Multi-Node RSS-based Localization with the Aid of Compressed Sensing: An ℓ1-localization Approach

Authors

E. Zandi, R. Mathar,

Abstract

        In this work try we try to estimate the positions of multiple co-channel wireless nodes along with the unknown transmit power of them. The propagation channel is assumed to be log-normal shadowing model. We propose an unbiased estimator. The underlying complicated optimization problem has a combinatorial nature that selects the best grid points as the location of the targets. We then convert the combinatorial problem to a convex form by means of `1-minimization, or precisely a technique which is inspired by the theory of compressed sensing (CS). The performance of the estimator is justified to be good using simulations.

BibTEX Reference Entry 

@inproceedings{ZaMa19,
	author = {Ehsan Zandi and Rudolf Mathar},
	title = "Multi-Node {RSS}-based Localization with the Aid of Compressed Sensing: An {$\ell_1$}-localization Approach",
	pages = "1-8",
	booktitle = "23rd International ITG Workshop on Smart Antennas (WSA 2019)",
	address = {Vienna, Austria},
	month = Apr,
	year = 2019,
	hsb = RWTH-2019-04279,
	}

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