A Low-Complexity Direct Position Determination Method Based on the Diffusion Strategy in Wireless Sensor Array Networks

The direct position determination (DPD) algorithm in wireless sensor array networks(WSANs) has high localization accuracy under low signal-to-noise ratios (SNRs). However, with the increasing of arrays, the DPD algorithm faces challenges in tracking of mobile sources in time-varying environments due to the growing communication pressure and computational complexity. In this brief, a novel low-complexity DPD algorithm is considered in WSANs. First, an adaptive-filtering-based DPD model is proposed to reduce computational complexity, and the position of the target is estimated using the gradient descent method. Second, the proposed DPD method is extended to the distributed framework based on the diffusion strategy to distribute the communication pressure and computational load across the WSANs. As indicated by the simulation results, the proposed model outperforms the existing model exploiting. Furthermore, a negligible difference exists in localization performance and tracking performance between the proposed DPD method based on the diffusion strategy and the corresponding DPD method.