Real-Time Specifications of the Geospace Environment

We report the recent progress in our joint program of real-time mapping of ionospheric electric fields and currents and field-aligned currents through the Geospace Environment Data Analysis System (GEDAS) at the Solar-Terrestrial Environment Laboratory and similar computer systems in the world. Data from individual ground magnetometers as well as from the solar wind are collected by these systems and are used as input for the KRM and AMIE magnetogram-inversion algorithms, which calculate the two-dimensional distribution of the ionospheric parameters. One of the goals of this program is to specify the solar-terrestrial environment in terms of ionospheric processes, providing the scientific community with more than what geomagnetic activity indices and statistical models provide. This revised version was published online in August 2006 with corrections to the Cover Date.     

Neutral Upper Atmosphere and Ionosphere Modeling

Numerical modeling tools can be used for a number of reasons yielding many benefits in their application to planetary upper atmosphere and ionosphere environments. These tools are commonly used to predict upper atmosphere and ionosphere characteristics and to interpret measurements once they are obtained. Additional applications of these tools include conducting diagnostic balance studies, converting raw measurements into useful physical parameters, and comparing features and processes of different planetary atmospheres. This chapter focuses upon various classes of upper atmosphere and ionosphere numerical modeling tools, the equations solved and key assumptions made, specified inputs and tunable parameters, their common applications, and finally their notable strengths and weaknesses. Examples of these model classes and their specific applications to individual planetary environments will be described.     

Doppler Compensation & Single Pulse Imaging using Adaptive Pulse Compression

The effects of target Doppler are addressed in relation to adaptive receive processing for radar pulse compression. To correct for Doppler-induced filter mismatch over a single pulse, the Doppler-compensated adaptive pulse compression (DC-APC) algorithm is presented whereby the respective Doppler shifts for large target returns are jointly estimated with the illuminated range profile and subsequently incorporated into the original APC adaptive receive filter formulation. As a result, the Doppler-mismatch-induced range sidelobes can be suppressed thereby regaining a significant portion of the sensitivity improvement that is possible when applying adaptive pulse compression (APC) without the existence of significant Doppler mismatch. In contrast, instead of compensating for Doppler mismatch, the single pulse imaging (SPI) algorithm generalizes the APC formulation for a bank of Doppler-shifted matched filters thereby producing a sidelobe-suppressed range-Doppler image from the return signal of a single radar pulse which is applicable for targets with substantial variation in Doppler. Both techniques are based on the recently proposed APC algorithm and its generalization, the multistatic adaptive pulse compression (MAPC) algorithm, which have been shown to be effective for the suppression of pulse compression range sidelobes thus dramatically increasing the sensitivity of pulse compression radar.     

Physiologic and metabolic responses of wheat seedlings to elevated and super-elevated carbon dioxide

The metabolic consequence of suboptimal (400 μmol mol⁻¹ or ppm), near-optimal (1500 ppm) and supra-optimal (10,000 ppm) atmospheric carbon dioxide concentrations [CO₂] was investigated in an attempt to reveal plausible underlying mechanisms for the differential physiological and developmental responses to increasing [CO₂]. Both non-targeted and targeted metabolite profiling by GC–MS and LC–MS were employed to examine primary and secondary metabolites in wheat (Triticum aestivum, cv Yocoro rojo) continuously exposed to these [CO₂] levels for 14, 21 and 28 days. Metabolite profile was altered by both [CO₂] and physiological age. In general, plants grown under high [CO₂] exhibited a metabolite profile characteristic of older plants under ambient CO₂. Elevated [CO₂] resulted in higher levels of phosphorylated sugar intermediates, though no clear trend in the content of reducing sugars was observed. Transient starch content was enhanced by increasing [CO₂] to a much greater extent at 10,000 ppm CO₂ than at 1500 ppm CO₂. The percentage increase of starch content resulting from CO₂ enrichment declined as plants develope. In contrast, elevated [CO₂] promoted the accumulation of secondary metabolites (flavonoids) progressively to a greater extent as plants became mature. Elevated [CO₂] to 1500 ppm induced a higher initial growth rate, while super-elevated [CO₂] appeared to negate such initial growth promotion. However, after 4 weeks, there was no difference in vegetative growth between 1500 and 10,000 ppm CO₂-grown plants, both elevated CO₂ levels resulted in an overall 25% increase in biomass over the control plants. More interestingly, elevated atmospheric [CO₂] reduced evapotranspiration rate (ET), but further increase to the supra-optimal level resulted in increased ET (a reversed trend), i.e. ET at 1500 ppm < ET at 10,000 ppm < ET at 400 ppm. The differential effect of elevated and super-elevated CO₂ on plants was further reflected in the nitrogen dynamics. These results provide the potential metabolic basis for the differential productivity and stomatal function of plants grown under elevated and super-elevated CO₂ levels.     

