High-Performance Clock Synchronization Algorithms for Distributed Wireless Airborne Computer Networks with Applications to Localization and Tracking of Targets
Abstract
The goal of this project was to develop efficient synchronization schemes to ensure robust operation of wireless airborne networks in the absence of GPS (Global Positioning Systems), and in the presence of arbitrary network delay distributions. To cope with the Gaussian or non-Gaussian nature of the random network delays, a novel method, referred to as the Gaussian Mixture Kalman Particle Filter (GMKPF), is proposed to estimate the clock offset and shown to be robust to arbitrary network delays. GMKPF represents a better and more flexible alternative to the Gaussian Maximum Likelihood (GML), and Exponential Maximum Likelihood (EML) estimators for clock offset estimation in non-Gaussian or non-exponential random delay models. The computer simulations illustrate that GMKPF yields much more accurate results relative to GML and EML when the network delays are modeled in terms of a single non-Gaussian/non-exponential distribution or as a mixture of several distributions. As deliverables, the set of Matlab programs used to implement GMKPF and validate its performance are uploaded separately into Jiffy.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2010
- Accession Number
- ADA523331
Entities
People
- Erchin Serpedin
Organizations
- Texas A&M University