Research Article
Detection and Localization Algorithm Based on Sparse Reconstruction
@INPROCEEDINGS{10.1007/978-3-030-89814-4_64, author={Zhao Tang and Xingcheng Liu}, title={Detection and Localization Algorithm Based on Sparse Reconstruction}, proceedings={Mobile Multimedia Communications. 14th EAI International Conference, Mobimedia 2021, Virtual Event, July 23-25, 2021, Proceedings}, proceedings_a={MOBIMEDIA}, year={2021}, month={11}, keywords={Wireless Sensor Networks (WSN) Malicious anchor detection Sparse recovery Gradient projection Secure localization}, doi={10.1007/978-3-030-89814-4_64} }- Zhao Tang
Xingcheng Liu
Year: 2021
Detection and Localization Algorithm Based on Sparse Reconstruction
MOBIMEDIA
Springer
DOI: 10.1007/978-3-030-89814-4_64
Abstract
Wireless sensor networks (WSN) have received wide attention in many fields of applications. Secure localization is a critical issue in WSN. In the presence of malicious anchors, the traditional solution is to detect the malicious anchors, use the information collected from the normal anchors and then estimate the target location. The way of thinking and operating is reformed by modeling the behavior of the malicious anchors as perturbations. The secure localization is formulated as a sparse reconstruction problem. A gradient projection algorithm with variable step sizes is proposed to solve the sparse reconstruction. The proposed algorithm utilizes sparse reconstruction formulation for obtaining anchors information and identifying the malicious anchors by exploiting the sparsity of malicious anchors. The proposed algorithm is further modified to enhance the accuracy. The simulation results demonstrate that the proposed algorithm can effectively identify the cheating anchors and achieve great target anchors localization accuracy. The proposed algorithm performs better than any other algorithms of interest.
