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NASA NTRS2012

VESGEN Software for Mapping and Quantification of Vascular Regulators

VESsel GENeration (VESGEN) Analysis is an automated software that maps and quantifies effects of vascular regulators on vascular morphology by analyzing important vessel parameters. Quantification parameters include vessel diameter, length, branch points, density, and fractal dimension. For vascular trees, measurements are reported as dependent functions of vessel branching generation. VESGEN maps and quantifies vascular morphological events according to fractal-based vascular branching generation. It also relies on careful imaging of branching and networked vascular form. It was developed as a plug-in for ImageJ (National Institutes of Health, USA). VESGEN uses image-processing concepts of 8-neighbor pixel connectivity, skeleton, and distance map to analyze 2D, black-and-white (binary) images of vascular trees, networks, and tree-network composites. VESGEN maps typically 5 to 12 (or more) generations of vascular branching, starting from a single parent vessel. These generations are tracked and measured for critical vascular parameters that include vessel diameter, length, density and number, and tortuosity per branching generation. The effects of vascular therapeutics and regulators on vascular morphology and branching tested in human clinical or laboratory animal experimental studies are quantified by comparing vascular parameters with control groups. VESGEN provides a user interface to both guide and allow control over the users vascular analysis process. An option is provided to select a morphological tissue type of vascular trees, network or tree-network composites, which determines the general collections of algorithms, intermediate images, and output images and measurements that will be produced.

Parsons-Wingerter, Patricia A.↗

NASA NTRS2011

Bringing Together Users and Developers of Forest Biomass Maps

Forests store carbon and thus represent important sinks for atmospheric carbon dioxide. Reducing uncertainty in current estimates of the amount of carbon in standing forests will improve precision of estimates of anthropogenic contributions to carbon dioxide in the atmosphere due to deforestation. Although satellite remote sensing has long been an important tool for mapping land cover, until recently aboveground forest biomass estimates have relied mostly on systematic ground sampling of forests. In alignment with fiscal year 2010 congressional direction, NASA has initiated work toward a carbon monitoring system (CMS) that includes both maps of forest biomass and total carbon flux estimates. A goal of the project is to ensure that the products are useful to a wide community of scientists, managers, and policy makers, as well as to carbon cycle scientists. Understanding the needs and requirements of these data users is helpful not just to the NASA CMS program but also to the entire community working on carbon-related activities. To that end, this meeting brought together a small group of natural resource managers and policy makers who use information on forests in their work with NASA scientists who are working to create aboveground forest biomass maps. These maps, derived from combining remote sensing and ground plots, aim to be more accurate than current inventory approaches when applied at local and regional scales.

Brown, Molly E.↗

NASA NTRS2011

Sodium Velocity Maps on Mercury

The objective of the current work was to measure two-dimensional maps of sodium velocities on the Mercury surface and examine the maps for evidence of sources or sinks of sodium on the surface. The McMath-Pierce Solar Telescope and the Stellar Spectrograph were used to measure Mercury spectra that were sampled at 7 milliAngstrom intervals. Observations were made each day during the period October 5-9, 2010. The dawn terminator was in view during that time. The velocity shift of the centroid of the Mercury emission line was measured relative to the solar sodium Fraunhofer line corrected for radial velocity of the Earth. The difference between the observed and calculated velocity shift was taken to be the velocity vector of the sodium relative to Earth. For each position of the spectrograph slit, a line of velocities across the planet was measured. Then, the spectrograph slit was stepped over the surface of Mercury at 1 arc second intervals. The position of Mercury was stabilized by an adaptive optics system. The collection of lines were assembled into an images of surface reflection, sodium emission intensities, and Earthward velocities over the surface of Mercury. The velocity map shows patches of higher velocity in the southern hemisphere, suggesting the existence of sodium sources there. The peak earthward velocity occurs in the equatorial region, and extends to the terminator. Since this was a dawn terminator, this might be an indication of dawn evaporation of sodium. Leblanc et al. (2008) have published a velocity map that is similar.

