Abstract
Counting and tracking multiple targets by binary proximity sensors (BPS) is known difficult because a BPS in “on” state cannot distinguish how many targets are presenting in its sensing range. Existing approaches investigated target counting by utilizing joint readings of a network of BPSs, called a snapshot [2,11]. A recent work [14] presented a snapshot-based target counting lower bound. But counting by individual snapshot has not fully utilized the information between the sequential readings of BPSs. This paper exploits the spatial and temporal dependency introduced by a sequence of snapshots to improve the counting bounds and resolution. In particular, a dynamic counting scheme which considers the dependency among the snapshots were developed. It leads to a dynamic lower bound and a dynamic upper bound respectively. Based on them, an improved precisely counting condition was presented. Simulations were conducted to verify the improved counting limits, which showed the improvements than the snapshot-based methods.
This work was supported by in part by National Natural Science Foundation of China Grant 61202360, 61073174, 61033001, 61061130540, the Hi-Tech research and Development Program of China Grant 2006AA10Z216, and the National Basic Research Program of China Grant 2011CBA00300, 2011C-BA00302.
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Li, T., Wang, Y., Song, L., Tan, H. (2015). On Target Counting by Sequential Snapshots of Binary Proximity Sensors. In: Abdelzaher, T., Pereira, N., Tovar, E. (eds) Wireless Sensor Networks. EWSN 2015. Lecture Notes in Computer Science, vol 8965. Springer, Cham. https://doi.org/10.1007/978-3-319-15582-1_2
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DOI: https://doi.org/10.1007/978-3-319-15582-1_2
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