Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A new criterion based on Bayesian predictive densities and subspace decomposition is proposed for simultaneous detection of signals impinging on a sensor array and estimation of their direction-of-arrivals (DOAs). The solution is applicable for both coherent and noncoherent signals and an arbitrary array geometry. The proposed detection criterion is strongly consistent and outperforms the MDL and AIC criteria, particularly for a small number of sensors and/or snapshots, and/or low SNR, without increased computational complexity. When the prior of the direction-of-arrival is a uniform distribution, the Bayesian estimator for the directional parameters coincides with the unconditional maximum likelihood estimator. Simulation results that demonstrate the performance of the proposed solution are included. >
['Chao-Ming Cho', 'Petar M. Djuric']
I am writing a research paper on a idea Detection and estimation of DOA's of signals via Bayesian predictive densities
[{"from": "human", "value": "I am writing a research paper on a idea Detection and estimation of DOA's of signals via Bayesian predictive densities"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A new criterion based on Bayesian predictive densities and subspace decomposition is proposed for simultaneous detection of signals impinging on a sensor array and estimation of their direction-of-arrivals (DOAs). The solution is applicable for both coherent and noncoherent signals and an arbitrary array geometry. The proposed detection criterion is strongly consistent and outperforms the MDL and AIC criteria, particularly for a small number of sensors and/or snapshots, and/or low SNR, without increased computational complexity. When the prior of the direction-of-arrival is a uniform distribution, the Bayesian estimator for the directional parameters coincides with the unconditional maximum likelihood estimator. Simulation results that demonstrate the performance of the proposed solution are included. >"}]