Satellite to Ground Station, Attenuation Prediction for 2.4-72GHz Using LTSM, An Artificial Recurrent Neural Network Technology

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.

Landscape transformations produce favorable roosting conditions for turkey vultures and black vultures

Recent increases in turkey vulture (Cathartes aura) and black vulture (Coragyps atratus) populations in North America have been attributed in part to their success adapting to human-modified landscapes. However, the capacity for such landscapes to generate favorable roosting conditions for these species has not been thoroughly investigated. We assessed the role of anthropogenic and natural landscape elements on roosting habitat selection of 11 black and 7 turkey vultures in coastal South Carolina, USA using a GPS satellite transmitter dataset derived from previous research. Our dataset spanned 2006–2012 and contained data from 7916 nights of roosting. Landscape fragmentation, as measured by land cover richness, influenced roosting probability for both species in all seasons, showing either a positive relationship or peaking at intermediate values. Roosting probability of turkey vultures was maximized at intermediate road densities in three of four seasons, and black vultures showed a positive relationship with roads in fall, but no relationship throughout the rest of the year. Roosting probability of both species declined with increasing high density urban cover throughout most of the year. We suggest that landscape transformations lead to favorable roosting conditions for turkey vultures and black vultures, which has likely contributed to their recent proliferations across much of the Western Hemisphere.

GPS z-PCO and GNSS-based scale determined by integrated processing with LEOs and Galileo

<p>The Global Positioning System (GPS) satellite transmitter antenna phase center offsets (PCOs) in z-direction and the scale of the terrestrial reference frame are highly correlated when neither of them is constrained to an a priori value in a least-squares adjustment. The commonly used PCO values offered by the International GNSS Service (IGS) are estimated in a global adjustment by constraining the ground station coordinates to the current International Terrestrial Reference Frame (ITRF). As the scale of the ITRF is determined by other techniques, the estimated GPS z-PCOs are not independent. Consequently, the z-PCOs transfer the scale to any subsequent GNSS solution. To get a GNSS-based scale that can contribute to a future ITRF realization, two methods are proposed to determine scale-independent GPS z-PCOs. One method is based on the gravitational constraint on Low Earth Orbiters (LEOs) in an integrated processing of the GPS satellites and LEOs. The correlation coefficient between the GPS PCO-z and the scale is reduced from 0.85 to 0.3 by supplementing a 54-ground-station network with seven LEOs. The impact of individual LEOs on the estimation is discussed by including different subsets of the LEOs. The accuracy of the z-PCOs of the LEOs is very important for the accuracy of the solution. In another method, the GPS z-PCOs and the scale are determined in a GPS+Galileo processing where the PCOs of Galileo are fixed to the values calibrated on ground from the released metadata. The correlation between the GPS PCO-z and the scale is reduced to 0.13 by including the current constellation of Galileo with 24 satellites. We use the whole constellation of Galileo and the three LEOs of the Swarm mission to perform a direct comparison and cross-check of the two methods. The two methods provide mean GPS z-PCO corrections of -186±25 mm and -221±37 mm with respect to the IGS values, and +1.55±0.22 ppb (part per billion) and +1.72±0.31 ppb in the terrestrial scale with respect to the IGS14 reference frame. The results of both methods agree with each other with only small differences. Due to the larger number of Galileo observations, the Galileo-PCO-fixed method leads to more precise and stable results. In the joint processing of GPS+Galileo+Swarm in which both methods are applied, the constraint on Galileo dominates the results. We also discuss how fixing either the Galileo transmitter antenna z-PCO or the Swarm receiver antenna z-PCOs in the GPS+Galileo+Swarm processing propagates to the respective freely estimated z-PCOs of Swarm or Galileo.</p>

First description of movement and ranging behavior of the Griffon vulture (Gyps fulvus) from Serbia using GPS satellite tracking

Understanding the movement pattern and ranging behavior of the Griffon vulture population in Serbia is of great importance for prioritizing conservation action. In 2011, an immature vulture was the first bird to be equipped with a satellite transmitter in Serbia. Our study aims to define the vulture?s foraging areas, home ranges, core and basic areas, and to investigate movement patterns across different years and seasons by analyzing satellite telemetry data. We tracked the movements of the vulture for over three years and obtained satellite tracking data for 34 bird-months (1976 GPS fixes) between October 2011 and July 2014. We determined that the overall foraging area of the vulture across the entire study period was 11654.34 km2. The overall area used by the vulture was larger during spring and summer than during winter periods. Combined ranges across all years identified one basic area and its associated core area around the Uvac colony and nearby feeding site; we identified three core areas in its proximity. This study showed that areas of traditional stock-raising practices are important vulture foraging areas and that supplementary feeding sites have a vital role. Our maps can be used for future planning of vulture conservation measures.

