Journal of Projectiles, Rockets, Missiles and Guidance >
A State Estimation Method Based on Interactive Multiple Model Particle Filter
Received date: 2011-02-26
Online published: 2025-05-30
In order to improve the state estimation performance which belongs to target tracking, the interactive multiple model particle filter (IMMPF) adopts IMM to describe target movement, and estimate the target state by particle filters. IMMPF can avoid estimation error caused by single motion model. It also overcomes the limitation of Kalman tracking filter. When the priori knowledge is inadequate, IMMPF can estimate target position, velocity and acceleration with appropriate error under different form of exercise. So IMMPF improves adaptability and robustness.
Key words： state estimation; particle filter; IMM
XIAO Yanghui , SHI Zelin , ZHAO Yongting . A State Estimation Method Based on Interactive Multiple Model Particle Filter[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2011 , 31(6) : 176 -178 . DOI: 10.15892/j.cnki.djzdxb.2011.06.012
| [1] | Arulampalam MS Maskell S Gordon N et al A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking[J]. IEEE Transactions on Signal Processing, 2002. 50(2): 174-188. |
| [2] | LIXR JILKOV V P A survey of maneuvering target tracking: Dynamic models[C]// Signal and Data Processing of Small Targets, SPIE Proc, 2000, vol. 4048: 212-235. |
| [3] | 彭可茂 申功璋 文传源. 机动目标状态估计器算法研究[J]. 北京航空航天大学学报, 2004, 30(3): 276-279. |
| [4] | Mazor E Averbuch A Bar-Shalom Y Dayan J Interacting multiple model methods in target tracking: A survey[J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(1): 103-123. |
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