Array localization using least squares error minimization

Accurate localization of array sensor nodes is often a problem in ocean surveillance areas where in-situ surveying is not possible. This is due to the inability to completely control an array during its deployment phase. Ocean currents, ship motion, and array line flexure often make post deployment calculation of final positions largely a guessing game. Different optimization techniques are researched as estimators for sensor node positions. In this study, the sensors consist of an array of total field magnetometers interleaved with acoustic and electromagnetic sensors. A surface ship with known course and speed traveling near the array generates a magnetic signature which is picked up by the array. A far-field dipole model is assumed and the parameters are estimated by minimizing the least-squares error discrepancy over the sampled time series. Variable-metric and stochastic methods are used to optimize the parameter estimation problem