Adaptive IMM-CFusion for a Remote IMM Track and Local Measurements

Abstract

The problem addressed in this paper is the tracking a maneuvering target in a distributed sensor network using a real-world-motivated fusion configuration. The local node $\mathrm{S}_{\mathrm{L}}$ receives a track from the remote node $\mathrm{S}_{\mathrm{R}}$ generated by its Interacting Multiple Model (IMM) estimator, and the “inside information” such as motion models, mode probabilities and mode-conditioned estimates of the remote track is unknown. The local node $\mathrm{S}_{\mathrm{L}}$ has its own measurements which need to be fused with the remote IMM track. This problem can be solved using an existing technique with the following steps: 1) generate a $\mathrm{S}_{\mathrm{L}}$ track based on its own measurements; 2) perform Track-to-Track Fusion (T2TF) on $\mathrm{S}_{\mathrm{R}}$ and $\mathrm{S}_{L}$ tracks. This paper will develop an alternative approach to fuse the remote IMM track and the local measurements directly. We called it the IMM Cumulated information Fusion (IMM-CFusion). The IMM-CFusion estimates the cumulated information of the local SLmeasurements with multiple models, and then fuses this cumulated information with the remote IMM track state. The IMM-CFusion shows better performance than the T2TF approach in a test case.