Obstacle mapping in wireless sensor networks via minimum number of measurements

Amirafshar Moshtaghpour; Mohammad Ali Akhaee; Masoud Attarifar

Obstacle mapping in wireless sensor networks via minimum number of measurements

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Author(s): Amirafshar Moshtaghpour ¹ ; Mohammad Ali Akhaee ¹ ; Masoud Attarifar ¹
- Affiliations: 1: Secure Communication Lab (SCL), School of Electrical and Computer Engineering, University of Tehran, 14395515 Tehran, Iran
Source: Volume 10, Issue 3, May 2016, p. 237 – 246
DOI: 10.1049/iet-spr.2014.0391 , Print ISSN 1751-9675, Online ISSN 1751-9683

Received 21/09/2014, Accepted 25/09/2015, Revised 16/09/2015, Published 01/05/2016

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.

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Obstacle mapping in wireless sensor networks via minimum number of measurements

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