Search NASASearch

NASA NTRS · 20210003832

A Grid Algorithm for Autonomous Star Identification

Abstract

An autonomous star identification algorithm is described that is simple and requires less computer resources than other such algorithms.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Dreutz-Delgado, Kenneth, Padgett, Curtis. 1996-01-01. A Grid Algorithm for Autonomous Star Identification. https://ntrs.nasa.gov/citations/20210003832

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Realization of a Faster, Cheaper, Better Star Tracker for the New Millennium

The first Danish satellite, إrsted, will be launched in August of 1997. The scientific objective of إrsted is to perform a precision mapping of the Earth's magnetic field. Attitude data for the payload and the satellite are provided by the Advanced Stellar Compass (ASC) star tracker. The ASC consists of a CCD star camera and a capable microprocessor which operates by comparing the star image frames taken by the camera to its internal star catalogs.

star

Cassini Stellar Reference Unit: Performance Test Approach and Results

The Cassini Stellar Reference Unit (SRU) is the prime attitude determination sensor on the Cassini spacecraft...To ensure that the SRU will operate within specification for the entire mission, an extensive test program has been undertaken to characterize the SRU performance prior to launch and to quantify any expected performance degradation. Results from several eomplimentary test programs are presented and compared with pre-test performance predictions.

star

Evaluation of Star Identification Techniques

A number of different strategies are used or have been suggested for identifying star fields atitude determination in space. We offer a general classification of the existing techniques and select three representative algorithms for more comprehensive evaluation. In addition, we describe a software simulation environment we developed for the design, paramter determination, and evaluation of star identification algorithms. The identification rates and performance on the three algorithms are presented over a variety of noise conditions using two different sized onboard catalogs.

star