Name
Abstract | ||
|---|---|---|
Detecting and processing Global Navigation Satellite System (GNSS) signals indoors and in urban canyons, have gained a great deal of attention due to the problems of very weak signals and hostile environments. The detection of GNSS signals is generally based on the application of a statistical test, derived from the maximum likelihood theory. The work presented here considers a new approach to the detection of weak GNSS signals using a Bayesian technique within a scenario where the search space size is already reduced to a few tens of cells using some kind of assisted information. The search space cells are considered as candidate cells, where each candidate cell is associated with a code delay and a Doppler frequency. For each candidate cell, a posteriori probability is propagated for a fixed number of operation cycles. At the end of the process, the maximum a posterior (MAP) criterion is used to select the correct cell. Simulation results are presented indicating that the proposed method provides a significant performance advantage over other reference schemes. They include a noncoherent integration scheme and another scheme which also utilizes the posterior probabilities as decision statistics but differs in the mechanism of probability propagation. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TAES.2014.120113 | IEEE Trans. Aerospace and Electronic Systems |
Keywords | Field | DocType |
Global Positioning System,Receivers,Satellite communication,Bayes methods,Detectors | Satellite system,Maximum likelihood,Electronic engineering,Posterior probability,A posteriori probability,GNSS applications,Code (cryptography),Statistical hypothesis testing,Mathematics,Bayesian probability | Journal |
Volume | Issue | ISSN |
50 | 3 | 0018-9251 |
Citations | PageRank | References |
2 | 0.41 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muhammad Tahir | 1 | 258 | 40.42 |
| Letizia Lo Presti | 2 | 129 | 21.84 |
| Maurizio Fantino | 3 | 28 | 5.15 |