Measurement driven birth model for the generalized labeled multi-Bernoulli filter

This paper presents a measurement driven birth (MDB) model for the generalized labeled multi-Bernoulli (GLMB) filter. The MDB model adaptively generates target births based on measurement data, thereby eliminating the dependence of $\mathit{\text{a}}\mathit{\text{priori}}$ knowledge of target birth distributions. Numerical results are provided to demonstrate the performance.