两级量测更新的粒子滤波检测前跟踪算法∗

摘要

针对低信噪比下弱目标的检测与跟踪问题，提出了一种基于两级量测更新的粒子滤波器检测前跟踪算法。算法在粒子滤波状态更新之后，在其状态估计附近，引入卡尔曼滤波框架，进行第2级的量测更新，提高了粒子携带信息的利用程度。仿真结果表明，新算法获得了更好的检测和跟踪性能。%A particle filter track-before-detect algorithm based on two-stage measurement update was proposed,to deal with detection and tracking a dim target in low signal-to-noise ratio. After updating of the posterior state in par-ticle filter,by using Kalman filter,a second-stage measurement update is executed. This improves the degree of using of particles-contained information. Simulation results show that the new algorithm obtains better detection and tracking performance.