一种基于改进UPF的运动声阵列交互多模型目标跟踪方法

针对运动声阵列在有色噪声环境中的非线性滤波跟踪实时性问题,提出一种基于改进粒子滤波的交互式多模型目标跟踪(IMM-IUPF)方法.该方法采用最小斜度单形无迹变换结合变尺度无迹变换的 Sigma点选取策略,对标准无迹粒子滤波(UPF)进行改进,大幅缩减UPF样本选取计算量;将改进的UPF与交互式多模型(IMM)相结合,通过定义自适应增益修正系数,弥补样本点缩减造成的精度降低问题;最终通过与传统的基于IMM的粒子滤波(IMM-PF)和基于IMM的无迹粒子滤波(IMM-UPF)进行Matlab数值仿真对比验证所提出算法的实用性.

An improved UPF-based interacting multiple model target tracking method for dynamic acoustic array

In order to solve the real-time problem of nonlinear filter tracking using dynamic acoustic array in colored noise environment, an interacting multiple model target tracking method based on the improved unscented particle filter(IMM-IUPF) is proposed.In the method, an improved Sigma point selection strategy based on a minimal skew simplex unscented transform and a scaled unscented transform is adopted, which reduces the computational complexity of Sigma point selection in the standard unscented particle filter(UPF).Then the improved UPF is combined with the interacting multiple model(IMM).In addition, a self-adaptive gain modification coefficient is defined for solving the low-accuracy problem caused by the Sigma point reduction.Finally, the validity and superiority of the proposed algorithm is verified in comparison with traditional the IMM-PF and recent IMM-UPF.