NDLI: Obstacle mapping in wireless sensor networks via minimum number of measurements

Content Provider	IET Digital Library
Author	Moshtaghpour, Amirafshar Akhaee, Mohammad Ali Attarifar, Masoud
Abstract	In this study, a group of wireless sensors are tasked to trace indoor obstacles without the need to sense them, directly. The authors introduce a novel framework based on compressed sensing theory that allows sensors to map two-dimensional spatial details, non-invasively. By exploiting an alternative projection method which reduces the randomness nature of previous works, the resulting measurement matrix can provide linear samples from an unknown environment more efficiently. It is shown that how sparse representation of the spatial parameters in some domains can be utilised in order to realise obstacle mapping with minimum number of wireless transmissions and receptions. In addition, theoretical analyses along with simulation results illustrate premier performance of their framework. Furthermore, they test their method in different circumstances and show how drawbacks such as walls, bulkheads, and environmental constraints can affect the reconstruction performance. Therefore, they proposed two algorithms (i.e. reducing wall effect and reducing bulkhead effect) in order to decrease the impression of walls and bulkheads which is supported theoretically. Finally, a well-applicable scenario based on their framework is defined and proposing the next best transmitter algorithm remarkable results are achieved.
Starting Page	237
Ending Page	246
Page Count	10
ISSN	17519675
Volume Number	10
e-ISSN	17519683
Issue Number	Issue 3, May (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/10/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2014.0391
Journal	IET Signal Processing
Publisher Date	2016-05-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Alternative Projection Method Compressed Sensing Compressed Sensing Theory Indoor Obstacle Tracing Indoor Radio Matrix Algebra Measurement Matrix Object Detection Obstacle Mapping Signal Processing And Detection Signal Representation Spatial Parameter Sparse Representation Transmitter Algorithm Wireless Reception Wireless Sensor Network Wireless Transmission
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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