摘要
在雷达回波的距离——多普勒数据上,建立了粒子滤波所需的系统动态模型和观测模型,将传统的点目标模型改进为更接近于实际的线形扩展目标模型,并推导出了新模型的似然比函数.同时,为了减少粒子数,对传统的粒子滤波(PF)算法进行了改进.由于模型的匹配和检测前跟踪(TBD)算法在时间上的积累功能,所提算法提高了雷达对低信噪比目标的检测概率.仿真结果表明,该算法能稳定地检测到信噪比为1 dB的目标.
The system dynamic model and measurement model in the particle filter（PF） are established in a sequence of radar range-Doppler measurements and a linear extended target model is proposed,which is more suitable for describing a maneuvering target than the conventional point target model.Furthermore,the likelihood ratio function of the new model is also derived.In addition,the conventional PF is improved here to reduce the number of particles.Due to the macthing between the proposed target model and the integration function of TBD algorithm over time,an improved probability of detection for the dim target is obtained.Simulation results demonstrate that the proposed method is capable of detecting and tracking a target with the SNR of 1dB stably.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2011年第2期99-104,共6页
Journal of Xidian University
基金
国家自然科学基金资助项目(60901065)
关键词
检测前跟踪
粒子滤波
扩展目标
似然比函数
track-before-detect
particle filter
extended target
likelihood ratio function
