论文部分内容阅读
多传感器多目标无源交叉定位时存在虚假点的问题,且随着传感器和目标数量的增加,虚假点的数量也急剧增加。针对这个问题,提出了一种对目标无源定位跟踪的新方法,即首先通过判断预测点到传感器与目标构成的传感器目标测向方程的最小距离,来选取传感器目标测向方程,该算法可以有效避免大量虚假点的产生,以传感器目标测向方程的交点作为目标量测状态,再通过无味滤波(UF)算法得到目标点的位置。此方法解决了多传感器多目标定位跟踪时大量虚假点的存在对目标定位的影响。研究表明:本算法大大降低了运算量,且提高了关联正确率以及对目标的定位跟踪精度。
Multi-sensor multi-target passive cross-positioning problems exist fake point, and as the number of sensors and targets increases, the number of false points also increased dramatically. Aiming at this problem, a new method of passive target tracking is proposed. Firstly, the sensor’s target direction finding equation is selected by judging the minimum distance between the predicted point and the sensor’s target direction finding equation. The algorithm can The generation of a large number of false points is effectively avoided. The intersection point of the sensor’s target direction finding equation is taken as the target measurement state, and the position of the target point is obtained through a tasteless filter (UF) algorithm. This method solves the impact of the existence of a large number of false points on the target localization in multi-sensor multi-target location tracking. The research shows that this algorithm can greatly reduce the computational complexity and improve the accuracy of association and tracking accuracy of the target.