Decorrelation of Previously Communicated Information for an Interacting Multiple Model Filter

In a sensor network compensation of the correlated information caused by previous communication is of utmost interest for distributed estimation. In this article, we investigate an information decorrelation approach that can be applied when using interacting multiple model filters in the sensor nodes for a family of jump Markov linear systems. Implementation issues that might arise while applying the decorrelation approach are addressed in detail. The investigated approach is compared with alternatives on simple distributed single maneuvering target tracking examples.

Automated summary

This article investigates an information decorrelation approach for distributed estimation in sensor networks, specifically for jump Markov linear systems. The implementation issues of this approach are addressed, and comparisons with alternative methods are made using simple examples of single maneuvering target tracking.