Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes a new algorithm for joint frequency, two-dimensional (2-D) directions-of-arrival (DOA), and polarization estimation using parallel factor (PARAFAC) analysis model and cumulant. The proposed algorithm designs a new array configuration, and extends the PARAFAC analysis model from the common data-domain and subspace-domain to the cumulant one, and forms three-way arrays by using the three cumulant matrices obtained from the properly chosen dipole outputs, and analyzes the uniqueness of low-rank decomposition of the three-way arrays, and then jointly estimates the source parameters via the low-rank decomposition of the constructed PARAFAC model. In comparison with the conventional methods, the proposed method alleviates the aperture loss, and avoids pairing parameter. Finally, the simulation results are presented to validate the performance of the proposed method.
['Junli Liang', 'Ding Liu', 'Junying Zhang']
I am writing a research paper on a idea Joint frequency, 2-D DOA, and polarization estimation using parallel factor analysis
[{"from": "human", "value": "I am writing a research paper on a idea Joint frequency, 2-D DOA, and polarization estimation using parallel factor analysis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes a new algorithm for joint frequency, two-dimensional (2-D) directions-of-arrival (DOA), and polarization estimation using parallel factor (PARAFAC) analysis model and cumulant. The proposed algorithm designs a new array configuration, and extends the PARAFAC analysis model from the common data-domain and subspace-domain to the cumulant one, and forms three-way arrays by using the three cumulant matrices obtained from the properly chosen dipole outputs, and analyzes the uniqueness of low-rank decomposition of the three-way arrays, and then jointly estimates the source parameters via the low-rank decomposition of the constructed PARAFAC model. In comparison with the conventional methods, the proposed method alleviates the aperture loss, and avoids pairing parameter. Finally, the simulation results are presented to validate the performance of the proposed method."}]