Abstract
Wireless sensor networks enjoy many advantages over wired networks due to their ability to be deployed easily and flexibly in many scenarios. However, they suffer from the drawback that the environment may be unknown and hence the sensor network cannot easily be optimised for it. Furthermore, state-of-the-art studies only consider the detection and localisation performance separately. The main novelty of this work is that we compare the theoretical properties of three scanning strategies both in terms of their detection and localisation performance. We consider: a) sequential scanning, where all sensors scan the channels in sequence, b) groupwise scanning, where the sensors are split into groups with each one performing a sequential scan, and c) random scanning, where each sensor is assigned a channel at random. We demonstrate the theoretical properties of the strategies and perform a numerical evaluation for a typical radio surveillance scenario. The tradeoffs of the methods between detection and localisation performance are demonstrated to be dependent on the detection and localisation accuracy with respect to the number of sensors. Approximate knowledge of those curves can aid in the design of an optimal sensor scanning strategy.
Original language | English |
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Title of host publication | 2019 Sensor Signal Processing for Defence Conference (SSPD) |
Publisher | IEEE |
ISBN (Electronic) | 9781728105031 |
DOIs | |
Publication status | Published - 1 Jul 2019 |
Event | 8th Sensor Signal Processing for Defence Conference 2019 - Brighton, United Kingdom Duration: 9 May 2019 → 10 May 2019 |
Conference
Conference | 8th Sensor Signal Processing for Defence Conference 2019 |
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Abbreviated title | SSPD 2019 |
Country/Territory | United Kingdom |
City | Brighton |
Period | 9/05/19 → 10/05/19 |
Keywords
- Detection
- Localisation
- Multiuser
- Sensor networks
- Sensor scanning
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Signal Processing
- Aerospace Engineering
- Control and Optimization