Design of bearing-only vision-based tracking filters

Abstract

We investigate tracking filters in electro-optical target-tracking systems with bearing-only measurements and a stationary tracker. In passive tracking, for maintaining the target in the camera field of view, two tracking angles should be controlled. To extract the target position, there is at least one frame period latency resulting from time duration required for image processing. Three filtering methods, a simple Kalman filter, a novel filtering approach based on curve fitting on time series data, and an interactive multiple model filter, are studied. Since target range is neither available nor observable, in the all mentioned techniques, instead of applying filters to the target states (position and velocity in the space), each filter is directly applied to the tracking angles. The performance of each filter in this approach is evaluated by tracking angles error with two maneuvering targets.