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At least 19 records

DSMS investment in support of satellite constellations and formation flying

Over the years, NASA has supported unmanned space missions, beyond earth orbit, through a Deep Space Mission System (DSMS) that is developed and operated by the Jet Propulsion Laboratory (JPL) and subcontractors. The DSMS capabilities have been incrementally upgraded since its establishment in the late '50s and are delivered primarily through three Deep Space Communications Complexes (DSCC 's) near Goldstone, California, Madrid, Spain, and Canberra, Australia and from facilities at JPL. Traditionally, mission support (tracking, command, telemetry, etc) is assigned on an individual-mission basis, between each mission and a ground-based asset, independent of other missions. As NASA, and its international partners, move toward flying fullconstellations and precision formations, the DSMS is developing plans and technologies to provide the requisite support. The key activities under way are: (1) integrated communications architecture for Mars exploration, including relays on science orbiters and dedicated relay satellites to provide continuous coverage for orbiters, landers and rovers. JPL is developing an architecture, as well as protocols and equipment, required for the cost-effective operations of such an infrastructure. (2) Internet-type protocols that will allow for efficient operations across the deep-space distances, accounting for and accommodating the long round-trip-light-time. JPL is working with the CCSDS to convert these protocols to an international standard and will deploy such protocol, the CCSDS File Delivery Protocol (CFDP), on the Mars Reconnaissance Orbiter (MRO) and on the Deep Impact (01) missions. (3) Techniques to perform cross-navigation between spacecrafi that fly in a loose formation. Typical cases are cross-navigation between missions that approach Mars and missionsthat are at Mars, or the determination of a baseline for missions that fly in an earth-lead- lag configuration. (4) Techniques and devices that allow the precise metrology and controllability of tightformations for precision constellation missions. In this paper we discuss the four classes of constellatiodformation support with emphasis of DSMS current status (technology and implementation) and plans in the first three areas.

space operations

DSMS science operations concept

The Deep Space Mission System (DSMS) Science Operations Concept describes the vision for enabling the use of the DSMS, particularly the Deep Space Network (DSN) for direct science observations in the areas of radio astronomy, planetary radar, radio science and VLBI.

deep space science

Control Architecture for the Deep Space Mission System (DSMS)

As NASA moves int an era of flying more missions at much lower cost and shorter development duration, the Deep Space Mission System (DSMS) has been redesigned to provide services to approximately 50 missions during the next 10 years.

architecture Deep Space Mission

DSMS Services and Capabilities

This viewgraph presentation reviews Interplanetary Network Directorate Deep Space Mission Systems services and support capabilities. The contents include: 1) Organization Chart; 2) IND DSMS Support Facilities; 3) Standard Services; and 4) Support Capabilities including Telemetry, command and tracking.

communications

DSMS Operations Concept

The concept provides an overview of operational roles and responsibilities in a service system environment. It describes changed and new interfaces between the customers and the service system, and variations on these interfaces as a function of the level of support required by the customer.

DSMS Operations Deep Space Mission Systems telecom

Boreal canopy surfaces from spaceborne stereogrammetry

Surface elevation estimates from high resolution spaceborne image (HRSI) stereogrammetry are used to examine fine-scaled structure of boreal forest canopies. These data can depict detailed spatial patterns of vertical forest structure at remote sites across the circumpolar domain where these estimates would otherwise be unavailable. This work examines where these estimates are most effective at describing vertical forest structure to explain which canopy surfaces they represent. We evaluated the variation in canopy surface estimates captured from four general types of HRSI digital surface models (DSMs) across the full range of boreal canopy cover. These DSMs, classified into 4 types by grouping them according to the acquisition's (1) sun elevation angle (low or high) and (2) seasonality-driven ground surface condition (snow presence/absence), vary with acquisition characteristics and the details of this variation continues to be studied. We explored some of this variation by comparing the distributions of differences in boreal canopy percentile heights derived from reference small footprint lidar in Tanana Valley, Alaska with canopy surface elevations derived from these 4 types of HRSI DSMs. We examined how canopy surface estimates from HRSI DSMs differ according to acquisition characteristics and canopy cover, and ultimately which canopy surfaces are represented in these DSMs. Our results help clarify which boreal canopy surfaces are representative of those captured with HRSI DSMs. They show that in the Tanana Valley (1) DSMs grouped by sun elevation angle and ground surface condition provide different surface estimates of boreal canopies; (2) the two DSM types that appear to most differently capture boreal forest canopy surfaces are DSMs from snow-free images acquired at sun elevation angles <30° (Low sun elev. & snow-free) and those with snow-cover at sun elevation angles ≥30° (High sun elev. & snow-free); (3) DSMs with snow most often do not capture upper canopy surfaces; (4) the “Low sun elev. & snow-free” DSMs resolve surfaces that are most representative of upper canopy surfaces (dense forests >60% cover, 70th–80th percentile heights); and (5) in the most dense forests (>80% cover) where canopy gaps are least likely to bias downward the average surface estimates, the snow-free DSM types are representative of 70th - 80th percentile heights (“Low sun elev. & snow-free”) and 60th–70th percentile heights (“High sun elev. & snow-free”). The combination of horizontal structure (canopy cover) and acquisition characteristics affect the boreal vertical structure (canopy surface height) estimates from spaceborne stereogrammetry. These effects should be considered when analyzing products derived from HRSI DSMs, and as part of a comprehensive approach to spaceborne remote sensing of circumpolar boreal forests.

