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Accurate astrometry is crucial for determining orbits of near-Earth-asteroids (NEAs) and therefore better tracking them. This paper reports on a demonstration of 10 milliarcsecond-level astrometric precision on a dozen NEAs using the Pomona College 40 inch telescope, at the JPL's Table Mountain Facility. We used the technique of synthetic tracking, in which many short exposure (1 second) images are acquired and then combined in post-processing to track both target asteroid and reference stars across the field of view. This technique avoids the trailing loss and keeps the jitter effects from atmosphere and telescope pointing common between the asteroid and reference stars, resulting in higher astrometric precision than the 100 mas level astrometry from traditional approach of using long exposure images. Treating our synthetic tracking of near-Earth asteroids as a proxy for observations of future spacecraft while they are downlinking data via their high rate optical communication laser beams, our approach shows precision plane-of-sky measurements can be obtained by the optical ground terminals for navigation. We also discuss how future data releases from the Gaia mission can improve our results., Comment: 26 pages, 10 figures, submitted to the Astronomical Journal

We present a new space mission concept that is capable of finding, detecting, and tracking 90% of near-Earth objects (NEO) with H magnitude of $\rm H\leq22$ (i.e., $\sim$140 m in size) that are potentially hazardous to the Earth. The new mission concept relies on two emerging technologies: the technique of synthetic tracking and the new generation of small and capable interplanetary spacecraft. Synthetic tracking is a technique that de-streaks asteroid images by taking multiple fast exposures. With synthetic tracking, an 800 sec observation with a 10 cm telescope in space can detect a moving object with apparent magnitude of 20.5 without losing sensitivity from streaking. We refer to NEOs with a minimum orbit intersection distance of $< 0.002$ au as Earth-grazers (EGs), representing typical albedo distributions. We show that a constellation of six SmallSats (comparable in size to 9U CubeSats) equipped with 10 cm synthetic tracking cameras and evenly-distributed in 1.0 au heliocentric orbit could detect 90% of EGs with $\rm H \leq 22~mag$ in $\sim$3.8 years of observing time. A more advanced constellation of nine 20 cm telescopes could detect 90% of $\rm H=24.2~mag$ (i.e., $\rm \sim 50~m$ in size) EGs in less than 5 years., Comment: 14 pages, 16 figures, 4 tables

We report a detection of a faint near-Earth asteroid (NEA), which was done using our synthetic tracking technique and the CHIMERA instrument on the Palomar 200-inch telescope. This asteroid, with apparent magnitude of 23, was moving at 5.97 degrees per day and was detected at a signal-to-noise ratio (SNR) of 15 using 30 sec of data taken at a 16.7 Hz frame rate. The detection was confirmed by a second observation one hour later at the same SNR. The asteroid moved 7 arcseconds in sky over the 30 sec of integration time because of its high proper motion. The synthetic tracking using 16.7 Hz frames avoided the trailing loss suffered by conventional techniques relying on 30-sec exposure, which would degrade the surface brightness of image on CCD to an approximate magnitude of 25. This detection was a result of our 12-hour blind search conducted on the Palomar 200-inch telescope over two nights on September 11 and 12, 2013 scanning twice over six 5.0 deg x 0.043 deg fields. The fact that we detected only one NEA, is consistent with Harris's estimation of the asteroid population distribution, which was used to predict the detection of 1--2 asteroids of absolute magnitude H=28--31 per night. The design of experiment, data analysis method, and algorithms for estimating astrometry are presented. We also demonstrate a milli-arcsecond astrometry using observations of two bright asteroids with the same system on Apr 3, 2013. Strategies of scheduling observations to detect small and fast-moving NEAs with the synthetic tracking technique are discussed.

The 2017 Decadal Survey: Thriving on Our Changing Planet, A Decadal Strategy for Earth Observation from Space has called new observations including global coverage VSWIR Wide Swath (VSWIR-WS) imaging spectroscopy measurements as part of the Surface Biology and Geology (SBG) Designated Observable. The SBG VSWIR-WS along with the companion SBG Thermal Infrared (TIR) imager is an important element of NASA’s larger Earth System Observatory (ESO).

