes with respect to the direction of the line of sight relative to the wave direction, the attenuation must show an anisotropic characteristic. In this work, we present a method to derive the wave direction from the anisotropy of the attenuation of the SNR data. The method is investigated based on simulated data as well by the analysis of experimental data from a GNSS station in the North Sea.
DATA DESCRIPTOR | doi:10.20944/preprints201810.0179.v1
Subject: Engineering, Electrical & Electronic Engineering Keywords: imaging; CMOS; camera; SNR; noise; performance
Online: 9 October 2018 (09:38:23 CEST)
Expensive cameras meant for research applications are usually characterized by the manufacturers and detailed specifications  are available for them. Suppliers of inexpensive cameras usually do not provide such detailed information about their cameras. This data set provides the acquisition speed and noise characteristics acquired from a monochrome 1.2 megapixel CMOS camera, the QHY5L-II M . The source code provided along with this data set  can also be used to acquire similar data for other QHY cameras. This enables the use of such cost-effective cameras for other scientific applications in other fields, beyond the designed use in Astronomy.
ARTICLE | doi:10.20944/preprints201802.0096.v2
Subject: Keywords: IoT; security; encryption; quantized speech image; SNR; PESQ; histogram; entropy; correlation
Online: 15 February 2018 (19:57:48 CET)
The IoT Internet of Things being a promising technology of the future. It is expected to connect billions of devices. The increased communication number is expected to generate data mountain and the data security can be a threat. The devices in the architecture are fundamentally smaller in size and low powered. In general, classical encryption algorithms are computationally expensive and this due to their complexity and needs numerous rounds for encrypting, basically wasting the constrained energy of the gadgets. Less complex algorithm, though, may compromise the desired integrity. In this paper we apply a lightweight encryption algorithm named as Secure IoT (SIT) to a quantized speech image for Secure IoT. It is a 64-bit block cipher and requires 64-bit key to encrypt the data. This quantized speech image is constructed by first quantizing a speech signal and then splitting the quantized signal into frames. Then each of these frames is transposed for obtaining the different columns of this quantized speech image. Simulations result shows the algorithm provides substantial security in just five encryption rounds.
ARTICLE | doi:10.20944/preprints202112.0031.v1
Subject: Mathematics & Computer Science, Information Technology & Data Management Keywords: Satellite Communication; Signal Propagation; Rain Attenuation; Urban area ground station; SNR, ITU-R; LSTM, Neural network
Online: 2 December 2021 (11:18:57 CET)
Free-space communication is a leading component in global communications. Its advantages relate to a broader signal spread, no wiring, and ease of engagement. Satellite communication services became recently attractive to mega-companies that foresee an excellent opportunity to connect disconnected remote regions, serve emerging machine-to-machine communication, Internet-of-things connectivity, and more. Satellite communication links suffer from arbitrary weather phenomena such as clouds, rain, snow, fog, and dust. In addition, when signals approach the ground station, it has to overcome buildings blocking the direct access to the ground station. Therefore, satellites commonly use redundant signal strength to ensure constant and continuous signal transmission, resulting in excess energy consumption, challenging the limited power capacity generated by solar energy or the fixed amount of fuel. This research proposes LTSM, an artificial recurrent neural network technology that provides a time-dependent prediction of the expected attenuation level due to rain and fog and the signal strength that remained after crossing physical obstacles surrounding the ground station. The satellite transmitter is calibrated accordingly. The satellite outgoing signal strength is based on the predicted signal strength to ensure it will remain strong enough for the ground station to process it. The instant calibration eliminates the excess use of energy resulting in energy savings.
REVIEW | doi:10.20944/preprints201903.0164.v1
Subject: Engineering, Electrical & Electronic Engineering Keywords: smart garments; e-textiles; biosignals; sensors; dry electrode; signal-to-noise ratio (SNR); internet-of-things (IoT); knitted fabrics
Online: 15 March 2019 (11:59:47 CET)
This paper presents an overview of the smart electro-clothing systems (SeCSs) targeted at health monitoring, sports benefits, fitness tracking, and social activities. Technical features of the available SeCSs, covering both textile and electronic components, are thoroughly discussed and their applications in the industry and research purposes have been highlighted. In addition, it also presents the developments in the associated areas of wearable sensor systems and textile-based dry sensors. As it became evident during the literature research, such a review on SeCSs covering all relevant issues has not been presented before. This paper will be particularly helpful for new generation researchers investigating the design, development, function and comforts of the sensor integrated clothing materials.
ARTICLE | doi:10.20944/preprints201608.0206.v2
Subject: Engineering, Electrical & Electronic Engineering Keywords: impulse radar; ultra-wideband (UWB); noncontact; short-range; healthcare; respiration; heartbeat; SNR; ensemble empirical mode decomposition (EEMD); continuous-wavelet transform (CWT)
Online: 15 September 2016 (11:24:00 CEST)
The radar sensor described realizes healthcare monitoring capable of detecting subject chest-wall movement caused by cardiopulmonary activities, and wirelessly estimating the respiration and heartbeat rates of the subject without attaching any devices to the body. No conventional Doppler only can capture Doppler signatures because of a lack of bandwidth information with noncontact sensors. In contrast, we take full advantages of impulse radio ultra-wideband (IR-UWB) radar to achieve low power consumption and convenient portability, with a flexible detection range and desirable accuracy. A noise reduction method based on improved ensemble empirical mode decomposition (EEMD) and a vital sign separation method based on continuous-wavelet transform (CWT) are proposed jointly to improve the signal-to-noise ratio (SNR) in order to acquire accurate respiration and heartbeat rates. This noncontact healthcare sensor system proves the commercial feasibility and considerable accessibility of using compact IR-UWB radar for emerging biomedical applications. Compared with traditional contact measurement devices, experimental results utilizing a 2.3 GHz bandwidth transceiver, demonstrate 100% similar results.