多传感器对编队目标无源定位的数据关联技术研究

Research on Data Association Method in Multi-Sensor Passive Location of Formation Targets

关键词:  多传感器  无源定位  数据关联  虚假点剔除

Key words:  Multi-sensor  Passive location  Data association  False points elimination

摘要:

针对多传感器对编队目标进行测向交叉定位会产生大量虚假点的问题，提出了一种属性方位联合数据关联方法。采用基于支持度的关联算法对传感器探测到的目标属性数据进行初步关联，剔除部分虚假交点。然后利用改进的基准线最小距离法从候选集合中找出目标的真实测量数据关联集合。仿真结果表明，相对传统的方位数据关联方法，该方法不仅可以快速剔除虚假点，而且能够显著提高关联正确率。

Abstract:

In order to solve the problem of bringing a large quantity of false points in multi-sensor passive location of formation targets, an association algorithm based on feature parameters and azimuth information is proposed. Firstly the association algorithm based on the supports threshold is used to deal with the feature parameters detected by passive sensors in primary association, which can eliminate some false intersection points. Then the modified baseline least distance method is used to find the right location points of target from the spare intersection points sets.The simulation results show that this method can not only eliminate the false points rapidly，but also have a better association correct rate compared with the classical association methods only based on azimuth information.