forest structure

The Use of Sun Elevation Angle for Stereogrammetric Boreal Forest Height in Open Canopies

Stereogrammetry applied to globally available high resolution spaceborne imagery (HRSI; less than 5 m spatial resolution) yields fine-scaled digital surface models (DSMs) of elevation. These DSMs may represent elevations that range from the ground to the vegetation canopy surface, are produced from stereoscopic image pairs (stereo pairs) that have a variety of acquisition characteristics, and have been coupled with lidar data of forest structure and ground surface elevation to examine forest height. This work explores surface elevations from HRSI DSMs derived from two types of acquisitions in open canopy forests. We (1) apply an automated mass-production stereogrammetry workflow to along-track HRSI stereo pairs, (2) identify multiple spatially coincident DSMs whose stereo pairs were acquired under different solar geometry, (3) vertically co-register these DSMs using coincident spaceborne lidar footprints (from ICESat-GLAS) as reference, and(4) examine differences in surface elevations between the reference lidar and the co-registered HRSI DSMs associated with two general types of acquisitions (DSM types) from different sun elevation angles. We find that these DSM types, distinguished by sun elevation angle at the time of stereo pair acquisition, are associated with different surface elevations estimated from automated stereogrammetry in open canopy forests. For DSM values with corresponding reference ground surface elevation from spaceborne lidar footprints in open canopy northern Siberian Larix forests with slopes less than10, our results show that HRSI DSM acquired with sun elevation angles greater than 35deg and less than 25deg (during snow-free conditions) produced characteristic and consistently distinct distributions of elevation differences from reference lidar. The former include DSMs of near-ground surfaces with root mean square errors less than 0.68 m relative to lidar. The latter, particularly those with angles less than 10deg, show distributions with larger differences from lidar that are associated with open canopy forests whose vegetation surface elevations are captured. Terrain aspect did not have a strong effect on the distribution of vegetation surfaces. Using the two DSM types together, the distribution of DSM-differenced heights in forests (6.0 m, sigma = 1.4 m) was consistent with the distribution of plot-level mean tree heights (6.5m, sigma = 1.2 m). We conclude that the variation in sun elevation angle at time of stereo pair acquisition can create illumination conditions conducive for capturing elevations of surfaces either near the ground or associated with vegetation canopy. Knowledge of HRSI acquisition solar geometry and snow cover can be used to understand and combine stereogrammetric surface elevation estimates to co-register rand difference overlapping DSMs, providing a means to map forest height at fine scales, resolving the vertical structure of groups of trees from spaceborne platforms in open canopy forests.

Paul M Montesano

High-Resolution Forest Canopy Height Estimation in an African Blue Carbon Ecosystem

Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereophotogrammetric techniques on high-resolution spaceborne imagery (HRSI) for southern Mozambique. A mean-weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18-1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three-dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications.

