A Method of Determining Detection Threshold for Bayesian Track-before-detection in White Complex Gaussian Noise

In order to set the detection threshold in real time according to the demanded false alarm probability for Bayesian track-before-detect under Neyman-Pearson criterion, this paper derives the closed-form solution of the detection threshold in white complex Gaussian noise. For the Bayesian track-before-detect, this paper starts from the likelihood ratio testing form, derives the relationship between the false alarm probability and the detection threshold in detail, and obtains the closed-form solution of the detection threshold in white complex Gaussian noise. The simulation results show that the detection threshold can be ascertained in real time for Bayesian track-before-detect according to the false alarm probability in demand using the presented approach.