基于正态分布判别函数的航迹关联双门限算法

Research of Double-threshold Tracks Correlation Algorithm Based on Normal Distribution Correlation Discriminant Function

雷达和电子支援(Electronic Support Measurement,简称ESM)传感器的航迹关联是异类多传感器数据融合研究方面的重要前提。以往对于关联判别函数的选取,多采用χ2分布,这使得在某些实际应用中,通常会出现计算量大,确定门限阈值复杂的问题。基于正态分布关联判别函数的航迹关联双门限算法,在门限阈值的选取上直接采用正态分布中的分位数概念,避免了χ2分布中选取阈值的复杂过程。通过仿真试验,验证了决策规则的第一类风险和第二类风险,表明该方法能有效地判决航迹的关联问题。

The problem of radar- ESM tracks correlation is precondition in the research of integrated data processing for asynchronous sensors. The method of X^2 distribution is which we always selected beforetime, but we would find the demerits such as much computational work and complicated determination of the threshold when we used it. In this article, it puts forward a algorithm of double- threshold tracks correlation based on normal distribution correlation discriminant function, using quantiles of normal distribution to determine the threshold and avoiding complicated determination in X^2 distribution. The simulation results validate the rough set and random set of decision - making rules and show the feasibility of the algorithm.