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Spacecraft carrying optical communication lasers can be treated as artificial stars, whose relative astrometry to Gaia reference stars provides spacecraft positions in the plane-of-sky for optical navigation. To be comparable to current Deep Space Network delta-Differential One-way Ranging measurements, thus sufficient for navigation, nanoradian optical astrometry is required. Here we describe our error budget, techniques for achieving nanoradian level ground-base astrometry, and preliminary results from a 1 m telescope. We discuss also how these spacecraft may serve as artificial reference stars for adaptive optics, high precision astrometry to detect exoplanets, and tying reference frames defined by radio and optical measurements.

Shortly after JPL’s Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) mission launches, separates, and commences its cruise phase, two CubeSats will deploy from the launch vehicle’s upper stage and begin independent flight to Mars (Fig. 1). During InSight’s entry, descent, and landing (EDL) sequence, these twin Mars Cube One (MarCO) spacecraft will fly 3,500 km above the Martian surface, recording and relaying InSight UHF radio data to the Deep Space Network (DSN) on Earth1. MarCO is a twin CubeSat mission developed by the NASA Jet Propulsion Laboratory (JPL) to accompany the InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) Mars mission lander. MarCO's primary mission objective is to launch with InSight and independently fly to Mars to serve as a communications relay during InSight's entry, descent, and landing (EDL) phase. MarCO represents a new type of deep space mission: CubeSats at Mars. Building on the development of JPL's first interplanetary CubeSat project, the Interplanetary Nano-Spacecraft Pathfinder in Relevant Environment (INSPIRE), MarCO further refined the approach to hardware, software, and ground architecture development to solve the challenges of quickly building low-budget spacecraft to fly to Mars. The greatest constraint, beyond others typical of CubeSat missions, was time. The duration between MarCO's conception to completion of spacecraft assembly was less than two years - an unprecedented schedule for any planetary mission to date. Through necessity, MarCO has built on previous experience, procedures, systems, and development methodologies, defining a new niche for supporting larger primary missions. The MarCO spacecraft are poised to write a new chapter in deep space exploration. Originally slated to launch and reach Mars in 2016, the InSight mission schedule subsequently slipped to 2018. During the original landing of InSight, Earth would not be in view, and no orbiter around Mars would have been in position to both receive UHF EDL data and simultaneously relay it back to Earth. It was from this obstacle that MarCO was conceived. Regardless of any changes to InSight’s 2018 EDL configuration geometry, MarCO is still expected to fly and serve in the same capacity as originally designed: the first CubeSat mission to Mars. CubeSats have historically been firmly in the domain of universities and small companies. As first conceived, they served as a platform upon which to teach all aspects of the space mission lifecycle. JPL took on this mission type with Interplanetary Nano-Spacecraft Pathfinder in Relevant Environment2 (INSPIRE), moving the concept into a new domain: deep space. Building from the INSPIRE platform and lessons learned, MarCO addressed new challenges in the domain of planetary missions: independent interplanetary flight and navigation, integration with a large-scale mission, long-distance and long-delay communication, short development time, and a small development team. Of these, the greatest constraint was schedule: only 18 months passed from conception of mission concept until delivery of fully assembled and tested flight hardware. Careful selection of mission team, along with extensive use of off-the-shelf equipment, and streamlining automated processes, was essential. This achievement represents the next step in the evolution of CubeSats beyond low-Earth orbit.

Solar System Exploration camera implementations to date have involved either single cameras with wide field-of-view (FOV) and consequently coarser spatial resolution, cameras on a movable mast, or single cameras necessitating rotation of the host vehicle to afford visibility outside a relatively narrow FOV. These cameras require detailed commanding from the ground or separate onboard computers to operate properly, and are incapable of making decisions based on image content that control pointing and downlink strategy. For color, a filter wheel having selectable positions was often added, which added moving parts, size, mass, power, and reduced reliability. A system was developed based on a general-purpose miniature visible-light camera using advanced CMOS (complementary metal oxide semiconductor) imager technology. The baseline camera has a 92 FOV and six cameras are arranged in an angled-up carousel fashion, with FOV overlaps such that the system has a 360 FOV (azimuth). A seventh camera, also with a FOV of 92 , is installed normal to the plane of the other 6 cameras giving the system a > 90 FOV in elevation and completing the hemispheric vision system. A central unit houses the common electronics box (CEB) controlling the system (power conversion, data processing, memory, and control software). Stereo is achieved by adding a second system on a baseline, and color is achieved by stacking two more systems (for a total of three, each system equipped with its own filter.) Two connectors on the bottom of the CEB provide a connection to a carrier (rover, spacecraft, balloon, etc.) for telemetry, commands, and power. This system has no moving parts. The system's onboard software (SW) supports autonomous operations such as pattern recognition and tracking.

