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Estimating Parameters of Multiple Heterogeneous Target Objects Using Composite Sensor Nodes

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4 Author(s)
Saito, H. ; NTT Service Integration Labs., Musashino, Japan ; Shimogawa, S. ; Tanaka, S. ; Shioda, S.

We propose a method for estimating parameters of multiple target objects by using networked binary sensors whose locations are unknown. These target objects may have different parameters, such as size and perimeter length. Each sensors, which is incapable of monitoring the target object's parameters, sends only binary data describing whether or not it detects target objects coming into, moving around, or leaving the sensing area at every moment. We previously developed a parameter estimation method for a single target object. However, a straight-forward extension of this method is not applicable for estimating multiple heterogeneous target objects. This is because a networked binary sensor at an unknown location cannot provide information that distinguishes individual target objects, but it can provide information on the total perimeter length and size of multiple target objects. Therefore, we propose composite sensor nodes with multiple sensors in a predetermined layout for obtaining additional information for estimating the parameter of each target object. As an example of a composite sensor node, we consider a two-sensor composite sensor node, which consists of two sensors, one at each of the two end points of a line segment of known length. For the two-sensor composite sensor node, measures are derived such as the two sensors detecting target objects. These derived measures are the basis for identifying the shape of each target object among a given set of categories (for example, disks and rectangles) and estimating parameters such as the radius and lengths of two sides of each target object. Numerical examples demonstrate that networked composite sensor nodes consisting of two binary sensors enable us to estimate the parameters of target objects.

Published in:

Mobile Computing, IEEE Transactions on  (Volume:11 ,  Issue: 1 )

Date of Publication:

Jan. 2012

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