Hierarchical-IMM Based Maneuvering Target Tracking in LOS/NLOS Hybrid Environments

作者：Zhou, Yan^*; Hu, Lan; Wang, Dongli

来源：IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2016, E99A(5): 900-907.

DOI：10.1587/transfun.E99.A.900

• maneuvering target tracking
• LOS/NLOS
• interacting multiple model
• current statistic
• unscented Kalman filter

Maneuvering target tracking under mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions has received considerable interest in the last decades. In this paper, a hierarchical interacting multiple model (HIMM) method is proposed for estimating target position under mixed LOS/NLOS conditions. The proposed HIMM is composed of two layers with Markov switching model. The purpose of the upper layer, which is composed of two interacting multiple model (IMM) filters in parallel, is to handle the switching between the LOS and the NLOS environments. To estimate the target kinetic variables (position, speed and acceleration), the unscented Kalman filter (UKF) with the current statistical (CS) model is used in the lower-layer. Simulation results demonstrate the effectiveness and superiority of the proposed method, which obtains better tracking accuracy than the traditional IMM.

• 出版日期2016-5
• 单位湘潭大学