基于改进Sigma点的无迹卡尔曼滤波水下目标跟踪算法  

Underwater Target Tracking Algorithm with Untraced Kalman Filter Based on Improved Sigma Points

作　　者：徐正兴 诸云[1] 吴祎楠 XU Zhengxing;ZHU Yun;WU Yinan(School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China)

机构地区：[1]南京理工大学自动化学院,南京210094

出　　处：《无人系统技术》2023年第4期22-30,共9页Unmanned Systems Technology

摘　　要：由于阵列所接收的信号在工作过程中会受到辐射噪声、环境噪声和目标信号、水下生物运动干扰,因此在目标跟踪的过程中降低噪声干扰并提高目标追踪精准度,正逐渐成为水下目标跟踪领域的研究热点和难点。常用的改进方法是根据Sigma点的采样策略进而对相应的方差权值和均值权值进行修改,Sigma点的采样策略则常常被忽视了。提出了一种基于改进Sigma点的无迹卡尔曼滤波算法(IUKF)优化水下目标跟踪效果。针对目标跟踪中测量噪声以及过程噪声影响导致的准确性问题,将第一次UT变换得到的增广状态向量以及协方差矩阵作为初始值对Sigma点进行了二次UT变换,与进行一次UT变换给定了的初始增广状态向量以及初始协方差矩阵相比,经过二次UT变换后的增广状态向量以及初始协方差矩阵精度更高。经过仿真,估计位置和真值之间的偏差减小了42.7%以上,估计距离和实际距离误差之间的偏差减小了86%,仿真实验结果表明所提的改进Sigma点的无迹卡尔曼滤波算法可以有效地抑制环境噪声的影响,提高水下目标跟踪精准度,在海洋资源勘探以及水下目标跟踪方面具有很好的实际应用前景。Since the signal received by the array will be interfered by radiated noise,environmental noise,target signal and underwater biological movement in the process of working,reducing noise interference and improving target tracking accuracy in the process of target tracking are gradually becoming a hot spot and difficult point in the field of underwater target tracking.The commonly used improvement method is to modify the corresponding variance weight and mean weight according to the sampling strategy of Sigma points,while the sampling strategy of Sigma points is often ignored.In this paper,an unscented Kalman filter algorithm(IUKF)based on improved Sigma points is proposed to optimize the tracking effect of underwater targets.Aiming at the accuracy problem caused by the noise influence in target tracking,this experiment uses the augmented state vector and covariance matrix obtained from the first UT transformation as the initial values to carry out the second UT transformation on the Sigma point.Compared with the initial augmented state vector and covariance matrix given by the first UT transformation,the accuracy of the augmented state vector and initial covariance matrix after the second UT transformation is higher.After simulation,the deviation between the estimated position and the true value is reduced by more than 42.7%,and the deviation between the estimated distance and the actual distance error is reduced by 86%.The simulation results show that the improved Sigma point unscented Kalman filter algorithm proposed in this paper can effectively suppress the impact of environmental noise,improve the accuracy of underwater target tracking,and have a good practical application prospect in marine resource exploration and underwater target tracking.

关 键 词：水下目标跟踪 改进Sigma点的无迹卡尔曼滤波 噪声优化 二次UT变换 卡尔曼滤波 采样策略 非线性 

分 类 号：TP15[自动化与计算机技术—控制理论与控制工程]