Engineering topics
Owen, William M.
Publications and source records attributed to Owen, William M..
High accuracy ground-based near-Earth-asteroid astrometry using synthetic tracking
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The Deep-Space Positioning System Concept: Automating Complex Navigation Operations Beyond the Earth
There is no equivalent of GPS in “deep space,” that is beyond the Earth Moon system (and use of GPS beyond LEO and MEO is already problematic.) NASA has been awarded a patent on the concept of the “Deep-space Positioning System” (DPS) which is a self-contained instrument concept that would use in-situ observations to provide an automated and autonomous means of determining its position in the Solar System, and at least as important, its position relative to a target, whether that target is a planet, asteroid, moon or comet. In addition, the DPS system computes trajectory change parameters, as necessary to keep a spacecraft on a planned trajectory. Implementation options include the use of a radio receiver to receive a frequency beacon from a non-in-situ source for additional navigation information over and above that which can be provided by the cameras that are the principal data source of DPS. This paper discusses the DPS instrument concept, and its potential use in deep space.
Trajectory Reconstruction of the ST-9 Sounding Rocket Experiment Using IMU and Landmark Data
This paper presents trajectory reconstruction of the ST-9 sounding rocket experiment using the onboard IMU data and descent imagery. The raw IMU accelerometer measurements are first converted into inertial acceleration and then used in trajectory integration. The descent images are pre-processed using a map-matching algorithm and unique landmarks for each image are created. Using the converted IMU data and descent images, the result from dead-reckoning and the kinematic-fix approaches are first compared with the GPS measurements. Then, both the IMU data and landmarks are processed together using a batch least-squares filter and the position, velocity, stochastic acceleration, and camera orientation of each image are estimated. The reconstructed trajectory is compared with the GPS data and the corresponding formal uncertainties are presented. The result shows that IMU data and descent images processed with a batch filter algorithm provide the trajectory accuracy required for pin-point landing.