Sensor deployment optimization based on optimal recovery interpolation

Sergio D. Cabrera; Veenarai Moram; Jose Gerardo Rosiles

doi:10.1117/12.886522

24 May 2011 Sensor deployment optimization based on optimal recovery interpolation

Sergio D. Cabrera, Veenarai Moram, Jose Gerardo Rosiles

Proceedings Volume 8061, Wireless Sensing, Localization, and Processing VI; 806107 (2011) https://doi.org/10.1117/12.886522
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

Obtaining the desired signals in wireless sensor networks can be challenging due to various constraints on sensor placement or deployment. Retrieving the information accurately from sensors placed at non-uniform locations, is a problem of sensor communication and signal interpolation. In this research, the optimal recovery (OR) method, a deterministic framework that can use a priori bandwidth or spectral shape information, is used to interpolate from the given non-uniformly spaced samples. The error to be minimized is the maximum possible norm difference over a set of feasible signals. In the OR problem formulation and solution, the role of worst case feasible signals can be recognized but these signals are very difficult to find analytically. Computer simulations of feasible signals can help to produce estimates of the theoretical minimal worst-case error bounds. In this paper, monitoring of OR error bounds serves to assess sensor deployment configuration quality and to optimize the placement of additional sensors. Starting from an initial configuration of sensors, optimal deployment of additional sensors is clearly a more powerful option than random deployment of such sensors. These two approaches are compared and contrasted to show the improvement that is possible using the OR framework for one-dimensional and two-dimensional signals.

Citation Download Citation

Sergio D. Cabrera, Veenarai Moram, and Jose Gerardo Rosiles "Sensor deployment optimization based on optimal recovery interpolation", Proc. SPIE 8061, Wireless Sensing, Localization, and Processing VI, 806107 (24 May 2011); https://doi.org/10.1117/12.886522

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available