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.
This work was supported by the Key Project of NSFC-Guangdong Province Joint Program (Grant No. U2001204), the National Natural Science Foundation of China (Grant Nos. 61873290 and 61972431), the Science and Technology Program of Guangzhou, China (Grant No. 202002030470), and the Funding Project of Featured Major of Guangzhou Xinhua University (2021TZ002).
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Tang, Z., Liu, X. (2021). Detection and Localization Algorithm Based on Sparse Reconstruction. In: Xiong, J., Wu, S., Peng, C., Tian, Y. (eds) Mobile Multimedia Communications. MobiMedia 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 394. Springer, Cham. https://doi.org/10.1007/978-3-030-89814-4_64
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DOI: https://doi.org/10.1007/978-3-030-89814-4_64
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