Research Of Optimization Method For Target Tracking Based On Particle Filter

With the widespread application and rapid development of target tracking technology,target tracking has become one of the hotspots in the field of intelligent information processing.Target tracking technology has important application value in such fields as intelligent monitoring,visual navigation,intelligent transportation,human-computer interaction,defense reconnaissance,augmented reality and video editing.There are many algorithms for target tracking.This paper selects the particle filter algorithm for research and discussion.Particle filter is a filter processing technology with great advantages in nonlinear,non-Gaussian systems.The idea of particle filtering is based on Monte Carlo sampling,using the random particles generated by the continuous sampling to approximate the posterior probability distribution of the state.In recent years,with the study of relevant theories,many effective and improved algorithms have been continuously proposed,making particle filters widely used in signal,image processing,target tracking and other fields.At present,particle filter technology has become a research hotspot of filter theory.The application of particle filter technology for target tracking often encounters problems such as insufficient feature description,the difficult tracking of complex motion or scale change,the requirement of precision and real-time.In order to reduce the impact of these issues on tracking,this paper combines the basic particle filter with multi-feature fusion method to design a multi-feature fusion particle filter tracker and combines the particle filter with the kalman filter algorithm to design an kalman particle filter tracker.Then these designed tracking systems are applied to the actual tracking scenario.Experimental results verify that improved particle filter trackers have better processing performance.The multi-feature fusion particle filter has better accuracy and robustness,and the kalman particle filter algorithm can improve the accuracy of the target tracking system without increasing the computation complexity too much.In this paper,the particle filter algorithm used in target tracking is discussed in detail,and the models and optimization methods used are also carefully analyzed and designed.These works are valuable for future engineering practice.