在基于粒子滤波的时延差定位估计方法中,重要密度函数的选取将直接影响估计的性能,为此,提出了基于容积粒子滤波的时延差估计(BCPF-TDE)算法.该算法利用最新的数据检测信息,通过容积卡尔曼滤波(CKF)获取粒子滤波的重要性密度函数.仿真实验表明,在粒子数目相同的情况下,基于容积粒子滤波的时延差估计(BCPFTDE)方法与基于扩展粒子滤波的时延差估计(BEPF-TDE)方法相比,定位估计误差只有后者的50%左右,而运行时间相当. In the time-delay location estimation method based on particle filter, the selection of the important density function will directly affect the performance of the estimation, so a time delay difference estimation (BCPF-TDE) algorithm based on volumetric particle filter is proposed.This algorithm uses the latest , The importance density function of particle filter is obtained by volumetric Kalman filter (CKF). The simulation results show that when the number of particles is the same, the time delay difference estimation based on volumetric particle filter (BCPFTDE) Compared with BEPF-TDE method, the estimation error of localization is only about 50% of the latter, and the running time is equivalent.