Accession Number : ADA052747
Title : Global Positioning System Navigation Algorithms
Descriptive Note : Final rept. 1 Apr 1976-31 Aug 1977
Corporate Author : TEXAS UNIV AT AUSTIN APPLIED MECHANICS RESEARCH LAB
Personal Author(s) : Kruczynski, Leonard R.
Full Text : http://www.dtic.mil/get-tr-doc/pdf?AD=ADA052747
Report Date : MAY 1977
Pagination or Media Count : 331
Abstract : The Global Positioning System (GPS) will be a constellation of 24 satellites placed in 12-hour, 63 degree inclination, circular orbits. The satellite configuration is designed to provide accurate three-dimensional position, velocity, and time information by transmitting signals from which users can extract range and range-rate measurements. This investigation describes the passive-ranging concept of the system and the various hardware, software, and environmental factors which determine system accuracy. The simulation of a New York-to-Chicago aircraft flight with satellite range and range-rate measurements and with barometric altimeter measurements is used to numerically evaluate navigation algorithms. The satellite configuration used in the simulation is the limited operational configuration which consists of only nine satellites. For 95 percent of the simulated flight, only three satellites are visible to the user. The search for acceptable navigation algorithms begins with a review of a linear filtering and prediction theory. A filter model for the aircraft is developed based on the assumption of an exponentially correlated random acceleration. The resulting model, combined with measurement bias models, is incorporated into an extended Kalman filter. Numerical results show that, for the basic filter model, filters which maintain good accuracy during the maneuvering phases of flight have poor performance during cruising flight, and conversely, filters which perform well during cruise, have degraded accuracy during maneuvers.
Descriptors : *GLOBAL POSITIONING SYSTEM , *ALGORITHMS , MATHEMATICAL PREDICTION , NAVIGATION SATELLITES , LOW COSTS , KALMAN FILTERING
Subject Categories : THEORETICAL MATHEMATICS
Distribution Statement : APPROVED FOR PUBLIC RELEASE