Decentralized track fusion in a dynamic battlespace network

Abstract

Track fusion in a decentralized battlespace network is examined. The battlespace comprises a mixed blue force (group carrier, AWACS, two fighter aircraft) and a red fighter aircraft. The network connectivity of the blue platforms evolves through four phases as the battlespace dynamics unfold. Specifically, it switches abruptly between fully connectivity and tree connectivity. The platforms are not permitted to have any global knowledge of this network topology; they only know about their local connections. This work consider the impact of unpredictable network topology changes on the performance of three decentralized track fusion algorithms. The first algorithm, referred to here as the Local Information Distribution (LID) algorithm, is optimal for fully connected networks. The second algorithm, known as the Global Information Distribution (GID) algorithm, is optimal for tree networks but otherwise inconsistent due to correlations induced by multiple combinations of the same item of information. The third algorithm, Covariance Intersection (CI), is always sub-optimal but is proven to be consistent in the presense of unknown correlations. Results are obtained, at each simulation time-step, for the accuracy of the fused red track at each blue platform. It is shown, for the battlespace scenario under investigation, that CI can sometimes outperform LID. This suggests that the platforms in a decentralized network, subject to unpredictable topology changes, should execute CI and LID in parallel for maximum overall tracking performance. However, this might impose prohibitive constraints on the amount of processing and network traffic. In practice, therefore, a trade-off solution might have to be found.