有限探测区域最大概率探测点寻优算法

Optimize Algorithm of the Maximum Probability of Detection Points in Limited Detection Area

研究了二维空间有限区域目标探测的最大概率探测点的计算问题。任意分布密度条件下目标的空间发现概率是空间面积上的积分,推导了发现概率对探测点梯度的一元积分的表达式,用于最大发现概率探测点的寻优计算,能够缩短计算时间,提高计算精度。

This dissertation researched calculation problem about the maximum probability of detection points of limited detection area in a two dimensional space. Under the condition of arbitrary distribution density, the discovering probability in space equals to integral on the space area. This thesis deduced one dimension integral expression of discovering probability to detection point of the gradient, which was used to the optimizing calculation of the maximum probability of detection point. It can reduce calculation time and improve calculation accuracy.