Projection-Based linear constrained estimation and fusion over long-haul links
- ORNL
We study estimation and fusion with linear dynamics in long-haul sensor networks, wherein a number of sensors are remotely deployed over a large geographical area for performing tasks such as target tracking, and a remote fusion center serves to combine the information provided by these sensors in order to improve the overall tracking accuracy. In reality, the motion of a dynamic target might be subject to certain constraints, for instance, those defined by a road network. We explore the accuracy performance of projection-based constrained estimation and fusion methods that is affected by information loss over the long-haul links. We use an example to compare the tracking errors under various implementations of centralized and distributed projection-based estimation and fusion methods and demonstrate the effectiveness of using projection-based methods in these settings.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- DOE Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1327694
- Resource Relation:
- Conference: IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Badem Baden, Germany, 20160919, 20160922
- Country of Publication:
- United States
- Language:
- English
Similar Records
Projection-based circular constrained state estimation and fusion over long-haul links
Estimation and Fusion for Tracking Over Long-Haul Links Using Artificial Neural Networks