摘要
为提高多传感器融合的精确度,提出一种容积信息粒子多传感器融合算法。算法将容积信息滤波(CIF)和粒子滤波(PF)结合一起,采用CIF传递PF的粒子,通过引入信息贡献向量和信息贡献矩阵,将多个传感器的量测信息更新到PF的粒子中,提高粒子与真实状态后验概率分布的逼近程度,改进多传感器融合精确度。同时将CIF估计值作为粒子,消除随机扰动对融合的影响,提高粒子有效度,进一步提高融合精确度。仿真与实验表明,算法能够有效处理集中式多传感器融合问题,具有较高的滤波精确度。
A cubature information particle multi-sensors fusion algorithm is proposed to improve the precision of multi-sensors fusion.The algorithm combines Cubature Information Filter(CIF)with Particle Filter(PF),and adopts CIF to propagate particles of PF.The measurement information of multiple sensors is updated into particles of PF by introducing information contribution vector and information contribution matrix,to increase the approximation degree of particles to really posterior probability distribution,and to improve the precision of multi-sensors fusion.Meanwhile,the algorithm takes the state estimation of CIF as current particles,to eliminate the influence of random disturbance on multi-sensors fusion,and the precision of multi-sensors fusion is further improved.Simulation and experiment results show that,the algorithm can deal with the centralized multi-sensors fusion problem,and the filtering precision is high.
作者
王成
李敏
WANG Cheng;LI Min(Department of Electronic Information,Hunan Vocational College of Finance and Industry,Hengyang Hunan 421002,China;School of Computer Science,University of South China,Hengyang Hunan 421001,China)
出处
《太赫兹科学与电子信息学报》
2021年第6期1097-1102,共6页
Journal of Terahertz Science and Electronic Information Technology
基金
国家自然科学基金资助项目(31860173)。
关键词
信息滤波
多传感器
粒子滤波
容积卡尔曼滤波
information filter
multi-sensors
particle filter
cubature Kalman filter
