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提出增量粒子滤波的概念,建立增量粒子滤波模型及其分析方法,给出其算法.对于工程实际中存在的由未知系统误差的影响而无法精确建立量测似然函数的这一问题,提出增量粒子滤波方法,通过对带有未知系统误差的量测数据进行校正,获得精确的量测似然函数,建立精确的增量粒子滤波模型,从而消除这种未知系统误差的影响,减少重采样的次数,较好地保存了粒子的多样性,提高非线性滤波的精度.模拟仿真中,重采样的次数减少41.7%,滤波误差均值和均方根误差分别降低了45.3%和70.1%,有效地改善了滤波的效果.
The concept of incremental particle filter is proposed, an incremental particle filter model and its analytical method are established and its algorithm is given.For the problem that the measurement likelihood function can not be established precisely due to the influence of unknown system error in engineering practice, An incremental particle filter method is proposed to correct the measurement data with unknown systematic errors to obtain an accurate measurement likelihood function and establish an accurate incremental particle filter model so as to eliminate the influence of such unknown system errors and reduce The number of resampling, the better preservation of the particle diversity and improve the accuracy of nonlinear filtering.In simulation, the number of resampling reduced by 41.7%, the filtering error mean and root mean square error decreased by 45.3% and 70.1% , Effectively improve the filtering effect.