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The global community, with coordination from the United Nations, is energized to pursue the Sustainable Development Goals (SDGs), a list of 17 important aspirations that summarize the key challenges of our era. The SDGs apply to every nation and represent an international effort to eliminate extreme poverty, ensure access to safe drinking water, strengthen food security, and produce clean and reliable energy, among other pursuits. Space technology is already being used around the world to advance progress toward the SDGs and monitor their related Indicators. This paper explores how six technologies related to space—satellite Earth observation, satellite communication, satellite navigation and positioning, human spaceflight and microgravity research, space technology transfer, and basic scientific research—are being used to realize the vision that the SDGs represent. The paper also discusses the obstacles that limit the application of these technologies for the SDGs and provides an overview of potential paths to overcome these barriers. The paper finally studies the historical and potential roles that four distinct types of entities involved in global sustainable development—governments, non- and inter-governmental organizations, entrepreneurial companies, and universities— have played or may play in the application of space technologies towards the SDGs. • Six space technology areas are shown to support the U.N. Sustainable Development Goals. • Examples of space projects that support the SDGs are found in many sectors. • New designs for technology are needed to improve effectiveness of space applications for the SDGS. [ABSTRACT FROM AUTHOR]

Global navigation satellite system (GNSS) provides users with all-weather, continuous, high-precision positioning, navigation, and timing (PNT) services. In the operation and use of GNSS, the influence of the space environment is a factor that must be considered. For example, during geomagnetic storms, a series of changes in the Earth's magnetosphere, ionosphere, and upper atmosphere affect GNSS's positioning performance. To investigate the positioning performance of global satellite navigation systems during geomagnetic storms, this study selected three geomagnetic storm events that occurred from September to December 2023. Utilizing the global positioning system (GPS)/Beidou navigation satellite system (BDS) dual-system, kinematic precise point positioning (PPP) experiments were conducted, and the raw observational data from 100 stations worldwide was analyzed. The experimental results show that the positioning accuracy of some stations in high-latitude areas decreases significantly when using the conventional Geometry Free (GF) cycle-slip detection threshold during geomagnetic storms, which means that the GF is no longer applicable to high-precision positioning services. Meanwhile, there is no significant change in the satellite signal strengths received at the stations during the period of the decrease in positioning accuracy. Analyzing the cycle-slip rates for stations where abnormal accuracy occurred, it was observed that stations experiencing a significant decline in positioning accuracy exhibited serious cycle-slip misjudgments. To improve the kinematic PPP accuracy during magnetic storms, this paper proposes an adaptive threshold for cycle-slip detection and designs five experimental strategies. After using the GF adaptive threshold, the station positioning accuracy improved significantly. It achieved the accuracy level of the quiet period, while the cycle-slip incidence reached the average level. During magnetic storms, the ionosphere changes rapidly, and the use of the traditional GF constant threshold will cause serious cycle-slip misjudgments, which makes the dynamic accuracy in high latitude areas and some mid-latitude areas uncommon, while the use of the GF adaptive threshold can alleviate this phenomenon and improve the positioning accuracy in the high-latitude regions and some of the affected mid-latitude areas during the magnetic storms. [ABSTRACT FROM AUTHOR]

The Seafloor Geodetic Observation–Array (SGO-A), operated by the Japan Coast Guard, relies on the Global Navigation Satellite System–Acoustics combination (GNSS-A) technique, which integrates satellite positioning systems and undersea acoustic ranging to determine seafloor crustal deformation at the centimeter level for earthquake disaster prevention. Recently, we found distortion in the SGO-A 10-kHz carrier wave that degraded the accuracy. Carrier wave distortion can cause errors on the scale of several centimeters to twenty centimeters, which greatly impedes centimeter-level observations. This study investigated this carrier wave degradation by an underwater acoustic communication experiment conducted in 2022, using a transducer similar to that used by SGO-A. Also, we reproduced degraded waveforms through a grid search-like method for quantitatively evaluating the extent to which the interior of the equipment contributed to deterioration. Our results underscore the importance of careful consideration in signal processing, as the observed waveform degradation is not solely attributed to hardware structures but also to internal electrical circuits. The findings suggest that conventional signal identification methods may lead to errors, providing motivation for a shift towards experimental and experiential timing-based waveform identification approaches to enhance accuracy in GNSS-A systems. [ABSTRACT FROM AUTHOR]

In recent years, there has been a drastic increase in navigation satellites. Due to the computational limitations of a global navigation satellite system (GNSS) receiver, such as limited tracking channels, bandwidth, and high-power consumption, selecting an optimal subset of satellites with a better geometric dilution of precision (GDOP) has become increasingly difficult. Moreover, the computation load on the receiver increases with multi-channel observation. However, a reduced subset of used satellites will significantly increase the receiver computation performance without compromising the positioning accuracy. This paper presents an end-to-end neural network (NN) architecture based on PointNet and VoxelNet to provide an optimal satellite subset from a multi-constellation with a minimum GDOP. The architecture is based on per-satellite parameters obtained from the global positioning system (GPS) and navigation with the Indian Constellation (NavIC) satellites. Experimental results indicate that the input channel with satellite positions, Doppler, acquisition peak metric, elevation, and azimuth angles provides the best outcome in terms of performance. This method can reduce the computation burden and time by 40–50% when used in the receiver. [ABSTRACT FROM AUTHOR]

• A framework based on road mileage nodes can enhance the flexibility of maps. • Lightweight maps can be constructed using only sparse feature and elevation information. • Lightweight maps will not significantly reduce matching and positioning accuracy. • Mini-matching method achieves sub-meter level dynamic positioning. In the global navigation satellite positioning denial environment, the matching localization based on a high-definition map is a well-recognized method to assist autonomous vehicles in achieving continuous, stable, and reliable navigation and positioning in complex scenes. However, due to the complexity, density, and richness of the typical high-definition point cloud map, there are high technical thresholds in the process of localization production, application, and maintenance. As a result, referring to the idea of traverse survey in geodesy, we design a priori lightweight point cloud feature map structure based on road mileage nodes as the main line to increase the flexibility of map segmentation, splicing, retrieval, and communication transmission. At the same time, an efficient and practical mini-matching positioning method is proposed. Finally, using the real datasets of various urban canyon scenes for verification, the proposed method can achieve stable sub-meter level localization. [ABSTRACT FROM AUTHOR]