Optimal Allocation And Data Fusion Scheme In Wireless Sensor Network For Target Tracking
Mobile objects location/tracking methods in wireless sensor networks (WSN)have received significant attention in
recent years. Among the network-based approaches, time of arrival (TOA) and time difference of arrival (TDOA) are two
major time-based techniques used for location/tracking estimation. In WSN, the geometric distribution of various sensor nodes
has a significant influence on the positioning accuracy. Geometric dilution of precision (GDOP) can be used to measure the
positioning precision of the localization system. This paper presents a data fusion scheme for mobile objects location via the
weighted least square (WLS) algorithm. When the sensors present the optimal allocation and then the WLS algorithm achieves
the optimal estimate. Simulation results verify the analysis of the optimal allocation form the data fusion framework, which can
be used in multi-sensor passive localization and validate our analysis.
Index Terms— Geometric dilution of precision; Data Fusion; Extended Kalman filter.