Optimal sensor placement for source localization based on RSSD

Wireless Networks - Source localization based on the received signal strength (RSS) has received great interest due to its low cost and simple implementation. In this paper we consider the source...     

Joint RSSD/AOA Source Localization: Bias Analysis and Asymptotically Efficient Estimator

In this paper we study blind source localization problem based on the joint received signal strength difference (RSSD) and angle of arrival (AOA) measurements with unknown transmit power of source. Since RSSD and AOA measurements are uncorrelated, combining two methods leads to a better performance for source localization. This paper focus on the pseudo linear estimator (PLE) with a closed-form and low complexity solution. One of the main limitations in this estimator is the bias created from the correlation between system matrix and error vector, which is not vanished by increasing the number of measurements. To overcome this problem first, we present a bias compensated PLE using the closed instrumental variable (IV). Then, for improving the localization performance a weighting IV estimator (WIV) is presented. Finally, for achieving the Cramer–Rao lower bound (CRLB) an improved WIV (IWIV) estimator is used based on the known relation between the estimated parameters of WIV estimator. The proposed IWIV estimator is proved to be asymptotically efficient (i.e., obtaining zero bias and the Cramer–Rao lower bound). Numerical simulations also verify the theoretical development and show source localization using hybrid information RSSD/AOA has a superior performance than RSSD and AOA solely.