By Topic

Optimality Analysis of Sensor-Source Geometries in Heterogeneous Sensor Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Wei Meng ; EXQUISITUS, Nanyang Technol. Univ., Singapore, Singapore ; Lihua Xie ; Wendong Xiao

Source localization is an important application of wireless sensor networks (WSNs). Many types of sensors can be used for source localization, e.g., range sensors, bearing sensors and time-difference-of-arrival (TDOA) based sensors, etc. It is well known that relative sensor-source geometry can significantly affect the performance of any particular localization algorithm. Existing works in the literature mainly deal with geometry analysis for homogeneous sensors. However, in real applications, different types of sensors may be utilized for source localization. Hence, in this paper, we consider the optimal sensor placement problem in heterogeneous sensor networks (HSNs), where two types of sensors are deployed for source localization. Relative optimal sensor-source configurations with the minimum number of sensors for source localization are identified under the Doptimality criterion with potential extensions to the general case. Explicit characterizations of optimal sensor-source geometries are given for hybrid range and bearing sensors, hybrid bearing and TDOA based sensors as well as co-located hybrid range and bearing sensors, respectively. The results of this work can be applied to the sensor path planning problem for optimal source localization.

Published in:

Wireless Communications, IEEE Transactions on  (Volume:12 ,  Issue: 4 )