Guaranteeing practical convergence in algorithms for sensor and source localization
This paper considers localization of a source or a sensor from distance measurements. We argue that linear algorithms proposed for this purpose are susceptible to poor noise performance. Instead given a set of sensors/anchors of known positions and measured distances of the source/ sensor to be localized from them we propose a potentially nonconvex weighted cost function whose global minimum estimates the location of the source/sensor one seeks. The contribution of this paper is to provide...[Show more]
|Collections||ANU Research Publications|
|Source:||IEEE Transactions on Signal Processing|
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