Potter, A. E.↗

NASA NTRS2012

A Near-Infrared and Thermal Imager for Mapping Titan's Surface Features

Approximately 10% of the solar insolation reaches the surface of Titan through atmospheric spectral windows. We will discuss a filter based imaging system for a future Titan orbiter that will exploit these windows mapping surface features, cloud regions, polar storms. In the near-infrared (NIR), two filters (1.28 micrometer and 1.6 micrometer), strategically positioned between CH1 absorption bands, and InSb linear array pixels will explore the solar reflected radiation. We propose to map the mid, infrared (MIR) region with two filters: 9.76 micrometer and 5.88-to-6.06 micrometers with MCT linear arrays. The first will map MIR thermal emission variations due to surface albedo differences in the atmospheric window between gas phase CH3D and C2H4 opacity sources. The latter spans the crossover spectral region where observed radiation transitions from being dominated by thermal emission to solar reflected light component. The passively cooled linear arrays will be incorporated into the focal plane of a light-weight thin film stretched membrane 10 cm telescope. A rad-hard ASIC together with an FPGA will be used for detector pixel readout and detector linear array selection depending on if the field-of-view (FOV) is looking at the day- or night-side of Titan. The instantaneous FOV corresponds to 3.1, 15.6, and 31.2 mrad for the 1, 5, and 10 micrometer channels, respectively. For a 1500 km orbit, a 5 micrometer channel pixel represents a spatial resolution of 91 m, with a FOV that spans 23 kilometers, and Titan is mapped in a push-broom manner as determined by the orbital path. The system mass and power requirements are estimated to be 6 kg and 5 W, respectively. The package is proposed for a polar orbiter with a lifetime matching two Saturn seasons.

Aslam, S.↗

NASA NTRS2014

Potential of Pest and Host Phenological Data in the Attribution of Regional Forest Disturbance Detection Maps According to Causal Agent

Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced since 2010 for the conterminous U.S., as part of the on-line ForWarn national forest threat early warning system. The latter has been used by the forest health community to identify and track many regional forest disturbances caused by multiple biotic and abiotic damage agents. Attribution of causal agents for detected disturbances has been a goal since project initiation in 2006. Combined with detailed cover type maps, geospatial pest phenology data offer a potential means for narrowing the candidate causal agents responsible for a given biotic disturbance. U.S. Aerial Detection Surveys (ADS) employ such phenology data. Historic ADS products provide general locational data on recent insect-induced forest type specific disturbances that may help in determining candidate causal agents for MODIS-based disturbance maps, especially when combined with other historic geospatial disturbance data (e.g., wildfire burn scars and drought maps). Historic ADS disturbance detection polygons can show severe and extensive regional forest disturbances, though they also can show polygons with sparsely scattered or infrequent disturbances. Examples will be discussed that use various historic disturbance data to help determine potential causes of MODIS-detected regional forest disturbance anomalies.

Spruce, Joseph↗

NASA NTRS2013

Preliminary Geological Map of the Peace Vallis Fan Integrated with In Situ Mosaics From the Curiosity Rover, Gale Crater, Mars

A geomorphically defined alluvial fan extends from Peace Vallis on the NW wall of Gale Crater, Mars into the Mars Science Laboratory (MSL) Curiosity rover landing ellipse. Prior to landing, the MSL team mapped the ellipse and surrounding areas, including the Peace Vallis fan. Map relationships suggest that bedded rocks east of the landing site are likely associated with the fan, which led to the decision to send Curiosity east. Curiosity's mast camera (Mastcam) color images are being used to refine local map relationships. Results from regional mapping and the first 100 sols of the mission demonstrate that the area has a rich geological history. Understanding this history will be critical for assessing ancient habitability and potential organic matter preservation at Gale Crater.

Gale Crater↗

NASA NTRS2014

Theoretical Foundations of Remote Sensing for Glacier Assessment and Mapping

The international scientific community is actively engaged in assessing ice sheet and alpine glacier fluctuations at a variety of scales. The availability of stereoscopic, multitemporal, and multispectral satellite imagery from the optical wavelength regions of the electromagnetic spectrum has greatly increased our ability to assess glaciological conditions and map the cryosphere. There are, however, important issues and limitations associated with accurate satellite information extraction and mapping, as well as new opportunities for assessment and mapping that are all rooted in understanding the fundamentals of the radiation transfer cascade. We address the primary radiation transfer components, relate them to glacier dynamics and mapping, and summarize the analytical approaches that permit transformation of spectral variation into thematic and quantitative parameters. We also discuss the integration of satellite-derived information into numerical modeling approaches to facilitate understandings of glacier dynamics and causal mechanisms.

