We develop an empirical model for solar radiation and related forces on GPS Block III satellites using in-orbit data, extending and refining the approach we previously applied to GPS Blocks IIA, IIR, and IIF. The model, labeled G3-SPM-2025, expresses the forces in the spacecraft body-fixed coordinate system as functions of the Earth-Spacecraft-Sun angle and the orbit beta angle, and does not require any information on the dimension, shape, and material properties of the spacecraft. The model is tailored for individual satellites, addressing SVNs 74–79, for which we have several years of precise orbit solutions. We assess the performance of the model relative to the present model employed in the GipsyX/RTGx software at JPL, which is a proprietary pre-launch, engineering-specification-based model. The new G3-SPM-2025 model performs better in terms of dynamic fit to multi-day sequences of precise orbit solutions, in overlap of daily orbit determination solutions, and in terms of orbit predictions.

The Earth’s ionosphere is susceptible to disturbances from terrestrial events, including tsunamis, which generate upward-propagating waves. Monitoring these disturbances using signals from global navigation satellites (GNSS) offers a novel way to detect these hazards. The GUARDIAN (GNSS Upper Atmospheric Real-time Disaster Information and Alert Network) System processes real-time satellite data to measure ionospheric changes. We introduce a machine learning-based extension, “Scout”, which implements automated detections for natural hazards. We demonstrate its effectiveness using the July 2025 Mw = 8.8 Kamchatka earthquake and subsequent Pacific-wide tsunami. Crucially, the system detected the ionospheric signature of the incoming tsunami 30 min before it reached the coast of Hawai’i (USA). This result highlights the potential for automated, satellite-based ionospheric monitoring to enhance existing early warning systems by providing crucial additional lead time for life-saving actions.

We present an implementation-oriented relativistic modeling framework for high-precision GNSS processing consistent with the IAU-adopted Geocentric and Barycentric Celestial Reference Systems (GCRS/BCRS) and their associated timescales (TCB/TDB and TCG/TT). We derive explicit O(c-2) transformations for position, velocity, and acceleration between TT-compatible GCRS quantities and TDB-compatible BCRS quantities, and provide screened operational forms with conservative remainder bounds that quantify state-map truncation errors for centimeter-class orbit modeling. For 10-16-class fractional-frequency transfer, the O(c-4) clock-rate terms identified below must be retained or explicitly included in the observable error budget. We implement a BCRS-native processing option in JPL's GipsyX and verify it internally via a 24 hr round-trip GCRS -> BCRS -> GCRS propagation-and-transform closure test at the few-millimeter level, demonstrating consistency of the implemented dynamical model and state transformations under matched force-model assumptions. To support emerging Earth-Moon applications, we define a Lunicentric Celestial Reference System (LCRS), its coordinate time (TCL), and a scaled lunar-surface time (TL), and specify a minimal near-rectilinear halo orbit (NRHO)-like regression test that exercises the BCRS <-> LCRS transformation chain together with the first post-Newtonian barycentric light-time model. End-to-end cislunar navigation performance additionally depends on signal availability and estimation strategy; the present work provides the relativistic reference-frame and time-transfer infrastructure needed to model observables at the centimeter and tens-of-picoseconds level.

We present an implementation-oriented relativistic modeling framework for high-precision GNSS processing consistent with the IAU-adopted Barycentric and Geocentric Celestial Reference Systems (BCRS/GCRS) and their associated time scales (TCB/TDB and TCG/TT). We derive explicit O(c^-2) transformations for position, velocity, and acceleration between TT-compatible GCRS quantities and TDB-compatible BCRS quantities, and provide screened operational forms with conservative remainder bounds that quantify truncation errors in sub-centimeter orbit modeling and retain the term order required by 10^-16-class fractional-frequency transfer. We implement a BCRS-native processing option in JPL's GipsyX and validate it via a 24 h round-trip GCRS→BCRS propagation-and-transform closure test at the few-mm level, demonstrating internal consistency of the dynamical model and the state transformations. To support emerging Earth-Moon applications, we define a Lunicentric Celestial Reference System (LCRS), its coordinate time (TCL), and a scaled lunar-surface time (TL), and specify a minimal near-rectilinear halo orbit (NRHO)-like regression test that exercises the BCRS↔LCRS transformation chain together with the 1PN barycentric light-time model. End-to-end cislunar navigation performance additionally depends on signal availability and estimation strategy; the present work provides the relativistic reference-frame and time-transfer infrastructure needed to model observables at the centimeter and tens-of-picoseconds level.

