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This paper describes the relationship between the Space Interferometer Mission (SIM) and the MicroArcsecond Measurment Testbed (MAM). MAM is necessary because differences exist between starlight and the metrology measurements through the SIM instrument optical path.
In this paper we outline the design of the SIM Instrument, and how it will be used in the search for extrasolar planets. We also briefly describe some selected topics from the SIM astrometric science program.
The Space Interferometry Mission (SIM) fligt system will be launched in June of 2005 into a nearly circular orbit arount the Earth. A Delta II 7920 launch vehicle will boost the SIM flight System from the Vandenberg Air Force Base into Earth orbit.
The volatile element Cl can be lost during the formation and evolution of planetary bodies, leading to fractionation of its two stable isotopes 35Cl and 37Cl. Chlorine isotope variations (reported as δ37Cl in parts per thousand (‰) relative to Standard Mean Ocean Chloride, SMOC) are documented to exceed 80‰ between different lunar rock samples and have been variably interpreted as the fingerprint of degassing during accretion, magma ocean, or volcanic portions of lunar history. The large intersample and intrasample variations observed by both bulk isotope ratio mass spectrometry (IRMS) and in-situ secondary ion mass spectrometry (SIMS) methods are difficult to interpret in part because of a paucity of bulk Cl isotope measurements. This lack of high-precision bulk data is due to the relative rarity of IRMS laboratories capable of making these high precision measurements on small samples of precious planetary materials such as those returned by human or robotic exploration. Here we present a new method for performing high precision δ37Cl measurements using the modified Middleton ion source of an existing accelerator mass spectrometer. For samples with as little as 1 μg Cl–the equivalent of 2–4 mm3 of a typical lunar rock sample–the average cathode accuracy is ∼1‰. Cathode reproducibility is typically ∼1‰ (2σ) for samples with at least 10 μg of Cl, increasing to ∼3–6‰ for aliquots with ∼1–2 μg Cl, similar to published SIMS results and sufficient to study astromaterials from the Moon, Mars, or 4 Vesta, which have tens of ‰ observed variations.
Depending on the environment, multipath can be one of the largest error sources contributing to degradation in Global Navigation Satellite System (GNSS) (e.g., GPS) performance. Currently, open-source tools for simulating GPS signals are available and can be used in the testing and evaluation of GPS receiver equipment. These tools can generate GPS signals that, when used by a GPS receiver, result in computation of a position solution that was pre-determined at the time of signal generation. This work utilizes a custom version of the open-source GPS-SDR-SIM to produce emulated multipath GPS signals. A proof of concept was prototyped and demonstrated using this modified version of GPS-SDR-SIM to produce GPS as well as multipath signals. The generated data was processed using a software defined GPS receiver (GNSS-SDR) and it was found that the introduction of simulated multipath signals successfully produced the expected characteristics of a composite multipath signal in simulation.
Depending on the environment, multipath can be one of the largest error sources contributing to degradation in Global Navigation Satellite System (GNSS) (e.g., GPS) performance. Currently, open-source tools for simulating GPS signals are available and can be used in the testing and evaluation of GPS receiver equipment. These tools can generate GPS signals that, when used by a GPS receiver, result in computation of a position solution that was pre-determined at the time of signal generation. This work utilizes a custom version of the open-source GPS-SDR-SIM to produce emulated multipath GPS signals. A proof of concept was prototyped and demonstrated using this modified version of GPS-SDR-SIM to produce GPS as well as multipath signals. The generated data was processed using a software defined GPS receiver (GNSS-SDR) and it was found that the introduction of simulated multipath signals successfully produced the expected characteristics of a composite multipath signal in simulation.
