Stansfield Localization Algorithm: Theoretical Analysis and Distributed Implementation

In this letter, we focus on the Stansfield localization algorithm, which is a direction-of-arrival (DoA) fusion algorithm with high accuracy and low complexity. We derive the mean square error of the Stansfield algorithm with estimated DoA estimation error variance. Our derivation considers the statistical variation of DoA, as well as the impact of receive signal strength variations and node self-positioning error. In addition, we propose a distributed implementation of the Stansfield algorithm based on diffusion adaptation, which obtains accuracy comparable to its centralized counterpart and saves total transmit power for sufficient node density.

[1]  A. Weiss,et al.  Performance analysis of bearing-only target location algorithms , 1992 .

[2]  R.L. Moses,et al.  Locating the nodes: cooperative localization in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[3]  Danijela Cabric,et al.  Bounds and Tradeoffs for Cooperative DoA-Only Localization of Primary Users , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[4]  R. G. Stansfield,et al.  Statistical theory of d.f. fixing , 1947 .

[5]  Danijela Cabric,et al.  Cramer-Rao Bounds for Joint RSS/DoA-Based Primary-User Localization in Cognitive Radio Networks , 2012, IEEE Transactions on Wireless Communications.

[6]  Ali H. Sayed,et al.  Diffusion Adaptation Strategies for Distributed Optimization and Learning Over Networks , 2011, IEEE Transactions on Signal Processing.

[7]  Petre Stoica,et al.  MUSIC, maximum likelihood and Cramer-Rao bound , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.