拟蒙特卡罗自适应粒子滤波的机载无源定位算法  

Quasi Monte-Carlo Adaptive Particle Filter for Airborne Passive Location

作　　者：刘学[1,2] 焦淑红[1] 

机构地区：[1]哈尔滨工程大学信息与通信工程学院 [2]中国人民解放军91245部队

出　　处：《西安交通大学学报》2011年第9期34-39,83,共7页Journal of Xi'an Jiaotong University

基　　金：国家"973计划"资助项目(61393010101-1);国防基础科研基金资助项目(K1503060217)

摘　　要：为了加快无源定位速度,提高定位精度和滤波算法的稳定性,提出一种基于拟蒙特卡罗自适应高斯粒子滤波的机载无源定位算法.利用拟蒙特卡罗积分技术优化采样粒子在状态空间中的分布特性,降低积分误差,提高滤波精度,并且根据预测粒子在状态空间中的分布情况实时自适应调整下一次滤波所需的粒子数,减少冗余粒子,在保证滤波精度的同时有效地提高了算法的运行效率.将所提算法应用于机载无源定位系统,仿真结果验证了该算法的有效性.To meet the requirements of higher location speed,stability and accuracy in the air-borne passive location,a quasi Monte-Carlo adaptive Gaussian particle filter is proposed.The deterministic samples are chosen according to quasi Monte-Carlo integration to explore the state space more efficiently,so that the integration error is reduced and the filter accuracy is improved.Predicting the distribution of the particles in the state space,the number of particles for the next time is adapted real-timely,and the redundant particles are reduced.Therefore,the efficiency of the filter is improved while the accuracy is guaranteed.Simulation results show the availability of this filter.

关 键 词：无源定位 拟蒙特卡罗 粒子滤波 

分 类 号：TN957.51[电子电信—信号与信息处理]