On scalable distributed sensor fusion

The theoretic fundamentals of distributed information fusion are well developed. However, practical applications of these theoretical results to dynamic sensor networks have remained a challenge. There has been a great deal of work in developing distributed fusion algorithms applicable to a network centric architecture. In general, in a distributed system such as ad hoc sensor networks, the communication architecture is not fixed. In those cases, the distributed fusion approaches based on pedigree information may not scale due to limited communication bandwidth. In this paper, we focus on scalable fusion algorithms and conduct analytical performance evaluation to compare their performance. The goal is to understand the performance of these algorithms under different operating conditions. Specifically, we evaluate the performance of Channel filter fusion, Chernoff fusion, Shannon Fusion, and Bhattacharyya fusion algorithms. We also compare their performance to Naïve fusion and “optimal” centralized fusion under a specific communication pattern.