CAJ | 학술논문

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。
침대저신조비하약목표적검측여근종문제，제출료일충기우량급량측경신적입자려파기검측전근종산법。산법재입자려파상태경신지후，재기상태고계부근，인입잡이만려파광가，진행제2급적량측경신，제고료입자휴대신식적이용정도。방진결과표명，신산법획득료경호적검측화근종성능。
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.