We introduce GUARDIAN, a near-real-time (NRT) ionospheric monitoring software for natural hazards warning. GUARDIAN's ultimate goal is to use NRT total electronic content (TEC) time series to (1) allow users to explore ionospheric TEC perturbations due to natural and anthropogenic events on earth, (2) automatically detect those perturbations, and (3) characterize potential natural hazards. The main goal of GUARDIAN is to provide an augmentation to existing natural hazards early warning systems (EWS). This contribution focuses mainly on objective (1): collecting GNSS measurements in NRT, computing TEC time series, and displaying them on a public website (https://guardian.jpl.nasa.gov). We validate the time series obtained in NRT using well-established post-processing methods. Furthermore, we present an inverse modeling proof of concept to obtain tsunami wave parameters from TEC time series, contributing significantly to objective (3). Note that objectives (2) and (3) are only introduced here as parts of the general architecture, and are not currently operational. In its current implementation, the GUARDIAN system uses more than 70 GNSS ground stations distributed around the Pacific Ring of Fire, and monitoring four GNSS constellations (GPS, Galileo, BDS, and GLONASS). As of today, and to the best of our knowledge, GUARDIAN is the only software available and capable of providing multi-GNSS NRT TEC time series over the Pacific region to the general public and scientific community.

Consistent inter-constellation timing is key to GNSS interoperability. We report a new capability, based on JPL’s Global Differential GPS (GDGPS) System, to monitor, assess, and predict GNSS inter-constellation timescale biases, globally, robustly, and in real-time. We demonstrate sub-nanosecond (one sigma) accuracy in determining the inter-constellation timescale bias on a sub-daily basis among all GNSS constellations with a global footprint, and a somewhat reduced accuracy relative to the regional GNSS constellations. The timescale of a specific GNSS constellation is an attribute of its broadcast ephemeris, and can only be indirectly realized through positioning (and timing) of a receiver (or preferably multiple receivers) relative to another timescale. But that process gets inevitably entangled with receiver timing biases, which are receiver-specific, installation-specific, temperature dependent, signal dependent, and constellation dependent… Therein lies the challenge of accessing, monitoring and inter-comparing the timescales expressed in the broadcast of the GNSS constellations. We compare two approaches for determining the biases between GPS and all other GNSS constellations: GLONASS, BeiDou, Galileo, QZSS, and NAVIC. Both approaches leverage the GDGPS global real-time GNSS tracking network of 60+ geodetic-quality receivers, many of which are in well-controlled environments, including several timing labs. Having so many receivers enable robust quality control and error assessment. We compare our estimates of inter-constellation biases to the values broadcasted by a variety of constellations over the last couple of years, and found general agreement at the few nsec level RMS, but also periods of large discrepancies, depending on the broadcasting constellation. We will discuss the inter-operability implications of errors in the relative timescale, and briefly describe our offering for real-time monitoring and prediction of these timescales.

GipsyX/RTGx is the Jet Propulsion Laboratory?s (JPL) next generation software package for positioning, navigation, timing, and Earth science using measurements from three geodetic techniques: Global Navigation Satellite Systems (GNSS), Satellite Laser Ranging (SLR), and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS); with Very Long Baseline Interferometry (VLBI) under development. The software facilitates combined estimation of geodetic and geophysical parameters using a Kalman filter approach on real or simulated data in both post -processing and in real-time. The estimated parameters include station coordinates and velocities, satellite orbits and clocks, Earth orientation, ionospheric and tropospheric delays. The software is also capable of full realiza- tion of a dynamic terrestrial reference through analysis and combination of time series of ground station coordinates. Applying lessons learned from its predecessors, GIPSY -OASIS and Real Time GIPSY (RTG), GipsyX/RTGx was re -designed from the ground up to offer improved precision, accuracy, usability, and operational flexibility. We present some key aspects of its new archi- tecture, and describe some of its major applications, including Real-time orbit determination and ephemeris predictions in the U.S. Air Force Next Generation GPS Operational Control Segment (OCX), as well as in JPL?s Global Differential GPS (GDGPS) System, sup- porting User Range Error (URE) of <5 cm RMS; precision post -processing GNSS orbit determination, including JPL?s contributions to the International GNSS Service (IGS) with URE in the 2 cm RMS range; Precise point positioning (PPP) with ambiguity resolution, both statically and kinematically, for geodetic applications with 2 mm horizontal, and 6.5 mm vertical repeatability for static positioning; Operational orbit and clock determination for Low Earth Orbiting (LEO) satellites, such as NASA?s Gravity Recovery and Climate Experiment (GRACE) mission with GRACE relative clock alignment at the 20 ps level; calibration of radio occultation data from LEO satellites for weather forecasting and climate studies; Satellite Laser Ranging (SLR) to GNSS and LEO satellites, DORIS-based and multi -technique orbit determination for LEO; production of terrestrial reference frames and Earth rotation parameters in support of JPL?s contribution to the International Terrestrial Reference Frame (ITRF). (c) 2020 COSPAR. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

