CAJ | 학술논문

针对非均匀稀疏采样环境下目标跟踪中的非线性滤波问题，提出了一种基于Gauss-Hermite积分和目标特性辅助的积分粒子滤波新方法（AQPF）。在该方法中，构建了基于Gauss-Hermite积分的积分点概率密度函数作为重要性密度函数，同时，在时间更新阶段引入目标观测、目标观测的有效时间间隔、目标速度等目标特性，综合改善滤波器中预测粒子和预测协方差估计的准确性和粒子的多样性，有效提高目标状态的估计性能。实验结果表明，提出方法的估计性能要明显好于无迹kalman滤波（UKF）、积分kalman滤波（QKF）、粒子滤波（PF）、辅助粒子滤波（APF）和高斯粒子滤波（GPF ），能够有效对目标状态进行估计。
침대비균균희소채양배경하목표근종중적비선성려파문제，제출료일충기우Gauss-Hermite적분화목표특성보조적적분입자려파신방법（AQPF）。재해방법중，구건료기우Gauss-Hermite적분적적분점개솔밀도함수작위중요성밀도함수，동시，재시간경신계단인입목표관측、목표관측적유효시간간격、목표속도등목표특성，종합개선려파기중예측입자화예측협방차고계적준학성화입자적다양성，유효제고목표상태적고계성능。실험결과표명，제출방법적고계성능요명현호우무적kalman려파（UKF）、적분kalman려파（QKF）、입자려파（PF）、보조입자려파（APF）화고사입자려파（GPF ），능구유효대목표상태진행고계。
For the nonlinear filtering problem of target tracking in aperiodic sparseness sampling environment ,a novel auxil-iary quadrature particle filter(AQPF) based on Gauss-Hermite quadrature and target characteristics is proposed .In the proposed al-gorithm ,a set of quadrature point probability densities based on the Gauss-Hermite quadrature is proposed to approximate the impor-tant density function .At the same time ,the proposed algorithm can incorporate target observation ,time interval of the target observa-tion and the target speed into the construction of important density function ,which can effectively enhance the diversity of samples and improve the performance .Finally ,the experimental results show that the performance of the proposed algorithm is better than these of the unscented Kalman filter(UKF) ,quadrature Kalman filter(QKF) ,particle filter(PF) ,auxiliary particle filtering(APF) and Gaussian particle filter(GPF) ,and can effectively estimate the target states .