Distributed registration of a network of asynchronous sensors

Abstract

Registration of multiple sensors through common targets of opportunity is an extensively studied problem. The majority of proposed methods for computationally efficient estimation of sensor biases considered only the case of synchronous sensors. The relatively recent EXX method, however, allows exact estimation (under certain conditions) of sensor biases of asynchronous sensors. Unfortunately, the EXX method requires all measurements (or pseudomea-surements) originated by the targets of opportunity, which implies in high communication costs for large networks of sensors. In this paper, we formulate an extension of the EXX method that can be used for distributed bias estimation, i.e. obtains exact joint bias estimates for the entire network of sensors from joint bias estimates from subsets of these sensors. The proposed method can also be hierarchized in any manner, and can work with dissimilar sensors and different forms of sensor biases, thus being highly suited for today's demands of distributed data fusion.