In emerging sensor network applications, localization requirement of applications and availability needs feasible algorithm with lower cost and higher accuracy. To localize the wireless sensor networks nodes accurately, we propose error-compensation based node distance estimation, which benefits from joint exploitation, at no cost, of the information provided by the adjacent areas and nodes. Under the given limitation, the localization problem is transformed into total least squares with inequality constraints (ICTLS) model with three estimated parameters, and the problem is solved by iteration of inequality constraints errors in variables. Simulation results show that the performance of our proposed algorithm is superior to DV-Hop algorithm and other improved algorithms in all considered scenarios.

In mobile wireless sensor networks (WSNs), error accumulation, and outlier problem seriously decrease the localization accuracy. To find a more accurate and cost-effective localization algorithm, cooperative localization with bounding constraints is proposed in this paper. By depicting the factor graph, the cooperative localization combines the trajectory prediction and observation correction of adjacent node. The trajectory prediction utilizes the polynomial Newton interpolation and bounding box which avoid the gross error. The observation correction explores the belief propagation and variational message passing, which are improved by judgment factor and punctuation function. Experiments are conducted to verify the proposed method in the aspect of algorithm parameter configuration, experiment parameter configuration, and distribution parameter configuration. The experiment results show that the proposed method in this paper outperforms than existing methods in large-scale WSNs.