A Novel Interpolation Method for TDOA and FDOA Estimation based on Second-order Cone Programming

Abstract

Locating an emitting source based on time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements from passive sensors has widely been used in radar and sensor networks. The localization accuracy is directly influenced by the TDOA and FDOA estimation accuracy. While considerable research works have been performed on algorithm development, limited accuracy has been paid in TDOA and FDOA estimation. Therefore, a novel joint TDOA and FDOA estimation interpolation method with sub-sample accuracy based on second-order cone programming (SOCP) is presented in this paper. It combines the advantages of “soft” constraint and “hard” constraint to build optimization models, and obtains the interpolation surface through the SOCP, which can change the discrete ambiguity surface into continuous surface. The estimation accuracy of TDOA and FDOA is no longer forced to lie on sampling interval and sampling time. Simulation results indicate that the proposed method is effective and outperforms the other traditional interpolation algorithms regarding the estimation accuracy.