Improved multi-target tracking algorithm based on SMC-CBMeMBer for the airborne Doppler radar

Abstract

To effectively suppress clutter in airborne Doppler radar and improve multi-target tracking (MTT) performance, this study proposes an improved MTT algorithm based on Sequential Monte Carlo Cardinality Balanced Multi-target Multi-Bernoulli (SMC-CBMeMBer) filter. Firstly, the filter introduces Doppler information in the measurement process. Then, the more accurate likelihood function and state estimation are deduced again in the filtering update stage. Finally, the influence of particles number on the algorithm is analysed. Through the simulation experiment, when the number of particles is selected properly, the algorithm can more effectively suppress the clutter and improve the target tracking performance.

Keywords

• monte carlo methods
• target tracking
• doppler radar
• filtering theory
• radar tracking
• radar clutter
• interference suppression
• airborne radar
• state estimation
• state estimation
• filtering update stage
• smc-cbmember
• airborne doppler radar
• sequential monte carlo cardinality balanced multitarget multibernoulli filter
• doppler information
• multitarget tracking algorithm
• likelihood function
• mtt algorithm