Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Recently, localization for the coexistence of the far-field and near-field sources has received more attentions. , a maximum likelihood (ML) localization method using data supported optimization is considered. The range and direction of arrival (DOA) of the sources are estimated sequentially. Since a two step estimation method is used, the proposed method is applicable for the near-field sources, far-field sources or the mixture of these two kinds of sources. Furthermore, the proposed method is applicable for far-field and near-field source classification. Simulations are implemented to verify the performance of the proposed method.
['Fuxi Wen', 'Wee Peng Tay']
I am writing a research paper on a idea Localization for mixed near-field and far-field sources using data supported optimization
[{"from": "human", "value": "I am writing a research paper on a idea Localization for mixed near-field and far-field sources using data supported optimization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Recently, localization for the coexistence of the far-field and near-field sources has received more attentions. , a maximum likelihood (ML) localization method using data supported optimization is considered. The range and direction of arrival (DOA) of the sources are estimated sequentially. Since a two step estimation method is used, the proposed method is applicable for the near-field sources, far-field sources or the mixture of these two kinds of sources. Furthermore, the proposed method is applicable for far-field and near-field source classification. Simulations are implemented to verify the performance of the proposed method."}]