Under the circumstances of multi-target tracking， due to clutter， missed detection and no-linearity， the Particle Probability Hypothesis Density (P-PHD) algorithm will result in such problems as low filter accuracy and tracking divergence.To overcome these problems， a Quadrature Particle based PHD Filter (QPF-PHD) algorithm is proposed.The Quadrature Particle Filter (QPF) is used to realize PHD;the Quadrature Kalman Filter (QKF) algorithm is applied to generate a better importance density function， from which to sample particles， enabling the distribution of particles to be much closer to the real distribution of PHD.The simulation results demonstrate that：compared with particle PHD and Gizmo particle PHD filter algorithms， the proposed filter algorithm has higher filter accuracy and stability.