Autonomous navigation for Deep Space Missions
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Engineering topics
Publications and source records attributed to Bhaskaran, Shyam.
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On July 4, 2005 at 05:44:34.2 UTC the Impactor Spacecraft (s/c) impacted comet Tempel 1 with a relative speed of 10.3 km/s capturing high-resolution images of the surface of a cometary nucleus just seconds before impact. Meanwhile, the Flyby s/c captured the impact event using both the Medium Resolution Imager (MRI) and the High Resolution Imager (HRI) and tracked the nucleus for the entire 800 sec period between impact and shield attitude transition. The objective of the Impactor s/c was to impact in an illuminated area viewable from the Flyby s/c and capture high-resolution context images of the impact site. This was accomplished by using autonomous navigation (AutoNav) algorithms and precise attitude information from the attitude determination and control subsystem (ADCS). The Flyby s/c had two primary objectives: 1) capture the impact event with the highest temporal resolution possible in order to observe the ejecta plume expansion dynamics; and 2) track the impact site for at least 800 sec to observe the crater formation and capture the highest resolution images possible of the fully developed crater. These two objectives were met by estimating the Flyby s/c trajectory relative to Tempel 1 using the same AutoNav algorithms along with precise attitude information from ADCS and independently selecting the best impact site. This paper describes the AutoNav system, what happened during the encounter with Tempel 1 and what could have happened.
This paper reviews the tentative set of deep space missions that will be supported by NASA's Deep Space Mission System in the next twenty-five years, and extracts the driving set of navigation capabilities that these missions will require. There will be many challenges including the support of new mission navigation approaches such as formation flying and rendezvous in deep space, low-energy and low-thrust orbit transfers, precise landing and ascent vehicles, and autonomous navigation. Innovative strategies and approaches will be needed to develop and field advanced navigation capabilities.
Mars Reconnaissance Orbiter will launch in August 2005 at Cape Canaveral Air Force Station. The heavyweight spacecraft will use a Lockheed-Martin Atlas V-401 launch vehicle. It will be the first mission in a low Mars Orbit to characterize the surface, subsurface, and atmospheric properties. The intensive science operation imposes a great challenge for Navigation to satisfy the stringent requirements. This paper describes navigation key requirements, major challenges, and the sophisticated dynamic modeling. It also details navigation strategy and processes for various mission phases. Mars Reconnaissance Orbiter will return significant amount of scientific data in support of the objectives set by the Mars Exploration Program. A robust and precise navigation is the key to the success of this mission.
Spacecraft flybys of small solar system bodies provide important science return in the form of images of the target body taken around closest approach. In order to maximize the number of images taken of the target, an autonomous closed-loop tracking system has been developed to maintain lock on the target during the flyby. The system uses images to estimate the spacecrafts target-relative position and attitude, which is then used to point the camera. The system has been successfully used twice: the Deep Space 1 flyby of comet Borrelly and the Stardust flyby of asteroid Annefrank. This paper describes in detail the tracking algorithms and flight results.
Several options are being examined to reduce the costs of spacecraft and deep space missions. One such option is to fly spacecraft in a non-coherent mode, that is, the spacecraft does not carry a transponder and cannot coherently return a Doppler signal. Historically, such one-way data has not been used as the sole data type due to the instability of the onboard oscillator, the use of S-band frequencies, and the corresponding larger error sources which could not be modeled. However, with the advent of high-speed work stations and more sophisticated modeling ability, the possibility of using one-way data is being re-examined. This paper addresses the navigation performance of various one-way data types for use in interplanetary missions.
Recent improvements in computational capability and Deep Space Network technology have renewed interest in examining the possibility of using one-way Doppler data alone to navigate interplanetary spacecraft. The one-way data can be formulated as the standard differenced-count Doppler or as phase measurements, and the data can be received at a single station or differenced if obtained simultaneously at two stations. A covariance analysis is performed which analyzes the accuracy obtainable by combinations of one-way Doppler data and compared with similar results using standard two-way Doppler and range. The sample interplanetary trajectory used was that of the Mars Pathfinder mission to Mars. It is shown that differenced one-way data is capable of determining the angular position of the spacecraft to fairly high accuracy, but has relatively poor sensitivity to the range. When combined with single station data, the position dispersions are roughly an order of magnitude larger in range and comparable in angular position as compared to dispersions obtained with standard data two-way types. It was also found that the phase formulation is less sensitive to data weight variations and data coverage than the differenced-count Doppler formulation.
Satellite altimetry was used to examine annual and interannual variability in the Gulf of Alaska region. Crossover data from the Geosat Geodetic Mission (GM) and collinear data from the Exact Repeat Mission (ERM) were processed separately to form sea surface height anomalies at grid points. The time series from the GM and ERM were then combined to produce a 3.75-year data set. The time series from the ERM data set agreed fairly well with hydrographic dynamic heights at several locations, with an average correlation of 0.70 between the two data sets. The combined and ERM altimetric data sets were analyzed using empirical orthogonal functions (EOFs). These revealed variability that occurs primarily on annual and interannual time scales. A comparison with EOF analysis of the atmospheric pressure field during the same time periods showed that the annual variation in pressure seemed to be reflected in both the combined and ERM altimetric data sets. The amplitude time series of the first mode in the combined data set was very similar to the North Pacific pressure index during the 1985-1989 time frame. The maximum correlation was at a lag of 250 days. Finally, an interannual mode was present in all three data sets which was closely linked to the baroclinic variations measured by the hydrographic data.