Direct position determination of multiple coherent sources using an iterative adaptive approach

Abstract

The direct position determination (DPD) approach is known to outperform the two-step localization at low signal to noise ratio, however, and it encounters many difficulties when locating multiple coherent sources. In this paper, we combine the DPD with the iterative adaptive approach (IAA) to address the localization problem of coherent sources without knowing the transmitted signals. The frequency-domain coherent signal model is established to obtain snapshot samples for jointly processing signals received by all distributed arrays. To avoid the covariance matrix becoming rank-deficient, we propose to use the IAA to compute it and the intercepted signals, instead of the traditional methods directly based on the snapshots. Once estimating the intercepted signals, the closed-form spatial power function is derived to determine the positions of multiple coherent sources. Additionally, the method based on connected domain separation is also proposed to extract the position of each source from the spatial power map. Numerical experiments show that the proposed algorithm is superior to the existing DPD algorithms in accuracy and robustness for coherent sources, and can obtain the same great performance with the existing ones for noncoherent sources.