Preliminary Analysis and Evaluation of BDS-3 RDSS Timing Performance

Radio determination satellite service (RDSS) is one of the characteristic services of Beidou navigation satellite system (BDS), and also distinguishes with other GNSS systems. BDS-3 RDSS adopts new signals, which is compatible with BDS-2 RDSS signals in order to guarantee the services of old users. Moreover, the new signals also separate civil signals and military signals which are modulated on different carriers to improve their isolation and RDSS service performance. Timing is an important part of RDSS service, which has been widely used in the field of the power, transportation, marine and others. Therefore, the timing accuracy, availability and continuity is an important guarantee for RDSS service. This paper summarizes the principle of one-way and two-way timing, and provides the evaluation method of RDSS timing accuracy, availability and continuity. Based on BDS-3 RDSS signal measurements of system, the performance of one-way timing and two-way timing is analyzed and evaluated for the first time. The results show that: (1) the accuracy of one-way timing and two-way timing is better than 30 ns and 8 ns respectively, which are better than the official claimed accuracy; (2) the RMS of one-way timing accuracy is 5.45 ns, which is 20% smaller than BDS-2, and the availability and continuity are 100%; (3) the RMS of two-way timing accuracy is 3.59 ns, which is 34% smaller than one-way timing, and both of the availability and continuity are 100%; (4) the orbit maneuver of GEO satellite make the one-way timing has 7.68 h recovery, but has no affection on the two-way timing.

Does health service funding go where the need is? A prototype spatial access analysis for new urban contracts data

Background Much of spatial access research measures the proximity to health service locations. We advance this research by focusing on whether health service funding is within walkable reach of neighborhoods with high hardship. This is made possible by a new administrative data source: financial contracts data for those human services that are delivered by nonprofits under contract with the government. Methods In a prototypical spatial access study we apply a classic 2-step floating area catchment model for walkable network access to analyze 2018 data about contracted nonprofit health services funded by the Chicago Department of Public Health (CDPH). CDPH collected the data for the purpose of this study. Results We find that the common container approach of aggregating contract amounts by provider headquarter locations in a given area (ignoring satellite service sites) underestimates the share of funding that goes to Chicago neighborhoods with higher hardship. Once service sites and spatial access are taken into account, a larger share of CDPH funds was found to be within walkable reach of Chicago’s high hardship areas. This was followed by low hardship areas (which could be driven by more headquarter locations there that do serve areas throughout the city). Medium hardship areas trail both, perhaps warranting closer attention. We explore these results by program type and neighborhood with a spatial decision support system developed for the health department. Conclusions The typical approach for analyzing human service contracts based on headquarters is misleading -- in fact, we find that results are reversed when service sites and walkable access are taken into account. This prototype provides an alternative framework for avoiding these misleading results.

Flexible ku/k band frequency reconfigurable bandpass filter

<abstract> <p>The proposed reconfigurable BPF satisfies the International Telecommunication Unionos (ITU) region 3 spectrum requirement. In transmit mode, the frequency range 11.41-12.92 GHz is used by the direct broadcast service (DBS) and the fixed satellite service (FSS). Direct broadcast service (DBS) in reception mode employs 11.7-12.2 GHz and 17.3-17.8 GHz frequency ranges. Frequency reconfigurable filters are popular because they can cover wide range of frequencies, reducing system cost and space. Another emerging trend is electronic component flexibility or conformability, which allows them to be mounted on non-planar objects and are used in wearable applications. This project contains a frequency-reconfigurable BPF that has been entirely printed on a flexible polimide substrate. Frequency reconfigurability is obtained by using a pin diode HSCH 5318 and it is used to switch between 12 GHz and 18 GHz. The prototype reconfigurable BPF is highly compact and low-cost due to the flexible polimide substrate and the measured results are promising and match the simulated results well.</p> </abstract>

Does Health Service Funding Go Where the Need Is? A Prototype Spatial Access Analysis for New Urban Contracts Data

Background | Much of spatial access research measures the proximity to health service locations. We advance this research by focusing on whether health service funding is within walkable reach of neighborhoods with high hardship. This is made possible by a new administrative data source: financial contracts data for those human services that are delivered by nonprofits under contract with the government.Methods | In a prototypical spatial access study we apply a classic 2-step floating area catchment model for walkable network access to analyze 2018 data about contracted nonprofit health services funded by the Chicago Department of Public Health (CDPH). CDPH collected the data for the purpose of this study.Results | We find that the common container approach of aggregating contract amounts by provider headquarter locations in a given area (ignoring satellite service sites) underestimates the share of funding that goes to Chicago neighborhoods with higher hardship. Once service sites and spatial access are taken into account, a larger share of CDPH funds was found to be within walkable reach of Chicago’s high hardship areas. This was followed by low hardship areas (which could be driven by more headquarter locations there that do serve areas throughout thecity). Medium hardship areas trail both, perhaps warranting closer attention. We explore these results by program type and neighborhood with a spatial decision support system developed for the health department.Conclusions | The typical approach for analyzing human service contracts based on headquarters is misleading -- in fact, we find that results are reversed when service sites and walkable access are taken into account. This prototype provides an alternative framework for avoiding these misleading results.

