A novel algorithm is presented in this paper to jointly estimate frequency, two-dimensional (2-D) direc- tion-of-arrival (DOA), and range of near-field narrowband sources. The proposed method extends the parallel factor (PARAFAC) analysis model from the common data- and subspace-domain to the cumu- lant one, and forms three-way arrays by using the five cumulant matrices obtained from the array out- puts, and analyzes the uniqueness of low-rank decomposition of the three-way arrays, then jointly es- timates source parameters via the low-rank decomposition. In comparison with the conventional methods, the proposed method alleviates the loss of the array aperture, and avoids pairing parameters. What is more important, this algorithm can deal with mixed far-field and near-field sources. Finally, the simulation results validate the performance of the proposed method. A novel algorithm is presented in this paper to jointly estimate frequency, two-dimensional (2-D) direc- tion-of-arrival (DOA), and range of near-field narrow band sources. The proposed method extends the parallel factor ) analysis model from the common data- and subspace-domain to the cumu lant one, and forms three-way arrays by using the five cumulant matrices obtained from the array out-puts, and analyzes the uniqueness of low-rank decomposition of the three-way arrays, then jointly es- timates source parameters via the low-rank decomposition. In comparison with the conventional methods, the proposed method alleviates the loss of the array aperture, and avoids pairing parameters. What is more important, this algorithm can deal with mixed far-field and near-field sources. Finally, the simulation results validate the performance of the proposed method.