Abstract

We present a strategy for designing an $\alpha$ - $\beta$ - $\eta$ - $\theta$ filter, a fixed-gain moving-object tracking filter using position and velocity measurements. First, performance indices and stability conditions for the filter are analytically derived. Then, an optimal gain design strategy using these results is proposed and its relationship to the position-velocity-measured (PVM) Kalman filter is shown. Numerical analyses demonstrate the effectiveness of the proposed strategy, as well as a performance improvement over the traditional position-only-measured $\alpha$ - $\beta$ filter. Moreover, we apply an $\alpha$ - $\beta$ - $\eta$ - $\theta$ filter designed using this strategy to ultra-wideband Doppler radar tracking in numerical simulations. We verify that the proposed strategy can easily design the gains for an $\alpha$ - $\beta$ - $\eta$ - $\theta$ filter based on the performance of the ultra-wideband Doppler radar and a rough approximation of the target’s acceleration. Moreover, its effectiveness in predicting the steady state performance in designing the position-velocity-measured Kalman filter is also demonstrated. View Full-Text