Yao Yu, Zhao Junhui, Wu Lenan
School of Information Engineering, East China Jiaotong University, Nanchang 330031, China.
School of Information Science and Engineering, Southeast University, Nanjing 210096, China.
Sensors (Basel). 2019 Apr 29;19(9):2003. doi: 10.3390/s19092003.
In many wireless sensors, the target kinematic states include location and Doppler information that can be observed from a time series of range and velocity measurements. In this work, we present a tracking strategy for comprising target velocity components as part of the measurement supplement procedure and evaluate the advantages of the proposed scheme. Data association capability can be considered as the key performance for multi-target tracking in an active sonar system. Then, we proposed an enhanced Doppler data association (DDA) scheme which exploits target range and target velocity components for linear multi-target tracking. If the target velocity measurements are not incorporated into target kinematic state tracking, the linear filter bank for the combination of target velocity components can be implemented. Finally, a significant enhancement in the multi-target tracking capability provided by the proposed DDA scheme with the linear multi-target combined probabilistic data association method is demonstrated in a sonar underwater scenario.
在许多无线传感器中，目标运动状态包括位置和多普勒信息，这些信息可从距离和速度测量的时间序列中观测到。在这项工作中，我们提出了一种跟踪策略，将目标速度分量作为测量补充程序的一部分，并评估所提方案的优势。数据关联能力可被视为主动声纳系统中多目标跟踪的关键性能。然后，我们提出了一种增强型多普勒数据关联（DDA）方案，该方案利用目标距离和目标速度分量进行线性多目标跟踪。如果目标速度测量未纳入目标运动状态跟踪，则可实现用于目标速度分量组合的线性滤波器组。最后，在所提DDA方案与线性多目标组合概率数据关联方法相结合的情况下，在声纳水下场景中展示了多目标跟踪能力的显著增强。
