The comparison of JADE based DOA estimation methods for unknown noncoherent source groups containing coherent signals with frequency matching

In this study, all parameters (including the frequency of each signal group) of direction-of-arrival (DOA) problem are aimed to be extracted in the presence of unknown noncoherent source groups, which are consisting of coherent signals. The antenna elements used in the fading analysis and application are isotropic, linear and uniformly distributed, and all parameters of the complete signal are assumed to be unknown except the number of coherent signal in each noncoherent group. To obtain the desired parameters (number of noncoherent groups, arrival angles, fading coefficients, frequencies), it is proposed a four-step approach. First, the number of noncoherent signal groups is determined by the minimum description length (MDL). Then, effective steering vectors are estimated using the joint approximate diagonalization of eigenmatrices (JADE) algorithm. In the third step, by using these steering vectors some popular high-resolution DOA methods such as the modified forward backward linear prediction (MFBLP), estimation of signal parameters via rotational invariance techniques (ESPRIT) and root multiple signal classification (MUSIC) algorithms are realized to calculate the angle and fading coefficient of each coherent signal. Finally, a frequency matching is realized to assign the possible frequency to each group. The proposed approach is summarized, and simulation results comparing the performance of high-resolution methods are demonstrated. According to the results, MFBLP is found to have better accuracy performances.