Influence of dense wavelength division multiplexing (DWDM) technique on the low earth orbit intersatellite systems performance

This work discusses the effect of wavelength division multiplexing on performance of intersatellite link. Intersatellite optical wireless communication (IsOWC) system is simulated by using OptiSystem software. Number of multiplexing channels involve on system performance. Bit rate is an operating parameter that determines the quality of the signal. Also, wavelength and distance between satellite transmitter and satellite receiver determine the system performance. In this article, the max Q factor, received power, and optical signal/noise ratio are the major leading performance parameters.

Two methods to determine scale-independent GPS PCOs and GNSS-based terrestrial scale: comparison and cross-check

The GPS satellite transmitter antenna phase center offsets (PCOs) can be estimated in a global adjustment by constraining the ground station coordinates to the current International Terrestrial Reference Frame (ITRF). Therefore, the derived PCO values rest on the terrestrial scale parameter of the frame. Consequently, the PCO values transfer this scale to any subsequent GNSS solution. A method to derive scale-independent PCOs without introducing the terrestrial scale of the frame is the prerequisite to derive an independent GNSS scale factor that can contribute to the datum definition of the next ITRF realization. By fixing the Galileo satellite transmitter antenna PCOs to the ground calibrated values from the released metadata, the GPS satellite PCOs in the z-direction (z-PCO) and a GNSS-based terrestrial scale parameter can be determined in GPS + Galileo processing. An alternative method is based on the gravitational constraint on low earth orbiters (LEOs) in the integrated processing of GPS and LEOs. We determine the GPS z-PCO and the GNSS-based scale using both methods by including the current constellation of Galileo and the three LEOs of the Swarm mission. For the first time, direct comparison and cross-check of the two methods are performed. They provide mean GPS z-PCO corrections of $$- 186 \pm 25$$ - 186 ± 25 mm and $$- 221 \pm 37$$ - 221 ± 37 mm with respect to the IGS values and $$+ 1.55 \pm 0.22$$ + 1.55 ± 0.22 ppb (parts per billion) and $$+ 1.72 \pm 0.31$$ + 1.72 ± 0.31 in the terrestrial scale with respect to the IGS14 reference frame. The results of both methods agree with each other with only small differences. Due to the larger number of Galileo observations, the Galileo-PCO-fixed method leads to more precise and stable results. In the joint processing of GPS + Galileo + Swarm in which both methods are applied, the constraint on Galileo dominates the results. We discuss and analyze how fixing either the Galileo transmitter antenna z-PCO or the Swarm receiver antenna z-PCO in the combined GPS + Galileo + Swarm processing propagates to the respective freely estimated z-PCO of Swarm and Galileo.

Lesson to Learn from an Endangered Green Turtle (Chelonia mydas): Marine Debris Ingestion, Rehabilitation and Satellite Tracking

Background: Marine debris is an environmental pollution problem affecting the oceans worldwide. Recent studies reveal that marine debris ingestion by sea turtles is rising. Sea turtles brought in for rehabilitation allows an opportunity to provide insights into the possible effects of anthropogenic debris on animal’s survivorship during rehabilitation. Methods: A green turtle (Chelonia mydas) was bycaught in fishing gear in south-western Taiwan in 2016. Debris were collected in the holding tank during rehabilitation. After a 3-month rehabilitation, the turtle was fit for release. Prior to the release, the turtle was tagged with a satellite transmitter. Result: Marine debris were found in turtle feces or floating on the surface of basins during rehabilitation. The debris were dominated by fishing line, hard plastic, soft plastic, rope, wood and styrofoam. The turtle survived and was successfully released back into the wild attached with a satellite transmitter. The turtle remained residing in waters of southern Taiwan, possibly its foraging ground, for almost two months. This study presents an apparent successful rehabilitation of an endangered green sea turtle, that hopefully helps further enhance environmental education and public awareness, as well as concerted actions against marine pollution in general and anthropogenic debris related problems in particular.