Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In multi-target tracking, the discrepancy beten the nominal and the true values of the model parameters might result in poor performance. , an adaptive Probability Hypothesis Density (PHD) filter is proposed which accounts for sensor parameter uncertainty. Variational Bayes technique is used for approximate inference which provides analytic expressions for the PHD recursions analogous to the Gaussian mixture implementation of the PHD filter. The proposed method is evaluated in a multi-target tracking scenario. The improvement in the performance is shown in simulations.
['Tohid Ardeshiri', 'Emre Ozkan']
I am writing a research paper on a idea An adaptive PHD filter for tracking with unknown sensor characteristics
[{"from": "human", "value": "I am writing a research paper on a idea An adaptive PHD filter for tracking with unknown sensor characteristics"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In multi-target tracking, the discrepancy beten the nominal and the true values of the model parameters might result in poor performance. , an adaptive Probability Hypothesis Density (PHD) filter is proposed which accounts for sensor parameter uncertainty. Variational Bayes technique is used for approximate inference which provides analytic expressions for the PHD recursions analogous to the Gaussian mixture implementation of the PHD filter. The proposed method is evaluated in a multi-target tracking scenario. The improvement in the performance is shown in simulations."}]