@inproceedings{aslam:tracking,
    author = {Aslam, Javed and Butler, Zack and Constantin, Florin and Crespi,
Valentino and Cybenko, George and Rus, Daniela},
    title = {Tracking a moving object with a binary sensor network},
    booktitle = {Proceedings of the First International Conference on Embedded
Networked Sensor Systems (SenSys)},
    year = {2003},
    month = {November},
    pages = {150--161},
    publisher = {ACM Press},
    copyright = {ACM},
    address = {Los Angeles, CA},
    group = {cmc, coabs},
    url = {http://doi.acm.org/10.1145/958491.958509},
    urlpdf = {http://cmc.cs.dartmouth.edu/papers/aslam:tracking.pdf},
    abstract = {In this paper we examine the role of very simple and noisy
sensors for the tracking problem. We propose a binary sensor model, where
each sensor's value is converted reliably to one bit of information only:
whether the object is moving toward the sensor or away from the sensor. We
show that a network of binary sensors has geometric properties that can be
used to develop a solution for tracking with binary sensors and present
resulting algorithms and simulation experiments. We develop a particle
filtering style algorithm for target tracking using such minimalist sensors.
We present an analysis of fundamental tracking limitation under this sensor
model, and show how this limitation can be overcome through the use of a
single bit of proximity information at each sensor node. Our extensive
simulations show low error that decreases with sensor density.}
}