This research is aimed at improving the state of the art of GPS
algorithms, namely, the development of a closed-form positioning
algorithm for a stand-alone user and the development of a novel
differential GPS algorithm for a network of users. The stand-alone
user GPS algorithm is a direct, closed-form, and efficient new
position determination algorithm that exploits the closed-form
solution of the GPS trilateration equations and works in the
presence of pseudorange measurement noise for an arbitrary number
of satellites in view. A two-step GPS position determination
algorithm is derived which entails the solution of a linear
regression and updates the solution based on one nonlinear
measurement equation. In this algorithm, only two or three
iterations are required as opposed to five iterations that are
normally required in the standard Iterative Least Squares (ILS)
algorithm currently used. The mathematically derived stochastic
model-based solution algorithm for the GPS pseudorange equations is
also assessed and compared to the conventional ILS algorithm. Good
estimation performance is achieved, even under high Geometric
Dilution of Precision (GDOP) conditions. The novel differential GPS
algorithm for a network of users that has been developed in this
research uses a Kinematic Differential Global Positioning System
(KDGPS) approach. A network of mobile receivers is considered, one
of which will be designated the 'reference station' which will have
known position and velocity information at the beginning of the
time interval being examined. The measurement situation on hand is
properly modeled, and a centralized estimation algorithm processing
several epochs of data is developed.
General
| Imprint: |
Biblioscholar
|
| Country of origin: |
United States |
| Release date: |
November 2012 |
| First published: |
November 2012 |
| Authors: |
Thao Q. Nguyen
|
| Dimensions: |
246 x 189 x 6mm (L x W x T) |
| Format: |
Paperback - Trade
|
| Pages: |
118 |
| ISBN-13: |
978-1-288-31107-1 |
| Categories: |
Books >
Social sciences >
Education >
General
|
| LSN: |
1-288-31107-9 |
| Barcode: |
9781288311071 |
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