Direct Position Determination of the Distributed Source

Abstract

The traditional Direct Position Determination (DPD) methods have localization accuracy decrease when locating distributed sources. DPD methods of the distributed source is proposed in this paper to overcome mentioned above shortcoming. Firstly, a DPD model of the distributed source is constructed. Then two new DPD methods based on Maximum likelihood criterion and multiple signal classification are proposed to locate the distributed sourceMaximum Likelihood estimation DPD method of the Distributed source (DML-DPD) and Generalized Subspace DPD method (GS-DPD). Finally, target position is estimated via multidimensional grid search. The simulations show that the proposed methods have higher localization accuracy than traditional DPD methods when locating the distributed source, and are close to CRLB under the low SNR condition. DML-DPD method has higher localization accuracy than GS-DPD method in the case of low SNR, while GS-DPD method has less computational complexity than DML-DPD method.