Abstract: Aiming at the multi-objective optimization problem of sparse linear arrays (SLA) antenna, a collaborative optimization scheme based on density tapering and multiple objective particle swarm optimization (MOPSO) is proposed. Firstly, the SLA antenna is divided into two zones within its aperture range: a full array zone adjacent to the aperture center with the element spacing equal to half a wavelength, and a sparse array zone far from the center. Then, the MOPSO algorithm is utilized to optimize the element positions in the spare zone, ensuring that the element distribution in this zone always maintains density tapering distribution and the element intervals are all greater than half a wavelength. Consequently, the infeasible solutions are effectively avoided to facilitate the rapid optimization of the algorithm. Finally, combining two optimization objective functions, numerical simulations are conducted for SLA antennas with different apertures. The simulation results show that compared with several existing methods, the proposed algorithm can improve the level of sidelobe suppression by about 0.11 dB~5.72 dB and reduce the beam width by 0.160° at most in a short period of time. Moreover, it can effectively reduce the level of the designated null trap zone without obviously raising the sidelobe level.