Remote Sensing↗

NASA NTRS2015

Construction of Polarimetric Radar-Based Reference Rain Maps for the Iowa Flood Studies Campaign

The Global Precipitation Measurement (GPM) Mission Iowa Flood Studies (IFloodS) campaign was conducted in central and northeastern Iowa during the months of April-June, 2013. Specific science objectives for IFloodS included quantification of uncertainties in satellite and ground-based estimates of precipitation, 4-D characterization of precipitation physical processes and associated parameters (e.g., size distributions, water contents, types, structure etc.), assessment of the impact of precipitation estimation uncertainty and physical processes on hydrologic predictive skill, and refinement of field observations and data analysis approaches as they pertain to future GPM integrated hydrologic validation and related field studies. In addition to field campaign archival of raw and processed satellite data (including precipitation products), key ground-based platforms such as the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars, University of Iowa X-band dual-polarimetric radars, a large network of paired rain gauge platforms, and a large network of 2D Video and Parsivel disdrometers were deployed. In something of a canonical approach, the radar (NPOL in particular), gauge and disdrometer observational assets were deployed to create a consistent high-quality distributed (time and space sampling) radar-based ground "reference" rainfall dataset, with known uncertainties, that could be used for assessing the satellite-based precipitation products at a range of space/time scales. Subsequently, the impact of uncertainties in the satellite products could be evaluated relative to the ground-benchmark in coupled weather, land-surface and distributed hydrologic modeling frameworks as related to flood prediction. Relative to establishing the ground-based "benchmark", numerous avenues were pursued in the making and verification of IFloodS "reference" dual-polarimetric radar-based rain maps, and this study documents the process and results as they pertain specifically to efforts using the NPOL radar dataset. The initial portions of the "process" involved dual-polarimetric quality control procedures which employed standard phase and correlation-based approaches to removal of clutter and non-meteorological echo. Calculation of a scale-adaptive KDP was accomplished using the method of Wang and Chandrasekar (2009; J. Atmos. Oceanic Tech.). A dual-polarimetric blockage algorithm based on Lang et al. (2009; J. Atmos. Oceanic Tech.) was then implemented to correct radar reflectivity and differential reflectivity at low elevation angles. Next, hydrometeor identification algorithms were run to identify liquid and ice hydrometeors. After the quality control and data preparation steps were completed several different dual-polarimetric rain estimation algorithms were employed to estimate rainfall rates using rainfall scans collected approximately every two to three minutes throughout the campaign. These algorithms included a polarimetrically-tuned Z-R algorithm that adjusts for drop oscillations (via Bringi et al., 2004, J. Atmos. Oceanic Tech.), and several different hybrid polarimetric variable approaches, including one that made use of parameters tuned to IFloodS 2D Video Disdrometer measurements. Finally, a hybrid scan algorithm was designed to merge the rain rate estimates from multiple low level elevation angle scans (where blockages could not be appropriately corrected) in order to create individual low-level rain maps. Individual rain maps at each time step were subsequently accumulated over multiple time scales for comparison to gauge network data. The comparison results and overall error character depended strongly on rain event type, polarimetric estimator applied, and range from the radar. We will present the outcome of these comparisons and their impact on constructing composited "reference" rainfall maps at select time and space scales.

Radar↗

NASA NTRS2016

Geologic Mapping of Ascraeus Mons, Mars

Ascraeus Mons (AM) is the northeastern most large shield volcano residing in the Tharsis province on Mars. We are funded by NASA's Mars Data Analysis Program to complete a digital geologic map based on the mapping style. Previous mapping of a limited area of these volcanoes using HRSC images (13-25 m/pixel) revealed a diverse distribution of volcanic landforms within the calderas, along the flanks, rift aprons, and surrounding plains. The general scientific objectives for which this mapping is based is to show the different lava flow morphologies across AM to better understand the evolution and geologic history.

Volcanoes↗

NASA NTRS2015

Quantifying Mapping Orbit Performance in the Vicinity of Primitive Bodies

Predicting and quantifying the capability of mapping orbits in the vicinity of primitive bodies is challenging given the complex orbit geometries that exist and the irregular shape of the bodies themselves. This paper employs various quantitative metrics to characterize the performance and relative effectiveness of various types of mapping orbits including terminator, quasi-terminator, hovering, pingpong, and conic-like trajectories. Metrics of interest include surface area coverage, lighting conditions, and the variety of viewing angles achieved. The metrics discussed in this investigation are intended to enable mission designers and project stakeholders to better characterize candidate mapping orbits during preliminary mission formulation activities.The goal of this investigation is to understand the trade space associated with carrying out remotesensing campaigns at small primitive bodies in the context of a robotic space mission. Specifically,this study seeks to understand the surface viewing geometries, ranges, etc. that are available fromseveral commonly proposed mapping orbits architectures.

