Robust Matched Field Localization Based on Replica Field Noise Subspace Perturbation Constraints
Yan Zhang · Jisuanji fangzhen · 2010
Based on replica field noise subspace perturbation constraints,a matched field localization algorithm in the presence of environmental uncertainties is presented.First,the environmental parameters are randomly sampled and the replica field vectors are computed for each search grid.Then,a replica field covariance matrix is formed with these replica field vectors.By decomposing the replica field covariance matrix and selecting eigenvectors corresponding to relatively small eigenvalues,a constraint matrix is obtained.Meantime,the eigenvector with largest eigenvalue for data covariance matrix is used as signal vector.At last the localization ambiguity surface is formed with the constraint matrix and the signal vector.By using simulation and experiment data,the robust performance of the presented algorithm is evaluated for different environment perturbation times and constraint matrix dimensions.