A Gaussian error correction multi‐objective positioning model with NSGA‐II

• Published in: Concurrency and computation Vol. 32; no. 5
• Main Authors: Wang, Penghong, Huang, Jianrou, Cui, Zhihua, Xie, Liping, Chen, Jinjun
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 10-03-2020
• Subjects: Algorithms; Error analysis; Error correction; Error correction & detection; Gaussian distribution; Gaussian error correction; GGAII‐DVHop; Model testing; multi‐objective DVHop model; Network topologies; Normal distribution; Remote sensors; Wireless networks; wireless sensor networks
• ISSN: 1532-0626; 1532-0634
• DOI: 10.1002/cpe.5464

Summary
Distance vector‐hop (DVHop), as a range‐independent positioning algorithm, is a significant positioning method in wireless sensor networks (WSNs). It is composed of three parts, including connectivity detection, distance estimation, and position estimation. However, this simple positioning method results in a larger positioning error. Therefore, to enhance the positioning precision, this paper investigates the characteristic of error distribution between the estimated and real distance in the DVHop algorithm and reveals that the error is subjecting to the Gaussian distribution, N∼(0,1/3CR). Furthermore, to improve positioning accuracy, we propose a Gaussian error correction multi‐objective positioning model with non‐dominated sorting (NSGA‐II), which named GGAII‐DVHop. Finally, this model is tested on three complex network topologies, and the results demonstrate that it is significantly superior to other four algorithms in both positioning precision and robustness.