This chapter addresses the fundamentals of global navigation satellite system-based orbit determination, highlighting the unique aspects of the technique relative to conventional terrestrial positioning. The unique challenge in satellite orbit determination is not the formulation or the solution of the estimation problem but, rather, the validation of the solution. Much of the special technology and expertise in precise orbit determination revolves around techniques and approaches for assessing solution accuracy. The inversion of the orbit determination problem to estimate the epoch state and model parameters can be accomplished with a variety of techniques, from classical least squares to various flavors of Kalman filtering or other statistical techniques. Regardless of the employed estimation technique, the first step is always the linearization of the problem around an initial approximation of the solution, consisting of a trajectory and a corresponding set of model parameters.

For airborne applications that require accurate real-time solutions and robustness to signal outages, cycle slips, etc., tightly coupled inertial navigation system (INS) is an important way to compensate for the slow convergence properties of real-time precise positioning point (PPP), and this benefit remains important even as other PPP error sources (namely, orbit and clock errors and tropospheri...

Early tsunami warning critically hinges on rapid determination of the tsunami hazard potential in real-time, before waves inundate critical coastlines. Tsunami energy can quickly characterize the destructive potential of generated waves. Traditional seismic analysis is inadequate to accurately predict a tsunami’s energy. Recently, two independent approaches have been proposed to determine tsunami source energy: one inverted from the Deep-ocean Assessment and Reporting of Tsunamis (DART) data during the tsunami propagation, and the other derived from the land-based coastal global positioning system (GPS) during tsunami generation. Here, we focus on assessing these two approaches with data from the March 11, 2011 Japanese tsunami. While the GPS approach takes into consideration the dynamic earthquake process, the DART inversion approach provides the actual tsunami energy estimation of the propagating tsunami waves; both approaches lead to consistent energy scales for previously studied tsunamis. Encouraged by these promising results, we examined a real-time approach to determine tsunami source energy by combining these two methods: first, determine the tsunami source from the globally expanding GPS network immediately after an earthquake for near-field early warnings; and then to refine the tsunami energy estimate from nearby DART measurements for improving forecast accuracy and early cancelations. The combination of these two real-time networks may offer an appealing opportunity for: early determination of the tsunami threat for the purpose of saving more lives, and early cancelation of tsunami warnings to avoid unnecessary false alarms.

We analyzed time series of daily DORIS and GPS station coordinate estimates derived from Precise Point Positioning (PPP). The DORIS coordinates were estimated using Jason-2 precise orbits based on GPS data only, implying that the station positions from the two techniques are expressed in the same GPS-based terrestrial reference frame. Comparisons of 3-D vectors of such co-located stations show systematic biases in position around South America when compared to local geodetic ties. We conclude that these results could be explained by a sensitivity of the Jason-2/DORIS oscillator to radiation when the satellite passes over the South Atlantic Anomaly (SAA). The effect for Jason-2 manifests mainly as an offset in station coordinates, though there is also evidence of a drift at the start of the mission thatdiminishes in time. This contrasts with the experience on Jason-1, wherein large, persistent drifts were observed for stations in this same (SAA) region. The spurious drift is much (∼90%) smaller for Jason-2, which may be attributable to the steps taken prior to launch to harden the oscillator. Analysis of DORIS Doppler residuals may indicate some small degradation after 2009 for these stations.

