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Sensor localization bounds have been derived assuming that received signal strength (RSS) measurements are performed with perfectly known sensor transmit powers. In this paper the Bayesian Cramer-Rao bound is derived assuming transmit powers are random with known prior distribution. Further, both directional measurements on each link, from i to j and from j to i, and their correlation, are explicitly...
Sensor localization bounds have been derived assuming that received signal strength (RSS) measurements are performed with perfectly known sensor transmit powers. In this paper the Bayesian Cramer-Rao bound is derived assuming transmit powers are random with known prior distribution. Further, both directional measurements on each link, from i to j and from j to i, and their correlation, are explicitly...
This paper addresses the problem of locating an acoustic source using a sensor network in a distributed manner, i.e., without transmitting the full data set to a central point for processing. This problem has been traditionally addressed through the maximum likelihood framework or nonlinear least squares. These methods, even though asymptotically optimal under certain conditions, pose a difficult...
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