GM-PHD filter-based multi-target tracking in the presence of Doppler blind zone

Abstract

For the problem of multi-target tracking, utilization of Doppler information can greatly improve the tracking performance. However, the presence of Doppler blind zone (DBZ) strongly deteriorates the performance. To overcome this problem, we first employ a well-known detection probability model with incorporating the minimum detectable velocity (MDV), which determines the width of the DBZ. Then, by substituting the resulting detection probability into the update equation of the standard Gaussian mixture probability hypothesis density (GM-PHD) filter, we derive the update expression for a novel GM-PHD filter where the MDV and Doppler information are fully exploited. Moreover, we present an approximate filter with detailed implementation steps to reduce the amount of calculation without a significant degradation in performance. It is demonstrated through numerical examples that the proposed approach outperforms the existing GM-PHD filter which doesn't incorporate the MDV or Doppler information. Particularly, it has significantly better performance at small MDV value.