DOA Estimation for Coherent Sources in Transformed Space

The existence of coherent sources results in the rank deficit of sample covariance matrix. Classic MUSIC(Multiple Signal Classification) can not classify coherent sources, and instead, generate an equivalent sources somewhere between them. In the proposed method, first, a specially designed transformation is constructed, which can suppress the coherent interfering sources while retain desired coherent sources. With the transformation the collected array signal can be mapping into a new data space. Since in the process of transformation, the contribution of the coherent interfering sources is suppressed, applying the classical music to the transformed data space will result in accurate DOA estimation of the coherent sources. Simulation experiment show that compared to the classical music, this method can accomplish accurate DOA estimation of coherent sources.