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FLORIS and CLORIS: Hybrid Source and Network Localization Based on Ranges and Video. (arXiv:1801.08155v1 [math.OC])
来源于:arXiv
We propose hybrid methods for localization in wireless sensor networks fusing
noisy range measurements with angular information (extracted from video).
Compared with conventional methods that rely on a single sensed variable, this
may pave the way for improved localization accuracy and robustness. We address
both the single-source and network (i.e., cooperative multiple-source)
localization paradigms, solving them via optimization of a convex surrogate.
The formulations for hybrid localization are unified in the sense that we
propose a single nonlinear least-squares cost function, fusing both angular and
range measurements. We then relax the problem to obtain an estimate of the
optimal positions. This contrasts with other hybrid approaches that alternate
the execution of localization algorithms for each type of measurement
separately, to progressively refine the position estimates. Single-source
localization uses a semidefinite relaxation to obtain a one-shot matrix
solution from which 查看全文>>