ENERGY-EFFICIENT DISTRIBUTED ESTIMATION ALGORITHM FOR WIRELESS SENSOR NETWORKS BASED ON COVARIANCE INTERSECTION WITH EIGENDECOMPOSITION

The paper introduces and assesses the Eigenvalue Covariance Intersection (EVCI) algorithm for data fusion in Wireless Sensor Networks. The EVCI aims to enhance information fusion efficiency, reduce transmitted data, and potentially extend network lifespan. By conducting the eigendecomposition of covariance matrices, the EVCI evaluates the utility of eigenvectors and strategically employs only those positively impacting estimate accuracy. Through simulations and comparisons with the Covariance Intersection (CI) algorithm, the study demonstrates EVCI's ability to maintain accuracy alongside with significant energy savings. The paper provides insights into popular data fusion algorithms, the concept of the EVCI, used formulas, and selected simulation results.