Distributed Multisensor Fusion Algorithms for Tracking Applications (Year 1)
Abstract
The objective of the research under this ONR award is to develop distributed multisensor data fusion algorithms for tracking applications, as well as non-simulation and analytical methods of performance evaluation. Since the beginning of this project in June 1997, we have achieved results in several different areas: (1) We have developed a method of distributed fusion that is amenable to general distributed architectures; (2) We have developed two non-simulation techniques for comparing multisensor probabilistic data association filters that are significantly more computationally efficient than performing Monte Carlo simulation evaluations; (3) We have investigated and compared the computational complexity and tracking performance of sequential and parallel implementations of the multisensor probabilistic data association algorithm; and (4) We have developed several schemes for controlling sensor information and have evaluated the effects of delays. Our results will provide insight as to the relative performance of various multisensor fusion methods, and the results will also provide a basis for assessing the tradeoffs between performance and computational and communication requirements when planning new sensor network architectures or communication link protocols.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 26, 1998
- Accession Number
- ADA345499
Entities
People
- Lucy Y. Pao
Organizations
- University of Colorado Boulder