Conditions for Guaranteed Convergence in 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:||Proceedings of the 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing|
|01_Fidan_Conditions_for_Guaranteed_2007.pdf||680.02 kB||Adobe PDF||Request a copy|
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