MicroShell is a lightweight shell environment for engineers and software developers working with embedded microprocessors in Xilinx FPGAs. (MicroShell has also been successfully ported to run on ARM Cortex-M1 microprocessors in Actel ProASIC3 FPGAs, but without project-integration support.) Micro Shell decreases the time spent performing initial tests of field-programmable gate array (FPGA) designs, simplifies running customizable one-time-only experiments, and provides a familiar-feeling command-line interface. The program comes with a collection of useful functions and enables the designer to add an unlimited number of custom commands, which are callable from the command-line. The commands are parameterizable (using the C-based command-line parameter idiom), so the designer can use one function to exercise hardware with different values. Also, since many hardware peripherals instantiated in FPGAs have reasonably simple register-mapped I/O interfaces, the engineer can edit and view hardware parameter settings at any time without stopping the processor. MicroShell comes with a set of support scripts that interface seamlessly with Xilinx's EDK tool. Adding an instance of MicroShell to a project is as simple as marking a check box in a library configuration dialog box and specifying a software project directory. The support scripts then examine the hardware design, build design-specific functions, conditionally include processor-specific functions, and complete the compilation process. For code-size constrained designs, most of the stock functionality can be excluded from the compiled library. When all of the configurable options are removed from the binary, MicroShell has an unoptimized memory footprint of about 4.8 kB and a size-optimized footprint of about 2.3 kB. Since MicroShell allows unfettered access to all processor-accessible memory locations, it is possible to perform live patching on a running system. This can be useful, for instance, if a bug is discovered in a routine but the system cannot be rebooted: Shell allows a skilled operator to directly edit the binary executable in memory. With some forethought, MicroShell code can be located in a different memory location from custom code, permitting the custom functionality to be overwritten at any time without stopping the controlling shell.

This paper presents the COVE payload architecture on the M-Cubed CubeSat and explores how the capabilities of this Virtex-5 FPGA-based processing platform could enable future CubeSat missions

The SIM-Lite astrometric interferometer will search for Earth-size planets in the habitable zones of nearby stars. In this search the interferometer will monitor the astrometric position of candidate stars relative to nearby reference stars over the course of a 5 year mission. The elemental measurement is the angle between a target star and a reference star. This is a two-step process, in which the interferometer will each time need to use its controllable optics to align the starlight in the two arms with each other and with the metrology beams. The sensor for this alignment is an angle tracking CCD camera. Various constraints in the design of the camera subject it to systematic alignment errors when observing a star of one spectrum compared with a start of a different spectrum. This effect is called a Color Dependent Centroid Shift (CDCS) and has been studied extensively with SIM-Lite's SCDU testbed. Here we describe results from the simulation and testing of this error in the SCDU testbed, as well as effective ways that it can be reduced to acceptable levels.

The most stringent astrometric performance requirements on NASA's SIM(Space Interferometer Mission)-Lite mission will come from the so-called Narrow-Angle (NA) observing scenario, aimed at finding Earth-like exoplanets, where the interferometer chops between the target star and several nearby reference stars multiple times over the course of a single visit. Previously, about 20 pm NA error with various shifts was reported. Since then, investigation has been under way to understand the mechanisms that give rise to these shifts. In this paper we report our findings, the adopted mitigation strategies, and the resulting testbed performance.