Does Health Service Funding Go Where the Need Is? A Prototype Spatial Access Analysis for New Urban Contracts Data

Background Much of spatial access research measures the proximity to health service locations. We advance this research by focusing on whether health service funding is within walkable reach of neighborhoods with high hardship. This is made possible by a new administrative data source: financial contracts data for those human services that are delivered by nonprofits under contract with the government. Methods In a prototypical spatial access study we apply a classic 2-step floating area catchment model for walkable network access to analyze 2018 data about contracted nonprofit health services funded by the Chicago Department of Public Health (CDPH). CDPH collected the data for the purpose of this study. Results We find that the common container approach of aggregating contract amounts by provider headquarter locations in a given area (ignoring satellite service sites) underestimates the share of funding that goes to Chicago neighborhoods with higher hardship. Once service sites and spatial access are taken into account, a larger share of CDPH funds was found to be within walkable reach of Chicago’s high hardship areas. This was followed by low hardship areas (which could be driven by more headquarter locations there that do serve areas throughout the city). Medium hardship areas trail both, perhaps warranting closer attention. We explore these results by program type and neighborhood with a spatial decision support system developed for the health department. Conclusions The typical approach for analyzing human service contracts based on headquarters is misleading -- in fact, we find that results are reversed when service sites and walkable access are taken into account. This prototype provides an alternative framework for avoiding these misleading results

THE USE OF NEAR-EARTH ORBITS BY SATELLITE SYSTEMS IN DIFFERENT FREQUENCY BANDS

Выполнен анализ интенсивности использования геостационарной орбиты (ГСО) и негеостационарных орбит (НГСО) современными системами спутниковой связи фиксированной спутниковой службы в Ки-, Ка- и Q/V-диапазонах частот. Исследование охватывает ГСО, а также два наиболее используемых сегмента НГСО с высотой апогея до 1500 км и выше 8000 км. Представлены также результаты исследований для высокоэллиптических орбит (ВЭО). Сделан вывод о дефиците орбитально-частотного ресурса на ГСО и НГСО для рассматриваемых диапазонов частот. The paper analyzes the intensity of the use of geostationary orbit (GSO) and non-geostationary orbits (non-GSO) by modern satellite communication systems of the fixed-satellite service in the Ku-, Ka- and Q/V-bands. The analysis is made for geostationary orbit and two most used segments of non-GSO orbits with apogee altitudes up to 1500 km and above 8000 km. Results for highly inclined elliptical orbits (HEO) are also presented. The analysis results show a shortage of orbital and frequency resources in GSOs and non-GSOs for the considered frequency bands.

Strategy for on-orbit space object classification using deep learning

Since nanosatellites are spotlighted as a verification platform for space technology, new studies on on-orbit satellite servicing using nanosatellites are being conducted. This servicing is based on space robotics using vision-based sensors in the rendezvous state with a target satellite. The space environment, such as sunlight and Earth albedo, affects the mission. Simulation of the space environment on the ground is difficult, but the development of robust algorithms which reflect the effect is essential. In particular, missions such as active debris removal require a method for overcoming changes in any known information due to external factors such as collisions. This study proposes a new strategy on nanosatellite for on-orbit space object classification by applying deep learning to sensor-based orbit satellite service activity. When previously known information is changed, a method of online learning on orbit after obtaining additional data at a short relative distance can help determine the final service part. Using the images and point cloud data that simulate the space environment, we apply a convolutional neural network and PointNet to classify the objects. The learning environment is studied using a general desktop and a micro-graphics processing unit (GPU) board that can be mounted on a nanosatellite. For the training, we used self-produced data using 3D models of nanosatellites and asteroids with similar shapes, which are difficult to distinguish with existing algorithms. Consequently, the proposed strategy by the author shows feasibility of using nanosatellite’s micro GPU for on-orbit space object classification, and it is verified that point cloud–based methods are more suitable by utilizing deep learning for nanosatellites. The proposed method with processor of nanosatellite is applicable to satellite service missions in orbit, such as capturing of robotic parts for extending life span or removing space debris.