IMM Bernoulli Filter for Cooperative Object Tracking in Road Traffic

Abstract

Cooperative multi-model state estimation is considered in road traffic scenario. Our goal is to detect and track a maneuvering object based on vehicular radar measurements. To handle the motion model switching of the navigating object we used the interacting Multiple Model (IMM) estimator with the Bernoulli filter (BF). We modified a recently derived IMM-BF, realized in a Gaussian mixture approximation to fulfil the requirements of a multi-sensor object tracking estimator with moving sensors. Our proposed method is implemented as a Sequential Monte Carlo estimator that allows nonlinear motion and sensor models and is capable of functioning effectively in a cooperative manner.