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Similar to many technological developments, wireless sensor networks have emerged from military needs and found its way into civil applications. Today wireless sensor networks has become a key technology for different kinds of smart environments and an intense research effort is currently underway to enable the application of wireless sensor networks for a wide range of industrial problems. Wireless...
In this work, we present an experimental study, in which we deploy a 14-node 802.15.4-based sensor network in our department building. Using the k-nearest-neighbor (KNN) method to the estimation of location, we implement an RSSI-signature-based localization system on top of the network.
Shooter localization is considered in a wireless network of microphones. Both the acoustic muzzle blast (MB) from the gunfire and the ballistic shock wave (SW) from the bullet can be detected by the microphones and are considered as measurements. The MB measurements give rise to a standard sensor network problem, similar to time difference of arrivals in cellular phone networks, and the localization...
For a large and dense outdoor sensor network, the impact of sensor density and signal to noise ratio (SNR) are investigated on the performance of a maximum likelihood (ML) location estimation algorithm. The ML estimator fuses data, in the form of signal amplitudes, transmitted from local sensors to estimate the location of a source. A Gaussian-like isotropic signal decay model is adopted to make the...
This paper exploits recent developments in sparse approximation and compressive sensing to efficiently perform localization in a sensor network. We introduce a Bayesian framework for the localization problem and provide sparse approximations to its optimal solution. By exploiting the spatial sparsity of the posterior density, we demonstrate that the optimal solution can be computed using fast sparse...
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