The challenging environment of autonomous vehicle (AV) navigation necessitates certain functions be performed by deep neural networks. Optimizing these models involves collecting vast quantities of domain-specific training data and ensuring that the dataset is representative of expected conditions. High-fidelity simulation plays a vital role in making this process feasible, allowing a wide range of scenarios to be explored at low cost. However, learning from simulation introduces subtle biases into models, which can degrade real-world performance in unpredictable ways. This effect can be mitigated with learning schemes specialized to bridge distributional shifts (transfer learning). Given the complex nature of these methods, the underlying models, and their environments, meaningfully evaluating performance is notstraight forward. Many unrelated factors can effect an improvement in generalization accuracy, but a full ablation analysis is often difficult. To tease out signal from noise, it is necessary to understand how transfer learning performance is affected by noise itself. The goals of this paper are (i) to establish a domain randomization baseline for a simple classification transfer learning task and (ii) to validate the RRAV testbed as a platform for further research in sim-to-real learning. We generate imagery from a simulation of NASA Ames Research Center and train a small convolutional neural network (ConvNet) to classify position relative to a centerline. Further models are trained with different types of noise progressively added to the data. The models are deployed aboard the on-site test vehicle to test real-world performance. In our experiments, we find that such naive domain randomization raises sim-to-real accuracy from 64% to 79%, while training directly on real data yields an 89% accuracy ceiling. These results suggest that the isolated mechanism of domain randomization can significantly improve generalization.
The Picometer Knowledge Transfer testbed is one of several technology testbeds that will help to prove technology readiness for the Space Interferometry Mission (SIM).
In this paper, we discuss the current reference design of the SIM instrument, and illustrate some of the tradeoffs that led to this arrangement.
The Space Interferometry Mission (SIM) is a space-based long-baseline optical interferometer for precision astrometry.
The Space Interferometry Mission (SIM) relies on interferometry and metrology capable of measuring the change in the optical path difference with picometer accuracy.
We summarize here results of our recent study of the relativistic stellar aberration requirements for the Space Interferometry Mission (SIM).
In 2006, NASA's Origins Program will launch the Space Interferometry Mission (SIM), a 10 meter baseline optical interferometry instrument, into a Earth trailing orbit.
Heterodyne interferometers have been commercially available for many years. In addition, many versions have been built at JPL for various projects. This activity is aimed at improving the accuracy of such interferometers from the 1-30 nanometer level to the picometer level for use in the proposes Stellar Interferometry Mission (SIM) as metrology gauges.
The Space Interferometry Mission (SIM) will be the NASA Origins Program's first space based long baseline interferometric observatory.
Participating in a Navy STTR project to develop a system capable of the 'real-time' detection and quanitification of nuclear, biological and chemical (NBC) warfare agents, and of related industrial chemicals including NBC agent synthesis by-products in water and in air immediately above the water's surface. This project uses JPL's Soft Ionization Membrane (SIM) technology which totally ionizes molecules without fragmentation (a process that can markedly improve the sensitivity and specificity of molecule compostition identification), and JPL's Rotating Field Mass Spectrometer (RFMS) technology which has large enough dynamic mass range to enable detection of nuclear materials as well as biological and chemical agents. This Navy project integrates these JPL Environmental Monitoring UnitS (REMUS) an autonomous underwater vehicle (AUV). It is anticipated that the REMUS AUV will be capable of 'real-time' detection and quantification of NBC warefare agents.
In the course of fulfilling its mandate, the Spectral Calibration Development Unit (SCDU) testbed for SIM-Lite produces copious amounts of raw data. To effectively spend time attempting to understand the science driving the data, the team devised computerized automations to limit the time spent bringing the testbed to a healthy state and commanding it, and instead focus on analyzing the processed results. We developed a multi-layered scripting language that emphasized the scientific experiments we conducted, which drastically shortened our experiment scripts, improved their readability, and all-but-eliminated testbed operator errors. In addition to scientific experiment functions, we also developed a set of automated alignments that bring the testbed up to a well-aligned state with little more than the push of a button. These scripts were written in the scripting language, and in Matlab via an interface library, allowing all members of the team to augment the existing scripting language with complex analysis scripts. To keep track of these results, we created an easily-parseable state log in which we logged both the state of the testbed and relevant metadata. Finally, we designed a distributed processing system that allowed us to farm lengthy analyses to a collection of client computers which reported their results in a central log. Since these logs were parseable, we wrote query scripts that gave us an effortless way to compare results collected under different conditions. This paper serves as a case-study, detailing the motivating requirements for the decisions we made and explaining the implementation process.
The proposed Space Interferometry Mission (SIM) spacecraft designs include high resolution stellar interferometers for micro-arc-second accuracy astrometric measurements.