基于最近邻-拓扑图的异类传感器目标关联算法

针对雷达和高动态平台上的红外传感器构成的异类传感器信息融合系统中的目标关联问题，该文提出了一种基于最近邻-拓扑图的目标关联算法。该算法避免了系统误差补偿环节，有效地克服了最近邻方法对系统偏差敏感和拓扑图方法运算量大的不足，显著提高了存在系统误差条件下的关联成功率，且具有很强的稳健性。数值实验结果表明了该方法的有效性，目标关联正确率在90%以上。 

Target Association of Heterogeneous Sensors Based on Nearest-neighbor and Topology

A new data association algorithm is proposed in this paper for heterogeneous sensors information fusion system, which consists of Radar and high-dynamic-range IR, based on joint usage of the nearest-neighbor (NN) and the topology similarity. The proposed algorithm can avoid the complicated system biases compensation based on topology information. Because the NN method is sensitive to the system bias while the existing topology-based algorithms need a large amount of computation, the proposed algorithm shows a lot of advantages, like high estimation accuracy and robustness as well as the improvement of success association rate. Finally, some numerical experiments are provided to demonstrate the effectiveness of the proposed method. And the estimation accuracy can be as high as 90%.