Particle filter based on particle swarm optimization algorithm(PSO-PF) has the defects of low precision and calculation complexity, It is difficult to satisfy the requirement of accuracy and real-time of radar target tracking. To solve these problems, a novel particle filter algorithm based on neighborhood adaptive particle swarm optimization（DPSO-PF）is proposed. This algorithm investigates the neighborhood information of the particles, it adjusts the neighborhood environment dynamically using diversity factors, neighborhood extension factor, neighborhood limiting factor and control the effect of particles, it reduces the local optimization and realizes the best balance between the convergence speed and search ability. Finally, simulation and testing in the different models. The simulation results show that this algorithm improves the velocity and precision compared with PSO-PF, it is suitable for radar target tracking.