HRSI

Deciphering the Precision of Stereo IKONOS Canopy Height Models for U.S. Forests with G-LiHT Airborne LiDAR

Few studies have evaluated the precision of IKONOS stereo data for measuring forest canopy height. The high cost of airborne light detection and ranging (LiDAR) data collection for large area studies and the present lack of a spaceborne instrument lead to the need to explore other low cost options. The US Government currently has access to a large archive of commercial high-resolution imagery, which could be quite valuable to forest structure studies. At 1 m resolution, we here compared canopy height models (CHMs) and height data derived from Goddard's airborne LiDAR Hyper-spectral and Thermal Imager (G-LiHT) with three types of IKONOS stereo derived digital surface models (DSMs) that estimate CHMs by subtracting National Elevation Data (NED) digital terrain models (DTMs). We found the following in three different forested regions of the US after excluding heterogeneous and disturbed forest samples: (1) G-LiHT DTMs were highly correlated with NED DTMs with R (sup 2) greater than 0.98 and root mean square errors (RMSEs) less than 2.96 m; (2) when using one visually identifiable ground control point (GCP) from NED, G-LiHT DSMs and IKONOS DSMs had R (sup 2) greater than 0.84 and RMSEs of 2.7 to 4.1 m; and (3) one GCP CHMs for two study sites had R (sup 2) greater than 0.7 and RMSEs of 2.6 to 3 m where data were collected less than four years apart. Our results suggest that IKONOS stereo data are a useful LiDAR alternative where high-quality DTMs are available.

IKONOS

Packaging data products using data grid middleware for Deep Space Mission Systems

We are investigating a distributed computing infrastructure for releasing science products out of the mission pipeline. We are creating a DSMS Product Service and DSMS Data Packaging Service based on the OODT middleware, a Data Grid middleware technology that has proven successful in providing access to heterogeneous, disparate data, and federating that data using a common data model.

Deep Space Mission Systems

Knowledge Base for Distributed Spacecraft Mission Design Using the Trade-Space Analysis Tool for Constellations (TAT-C)

Opportunities for multi-point measurements, greater revisit frequency, failure robustness, and improved cost effectiveness motivate consideration of Distributed Spacecraft Missions (DSMs) for future Earth science missions. However, careful analysis is required to assess the distributed sensing capabilities of a constellation compared to more mature monolithic spacecraft while also considering other important dimensions such as cost and risk. The large combinatorial DSM design space limits existing mission analysis tools and exploration methods which emphasize monolithic design variables. The Trade-space Analysis Tool for Constellations (TAT-C) under development at Goddard seeks to enumerate and evaluate alternative mission architectures to minimize cost and maximize scientific return for pre-defined goals during pre-phase A analysis.Similar to other model-centric engineering efforts, efficient data management is a significant challenge for DSM mission analysis. In TAT-C, a Knowledge Base (KB) is envisioned as a cumulative central repository of information and meta-information about DSMs. Initial KB concepts store related data for reuse within or across mission analyses; however, over time, the KB is envisioned to be an important layer to coordinate actions of both human analysts and automated design agents to search a large design space for desirable mission alternatives. Preliminary KB research builds on a modern web technology stack to provide the following functionality: 1) storage of trade-space search requests which set requirements and constraints for DSM concepts, 2) storage of analysis results which quantify performance metrics for evaluated DSM concepts, 3) a RESTful application programming interface (API) for scripted access to data from TAT-C modules, 4) web-based graphical user interface (GUI) for manual access to underlying data, and 5) access control and management restrictions relevant to data protection and security. These efforts have culminated in a prototype KB used by the research team during TAT-C development to assess opportunities for future work.

Pattern Recognition

Evaluating Expected Performance and Graceful Degradation in Distributed Spacecraft Missions

Distributed Spacecraft Missions (DSMs) have largely garnered interest due to lower cost and new technical capabilities. However, another important attribute in DSMs is the potential of graceful degradation where a failure of one or more spacecraft (or instruments) in the DSM can reduce total performance, but the remaining functional spacecraft can maintain a limited science return. The potential for retaining some mission value in the event of partial failures leads to enhanced lifetime value. Here, an approach is developed to analyze graceful degradation and performance of DSM used for Earth observation. The system performance is defined through metrics of coverage and average revisit time of points of interest. Graceful degradation is quantified through total change and rate of change in performance metrics with increasing sub-system failures over the lifetime of a mission. An Expected Performance measure is formulated for conducting comparison of DSM architectures for early stage conceptual mission design and trade studies.

Distributed Spacecraft Missions