JOURNAL ARTICLE

Self-localization based on improved subspace approach in wireless sensor network

Abstract

In this paper, an improved subspace approach based on range measurement is proposed and analyzed. Through the factorization of multidimensional similarity (MDS) matrix, we derive a novel kernel subspace to estimate the coordinate of unknown mobile node in wireless sensor networks (WSN). Simulation results are included to contrast the estimator performance with general subspace method, and the performance analysis is provided.

Keywords:
Subspace topology Computer science Kernel (algebra) Wireless sensor network Node (physics) Estimator Matrix decomposition Similarity (geometry) Wireless Algorithm Range (aeronautics) Mathematics Artificial intelligence Computer network Telecommunications Statistics Engineering Discrete mathematics Eigenvalues and eigenvectors

Metrics

1
Cited By
0.29
FWCI (Field Weighted Citation Impact)
5
Refs
0.66
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing

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