We describe a terrestrial reference frame (TRF) realization based on Global Positioning System (GPS) data alone. Our approach rests on a highly dynamic, long‐arc (9 day) estimation strategy and on GPS satellite antenna calibrations derived from Gravity Recovery and Climate Experiment and TOPEX/Poseidon low Earth orbit receiver GPS data. Based on nearly 17 years of data (1997–2013), our solution for scale rate agrees with International Terrestrial Reference Frame (ITRF)2008 to 0.03 ppb yr−1, and our solution for 3‐D origin rate agrees with ITRF2008 to 0.4 mm yr−1. Absolute scale differs by 1.1 ppb (7 mm at the Earth's surface) and 3‐D origin by 8 mm. These differences lie within estimated error levels for the contemporary TRF.

We describe a terrestrial reference frame (TRF) realization based on Global Positioning System (GPS) data alone. Our approach rests on a highly dynamic, long-arc (9 day) estimation strategy and on GPS satellite antenna calibrations derived from Gravity Recovery and Climate Experiment and TOPEX/Poseidon low Earth orbit receiver GPS data. Based on nearly 17 years of data (1997-2013), our solution for scale rate agrees with International Terrestrial Reference Frame (ITRF)2008 to 0.03 ppbyr(-1), and our solution for 3-D origin rate agrees with ITRF2008 to 0.4 mmyr(-1). Absolute scale differs by 1.1ppb (7 mm at the Earth's surface) and 3-D origin by 8 mm. These differences lie within estimated error levels for the contemporary TRF.

We use a series of simulated scenarios to characterize the observability of geocenter location with GPS tracking data. We examine in particular the improvement realized when a GPS receiver in low Earth orbit (LEO) augments the ground network. Various orbital configurations for the LEO are considered and the observability of geocenter location based on GPS tracking is compared to that based on satellite laser ranging (SLR). The distance between a satellite and a ground tracking-site is the primary measurement, and Earth rotation plays important role in determining the geocenter location. Compared to SLR, which directly and unambiguously measures this distance, terrestrial GPS observations provide a weaker (relative) measurement for geocenter location determination. The estimation of GPS transmitter and receiver clock errors, which is equivalent to double differencing four simultaneous range measurements, removes much of this absolute distance information. We show that when ground GPS tracking data are augmented with precise measurements from a GPS receiver onboard a LEO satellite, the sensitivity of the data to geocenter location increases by more than a factor of two for Z-component. The geometric diversity underlying the varying baselines between the LEO and ground stations promotes improved global observability, and renders the GPS technique comparable to SLR in terms of information content for geocenter location determination. We assess a variety of LEO orbital configurations, including the proposed orbit for the geodetic reference antenna in space mission concept. The results suggest that a retrograde LEO with altitude near 3,000 km is favorable for geocenter determination.

This paper details the integration of an Inertial Navigation System (INS) processing capability within JPL's RTGx geodetic data analysis and navigation software, and provides a performance analysis with experimental flight data in order to validate the implementation. The RTGx software, when used in conjunction with JPL's Global Differential GPS System (GDGPS), can be configured for real-t ime kinematic Precise Point Positioning (K-PPP) for centimeter-level positioning accuracy. Since 2006, RTGx's predecessor, RTG, has provided operational real-time K-PPP for NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) repeat pass interferometry mission on campaigns all over the world. While RTG's GPS-only data processing is meeting mission requirements during nominal science operations, its performance naturally degrades during certain flight scenarios, such as abrupt changes in the aircraft attitude or high banking turns, which induce signal loss-of-lock, carrier-phase breaks and/or cycle slips. During these periods, the well-known downsides of K-PPP, including the position solution's sensitivity to phase breaks and slow convergence after loss-of-lock become apparent, and may impact the instruments critical data take periods. Therefore, tightly-coupled INS has been integrated into RTGx to offer additional robustness. This paper discusses the adopted INS formulation and uses the flight data made available to the community by the National Geodetic Survey's Kinematic Challenge (Damiani et al., 2013) to offer an experimental performance evaluation. The integration of INS in RTGx is shown to provide solution improvements both in terms of accuracy and precision with respect to a post-processed ambiguity-fixed reference solution. Furthermore, the integration of INS into the RTGx software will enable RTGx to support new application domains.