Pavlak, Thomas A.↗

NASA NTRS2017

Daily Kilometer-Scale MODIS Satellite Maps of PM2.5 Describe Wintertime Episodes

The San Joaquin Valley (SJV) suffers from severe health-endangering episodes of PM2.5 aerosol loadings in wintertime; episodes last approximately 5 days and differ in geographical distribution and composition. PM2.5 stations are scattered; consequently the use of remote sensing to map variable regional patterns of these varying respirable aerosol concentrations is desirable. High-precision AOT retrievals can capture column particulate loading. However,PM2.5 mapping is challenging due to several reasons: particularly thin mixed layers (ML) and thus relatively low aerosol optical thickness (AOT) close to current measurement limits, variable and a typical composition of the aerosols, and complex surface bidirectional reflectance. However, the West does present some advantages in analysis. Air basins are isolated from long-distance transport, and experience predominant strong meteorological subsidence. Thus these Western basin regions have fewer problematic cases of overriding aerosol layers detached from the surface. To counter such local overriding, Chu et al. have described an approach for the Eastern US, and He et al have described a synoptic classification approach useful in Shanghai. The Bay Area Air Quality Management District (BAAQMD) expands our experience with the use of AOT, with lower PM2.5 and several isolated sub-basins. We have prepared daily maps of episodes in each region. We present also a sequence of increasingly detailed statistical models, AOT initially appears to contribute little information; however, inclusion of weather information reveals its utility. Lyapustin and Wang's MultiAngle Implementation of Atmospheric Correction (MAIAC) retrieval for AOT provided the most useful operational remote sensing information for these regions. It provides high (1-km) spatial resolution maps and a high percentage of availability. Empirical regression methods have found that random effects regression models (aka mixed effects models, ME) employing AOT provide good estimates of ground PM2.5 concentrations.Here, we attempt to extend these methods and evaluate the usefulness of AOT with greater physical analysis, based on DISCOVER-AQ4 experience.

Chatfield, Robert B.↗

NASA NTRS2016

Erasing the Milky Way: New Cleaning Technique Applied to GBT Intensity Mapping Data

We present the first application of a new foreground removal pipeline to the current leading HI intensity mapping dataset, obtained by the Green Bank Telescope (GBT). We study the 15- and 1-h field data of the GBT observations previously presented in Masui et al. (2013) and Switzer et al. (2013), covering about 41 square degrees at 0.6 less than z is less than 1.0, for which cross-correlations may be measured with the galaxy distribution of the WiggleZ Dark Energy Survey. In the presented pipeline, we subtract the Galactic foreground continuum and the point source contamination using an independent component analysis technique (fastica), and develop a Fourier-based optimal estimator to compute the temperature power spectrum of the intensity maps and cross-correlation with the galaxy survey data. We show that fastica is a reliable tool to subtract diffuse and point-source emission through the non-Gaussian nature of their probability distributions. The temperature power spectra of the intensity maps is dominated by instrumental noise on small scales which fastica, as a conservative sub-traction technique of non-Gaussian signals, can not mitigate. However, we determine similar GBT-WiggleZ cross-correlation measurements to those obtained by the Singular Value Decomposition (SVD) method, and confirm that foreground subtraction with fastica is robust against 21cm signal loss, as seen by the converged amplitude of these cross-correlation measurements. We conclude that SVD and fastica are complementary methods to investigate the foregrounds and noise systematics present in intensity mapping datasets.

Wolz, L.↗

NASA NTRS2015

Quantifying Mapping Orbit Performance in the Vicinity of Primitive Bodies

Predicting and quantifying the capability of mapping orbits in the vicinity of primitive bodies is challenging given the complex orbit geometries that exist and the irregular shape of the bodies themselves. This paper employs various quantitative metrics to characterize the performance and relative effectiveness of various types of mapping orbits including terminator, quasi-terminator, hovering, ping pong, and conic-like trajectories. Metrics of interest include surface area coverage, lighting conditions, and the variety of viewing angles achieved. The metrics discussed in this investigation are intended to enable mission designers and project stakeholders to better characterize candidate mapping orbits during preliminary mission formulation activities. The goal of this investigation is to understand the trade space associated with carrying out remote sensing campaigns at small primitive bodies in the context of a robotic space mission. Specifically, this study seeks to understand the surface viewing geometries, ranges, etc. that are available from several commonly proposed mapping orbits architectures