Assessing and minimizing collisions in satellite mega-constellations

We aim to provide satellite operators and researchers with an efficient means for evaluating and mitigating collision risk during the design process of mega-constellations. We first introduce a novel algorithm for conjunction prediction that relies on large-scale numerical simulations and uses a sequence of filters to greatly reduce its computational expense. We then use this brute-force algorithm to establish baselines of endogenous (intra-constellation), or self-induced, conjunction events for the FCC-reported designs of the OneWeb LEO and SpaceX Starlink mega-constellations. We demonstrate how these deterministic results can be used to validate more computationally efficient, stochastic techniques for close-encounter prediction by adopting a new probabilistic approach from Solar-System dynamics as a simple test case. Finally, we show how our methodology can be applied during the design phase of large constellations by investigating Minimum Space Occupancy (MiSO) orbits, a generalization of classical frozen orbits that holistically account for the perturbed-Keplerian dynamics of the Earth-satellite-Moon-Sun system. The results indicate that the adoption of MiSO orbital configurations of the proposed mega-constellations can significantly reduce the risk of endogenous collisions with nearly indistinguishable adjustments to the nominal orbital elements of the constellation satellites.     

Decentralized formation pose estimation for spacecraft swarms

For spacecraft swarms, the multi-agent localization algorithm must scale well with the number of spacecraft and adapt to time-varying communication and relative sensing networks. In this paper, we present a decentralized, scalable algorithm for swarm localization, called the Decentralized Pose Estimation (DPE) algorithm. The DPE considers both communication and relative sensing graphs and defines an observable local formation. Each spacecraft jointly localizes its local subset of spacecraft using direct and communicated measurements. Since the algorithm is local, the algorithm complexity does not grow with the number of spacecraft in the swarm. As part of the DPE, we present the Swarm Reference Frame Estimation (SRFE) algorithm, a distributed consensus algorithm to co-estimate a common Local-Vertical, Local-Horizontal (LVLH) frame. The DPE combined with the SRFE provides a scalable, fully-decentralized navigation solution that can be used for swarm control and motion planning. Numerical simulations and experiments using Caltech’s robotic spacecraft simulators are presented to validate the effectiveness and scalability of the DPE algorithm.     

Multi-point observations and modeling of subauroral polarization streams (SAPS) and double-peak subauroral ion drifts (DSAIDs): A case study

While subauroral polarization streams (SAPS) are well recognized as representatively one of the most important features of magnetosphere-ionosphere (M-I) coupling processes in the subauroral region, the double-peak subauroral ion drifts (DSAIDs) is a newly recognized ionospheric phenomenon, categorized as a subset of subauroral ion drifts (SAIDs). In this study, we investigate both SAPS and DSAIDs that appear during the storm main phase of the 17 March 2015 event through a combination of multi-point observations and numerical simulations. We find that when SAPS/DSAIDs are observed by the DMSP spacecraft near the dusk subauroral region, strong electric fields are detected minutes later by the Van Allen Probes almost in the same conjugate region near the equatorial plane. Numerical simulations are carried out not only to reveal the global context and dynamic evolution of the SAPS in both the magnetospheric and ionospheric systems, but also to aid the understanding of the effect of conductance on the DSAIDs. Our results confirm that SAPS are indeed associated with Region 2 field-aligned currents (FACs) flowing into the low conductance region. On the other hand, the DSAIDs may be related to the double-conductance-trough in the subauroral region.     

Acoustic κ-density fluctuation waves in suprathermal κ function fluids

We describe a new wave mode similar to the acoustic wave in which both density and velocity fluctuate. Unlike the acoustic wave in which the underlying distribution is Maxwellian, this new wave mode occurs when the underlying distribution is a suprathermal κ-function and involves fluctuations in the power law index, κ. This wave mode always propagates faster than the acoustic wave with an equivalent effective temperature and becomes the acoustic wave in the Maxwellian limit as κ → ∞.