复高斯白噪声背景下贝叶斯检测前跟踪的检测阈值设置方法

在Neyman-Pearson准则下，对于贝叶斯检测前跟踪算法，为了能够按照系统要求的虚警概率实时地设置检测阈值，该文在观测噪声为复高斯白噪声的情况下推导得到了检测阈值的近似闭式解。对于贝叶斯检测前跟踪算法，该文从似然比检测形式入手，推导了检测统计量的表达式，得到了系统虚警概率同检测阈值之间的关系，并在观测噪声为复高斯白噪声的情况下给出了检测阈值的近似闭式解。计算机仿真实验表明，利用该检测阈值的近似闭式解，可以按照系统要求的虚警概率实时地计算检测阈值，从而使得实际系统的虚警概率满足要求。

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.