Pavlak, Thomas A.↗

NASA NTRS2017

HOTEX: An Approach for Global Mapping of Human Built-Up and Settlement Extent

Understanding the impacts of urbanization requires accurate and updatable urban extent maps. Here we present an algorithm for mapping urban extent at global scale using Landsat data. An innovative hierarchical object-based texture (HOTex) classification approach was designed to overcome spectral confusion between urban and nonurban land cover types. VIIRS nightlights data and MODIS vegetation index datasets are integrated as high-level features under an object-based framework. We applied the HOTex method to the GLS-2010 Landsat images to produce a global map of human built-up and settlement extent. As shown by visual assessments, our method could effectively map urban extent and generate consistent results using images with inconsistent acquisition time and vegetation phenology. Using scene-level cross validation for results in Europe, we assessed the performance of HOTex and achieved a kappa coefficient of 0.91, compared to 0.74 from a baseline method using per-pixel classification using spectral information.

Wang, Panshi↗

NASA NTRS2018

Quantitative Daily Maps of PM 2.5 Episodes for California and Other Regions: Satellite Column Water and Optical Depth as Allied Tracers of Dilution

The Western US and many regions globally present daunting difficulties in understanding PM 2.5 episodes. We evaluate extensions of a method independent of modeled source-description and transport/transformation and using several satellite remote sensing products from imaging spectrometers. The San Joaquin Valley (SJV) especially suffers few-day episodes due to shallow mixing; PM 2.5 retrieval suffers low satellite AOT (Aerosol Optical Thickness) and bright surfaces.Nevertheless, we find residual errors in our maps of of typically 5-8 micrograms per cubic meter. Episodes in the Valley reaching 60-100 micrograms per cubic meter. These maps detail pollution from Interstate 5 at the scale of a few kilometers. The maps are based on NASA's MODerate resolution Imaging Spectrometer (MODIS) data at circa 1 kilometer as processed with the Multi-Angle Implementation of Atmospheric Correction. The Bay Area Air Quality Management District has requested that we test our methods in their challenging environment characterized by multiple sub-basins defined by complex topography. Our tests suggest that nearly similar precision may be expected for wintertime conditions with high PM 2.5 . We note difficulties when measured PM 2.5 is less than 8-10 micrograms per cubic meter, but good relative precision when PM 2.5 rises above 20; i.e. in episodes of concern for morbidity and mortality. Our method stresses physically meaningful functions of MODIS-MAIAC (Multi-Angle Implementation of Atmospheric Correction)-derived AOD (Aerosol Optical Depth) and total water vapor column. A mixed-effects statistical model exploiting existing station data works powerfully to allow us daily AOT-to-PM 2.5 relationships that allow a calibration of the map. In those cases where water vapor and particles have generally similar surface sources, using the ratio of AOT / Column_water can improve the daily calibrations so as to reach our quoted precision. We briefly present some cartoon idealizations that explain this success and also the likely reasons that our mixed effects model (or "daily calibration") works; also when it should not work. The combined satellite/mixed-effects model works best for wintertime San Joaquin Valley episodes, where the meteorology of particle and H2O(v) dilution is quite appropriate. We extended and tested the methodology (a) for the Bay Area wintertime situations and (b) for smoke plume events (e.g. the October 2017 fire events of the Sonoma area). Our SJV work was evaluated using NASA's DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) airborne measurements, and by season- long measurements in Fresno. If the composition and size distribution of the aerosols can be assessed for the regions we describe, retrievals should have improved accuracy.

