Effect of retransmission and retrodiction on estimation and fusion in long-haul sensor networks

Journal Article · Fri Jan 01 00:00:00 EST 2016 · IEEE/ACM Transactions on Networking

DOI:https://doi.org/10.1109/TNET.2014.2363841· OSTI ID:1327743

Liu, Qiang ^[1]; Wang, Xin ^[1]; Rao, Nageswara S. V. ^[2]; Brigham, Katharine ^[3]; Vijaya Kumar, B. V. K. ^[3]

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1. Stony Brook Univ., Stony Brook, NY (United States)
2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
3. Carnegie Mellon Univ., Pittsburgh, PA (United States)

In a long-haul sensor network, sensors are remotely deployed over a large geographical area to perform certain tasks, such as target tracking. In this work, we study the scenario where sensors take measurements of one or more dynamic targets and send state estimates of the targets to a fusion center via satellite links. The severe loss and delay inherent over the satellite channels reduce the number of estimates successfully arriving at the fusion center, thereby limiting the potential fusion gain and resulting in suboptimal accuracy performance of the fused estimates. In addition, the errors in target-sensor data association can also degrade the estimation performance. To mitigate the effect of imperfect communications on state estimation and fusion, we consider retransmission and retrodiction. The system adopts certain retransmission-based transport protocols so that lost messages can be recovered over time. Besides, retrodiction/smoothing techniques are applied so that the chances of incurring excess delay due to retransmission are greatly reduced. We analyze the extent to which retransmission and retrodiction can improve the performance of delay-sensitive target tracking tasks under variable communication loss and delay conditions. Lastly, simulation results of a ballistic target tracking application are shown in the end to demonstrate the validity of our analysis.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Science (SC)
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 1327743
• Journal Information: IEEE/ACM Transactions on Networking, Vol. 24, Issue 1; ISSN 1063-6692
• Publisher: IEEE/ACM
• Country of Publication: United States
• Language: English

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