基于双重采样粒子滤波的目标轨迹跟踪研究

摘要

In order to guarantee the real‐time performance and improve the accuracy of target tracking ,the model of double sampling particle filter is proposed .First of all , by using the particle aggregation technique ,the weighted average of the particle weights of the state space is used to form the aggregated particles .Then ,using the linear optimization to produce new particles ,the distribution of the particle in the state space is optimized , and the diversity of the particles is increased , and the accuracy of the algorithm is improved .The simulation results show that the algorithm proposed in this paper is accurate and robust .%为保证对目标轨迹跟踪的实时性，提高其精度，提出双重采样粒子滤波模型。首先，利用粒子聚合技术对状态空间的粒子权值进行加权平均处理，形成聚合粒子，使得粒子在状态空间内分布更为合理。然后，利用线性优化方法重新产生新的粒子，优化粒子在状态空间的分布特性，增加粒子的多样性，提高算法的精确性。经仿真验证，本文提出的算法较准确，鲁棒性也较高。