The Earth Sciences Decadal Survey identifies a multiangle, multispectral, high-accuracy polarization imager as one requirement for the Aerosol-Cloud-Ecosystem (ACE) mission. JPL has been developing a Multiangle SpectroPolarimetric Imager (MSPI) as a candidate to fill this need. A key technology development needed for MSPI is on-board signal processing to calculate polarimetry data as imaged by each of the 9 cameras forming the instrument. With funding from NASA's Advanced Information Systems Technology (AIST) Program, JPL is solving the real-time data processing requirements to demonstrate, for the first time, how signal data at 95 Mbytes/sec over 16-channels for each of the 9 multiangle cameras in the spaceborne instrument can be reduced on-board to 0.45 Mbytes/sec. This will produce the intensity and polarization data needed to characterize aerosol and cloud microphysical properties. Using the Xilinx Virtex-5 FPGA including PowerPC440 processors we have implemented a least squares fitting algorithm that extracts intensity and polarimetric parameters in real-time, thereby substantially reducing the image data volume for spacecraft downlink without loss of science information.

A multi-angle spectro-polarimetric imager (MSPI) is an advanced camera system currently under development at JPL for possible future consideration on a satellite-based Aerosol-Cloud-Environ - ment (ACE) interaction study. The light in the optical system is subjected to a complex modulation designed to make the overall system robust against many instrumental artifacts that have plagued such measurements in the past. This scheme involves two photoelastic modulators that are beating in a carefully selected pattern against each other. In order to properly sample this modulation pattern, each of the proposed nine cameras in the system needs to read out its imager array about 1,000 times per second. The onboard processing required to compress this data involves least-squares fits (LSFs) of Bessel functions to data from every pixel in realtime, thus requiring an onboard computing system with advanced data processing capabilities in excess of those commonly available for space flight. As a potential solution to meet the MSPI onboard processing requirements, an LSF algorithm was developed on the Xilinx Virtex-4FX60 field programmable gate array (FPGA). In addition to configurable hardware capability, this FPGA includes Power -PC405 microprocessors, which together enable a combination hardware/ software processing system. A laboratory demonstration was carried out based on a hardware/ software co-designed processing architecture that includes hardware-based data collection and least-squares fitting (computationally), and softwarebased transcendental function computation (algorithmically complex) on the FPGA. Initial results showed that these calculations can be handled using a combination of the Virtex- 4TM Power-PC core and the hardware fabric.

Traditional design methodology dictates that an instrument electronics platform should consist of a printed circuit board (PCB)—often multiple boards—populated with many components and support electronics. More specifically, each subsystem is composed of numerous integrated circuits (ICs) spread across the board(s), connected with innumerable traces and wires. Additionally, it is often the case that the hardware and software design teams are quite separated—the hardware team designs a board and hands it to a software team, who must then deal with any hardware quirkiness and may need to rewrite software due to inadequately defined interfaces...

An effort related to that described in the preceding article focuses on developing a spaceborne processing platform for fast and accurate onboard classification of image data, a critical part of modern satellite image processing. The approach again has been to exploit the versatility of recently developed hybrid Virtex-4FX field-programmable gate array (FPGA) to run diverse science applications on embedded processors while taking advantage of the reconfigurable hardware resources of the FPGAs. In this case, the FPGA serves as a coprocessor that implements legacy C-language support-vector-machine (SVM) image-classification algorithms to detect and identify natural phenomena such as flooding, volcanic eruptions, and sea-ice break-up. The FPGA provides hardware acceleration for increased onboard processing capability than previously demonstrated in software. The original C-language program demonstrated on an imaging instrument aboard the Earth Observing-1 (EO-1) satellite implements a linear-kernel SVM algorithm for classifying parts of the images as snow, water, ice, land, or cloud or unclassified. Current onboard processors, such as on EO-1, have limited computing power, extremely limited active storage capability and are no longer considered state-of-the-art. Using commercially available software that translates C-language programs into hardware description language (HDL) files, the legacy C-language program, and two newly formulated programs for a more capable expanded-linear-kernel and a more accurate polynomial-kernel SVM algorithm, have been implemented in the Virtex-4FX FPGA. In tests, the FPGA implementations have exhibited significant speedups over conventional software implementations running on general-purpose hardware.

Accurate, on-board classification of instrument data is used to increase science return by autonomously identifying regions of interest for priority transmission or generating summary products to conserve transmission bandwidth. Due to on-board processing constraints, such classification has been limited to using the simplest functions on a small subset of the full instrument data. FPGA co-processor designs for SVM1 classifiers will lead to significant improvement in on-board classification capability and accuracy.