Chatfield, Robert B.↗

NASA NTRS2018

Quantifying the Early Snowmelt Event of 2015 in the Cascade Mountains, USA by Developing and Validating MODIS-Based Snowmelt Timing Maps

Spring snowmelt serves as the major hydrological contribution to many watersheds of the US West. Since the 1970s the conterminous western USA has seen an earlier arrival of spring snowmelt. The extremely low snowpack and early melt of 2015 in the Cascade Mountains may be a harbinger of winters to come, underscoring the interest in advancements in spring snowmelt monitoring. Target-of-opportunity and point measurements of snowmelt using meteorological stations or stream gauges are common sources of these data, however, there have been few attempts to identify snowmelt timing using remote sensing. In this study, we describe the creation of snowmelt timing maps (STMs) which identify the day of year that each pixel of a remotely sensed image transitions from "snow-covered" to "no snow" during the spring melt season, controlling for cloud coverage and ephemeral spring snow storms. Derived from the 500 meter MODerate-resolution Imaging Spectroradiometer (MODIS) standard snow map, MOD10A2, this new dataset provides annual maps of snowmelt timing, with corresponding maps of cloud interference and interannual variability in snow coverage from 2001-2015. We first show that the STMs agree strongly with in-situ snow telemetry (SNOTEL) meteorological station measurements in terms of snowmelt timing. We then use the STMs to investigate the early snowmelt event of 2015 in the Cascade Mountains, USA, highlighting the protected areas of Mt. Rainier, Crater Lake, and Lassen Volcanic National Parks. In 2015 the Cascade Mountains experienced snowmelt 41 days earlier than the 2001-2015 average, with 25 percent of its land area melting more than 65 days earlier than average. The upper elevations of the Cascade Mountains experienced the greatest snowmelt anomaly. Our results are relevant to land managers and biologists as they plan adaptation strategies for mitigating the effects of climate change throughout temperate mountains.

snowmelt timing↗

NASA NTRS2018

Landslide Mapping Along the Karnali Highway, Nepal using High-Resolution Imagery

The Karnali highway (Figure 1) is the only major transportation link that connects the remote Karnali region to the provincial capital in Province 6 of Nepal. This area becomes inaccessible by roads during every rainy season due to landslides. Despite the known landslide frequency, there have been no systematic landslide inventories conducted along this highway to date. Recent advancements in remote-sensing technologies have significantly increased our ability to map landslides of various sizes rapidly with less in situ surveys or human interaction. Landslide susceptibility, hazard and risk studies require a complete landslide inventory, which might only be possible from very high-resolution (VHR) and high-resolution (HR) imagery. Recent launch of Sentinel-2 in 2015 has provided free access to HR imagery enabling landslide detection at finer scales then what was possible with previous open source satellite imagery obtained from Landsat and ASTER. Satellites providing VHR imagery are commercially owned, expensive and not freely available expect for when disasters charter is activated. NextView licensing agreement, a partnership between the US government and US commercial vendors provides access to VHR imagery to federal agencies in support of scientific research [1]. This partnership provides access to VHR imagery obtained from the DigitalGlobe (DG) constellation which enables mapping of small landslides (< 100 m2). In this study, VHR imagery from DG and HR imagery from Sentinel-2 will be used to map landslides along the Karnali highway using a semi automatic method based on object-oriented analysis (OOA) to create most recent and up-to-date landslide inventory. The effectiveness of this remote sensing based landslide inventory to produce a susceptibility map and its predictive capacity will be tested.

landslide↗

NASA NTRS2019

Simultaneous Localization and Mapping for Satellite Rendezvous and Proximity Operations Using Random Finite Sets

Future space missions require that spacecraft have the capability to autonomously navigate non-cooperative environments for rendezvous and proximity operations (RPO). Current relative navigation filters can have difficulty in these situations, diverging due to complications with data association, high measurement uncertainty, and clutter, particularly when detailed a priori maps of the target object or spacecraft do not exist. The goal of this work is to demonstrate the feasibility of random finite set (RFS) filters for spacecraft relative navigation and pose estimation. The approach is to formulate satellite relative navigation and pose estimation as a simultaneous localization and mapping (SLAM) problem, in which an observer spacecraft seeks to simultaneously estimate the location of features on a target object or spacecraft as well as its relative position, velocity and attitude. This work utilizes a filter developed using the framework of RFS which are well suited to multi-target SLAM operations, avoiding data association entirely. Relevant RPO scenarios with simulated flash LIDAR measurements are tested with a Probability Hypothesis Density (PHD) RFS filter embedded in a particle filter to obtain a feature map of a target and a relative pose estimate between the target and observer. Preliminary results show that an RFS-based filter can successfully perform SLAM in a spacecraft relative navigation scenario with no a priori map of the target. These results demonstrate the feasibility of RFS filtering for spacecraft relative navigation and motivate future studies which may expand to tracking space objects for space situational awareness, as well as relative navigation around small bodies.

Schlenker, Lauren↗