Balanced Cooperative Target Search of Mobile Sensor Fleet under Localization Uncertainty

Abstract

This paper deals with the problem of multiple sensors installed on mobile platforms cooperating to search for the target while each sensor is subject to localization uncertainty. The balance between a couple of conflicting objectives: i) suppressing the growth of self-localization uncertainty as an individual mobile agent; ii) reducing target uncertainty as a team, is sought under the information-theoretic framework. The conventional particle filter approach that concerns only the target state is augmented with self-localization by jointly estimating both. The self-localization is facilitated by introducing additional radio signals emitted from the origin, which should be a practical assumption considering limited resources and the restricted capability of small mobile sensors in case of a GNSS outage. The proposed method is featured with the numerical calculation of mutual information based on the principle of kernel conditional density estimation, and the unified comparison scheme between conflicting objectives. The numerical experiment shows that the proposed probing control law can automatically switch between target ascertaining and observability enhancing based on the mutual information-based utility function in a distributed fashion.