based on measurement fusion theory, a target-tracking algorithm which fused measurements of nonlinear system with dissimilar sensors in case of arbitrary correlated noises is developed.
基于测量融合理论提出了一种任意相关噪声异类传感器非线性系统目标跟蹤算法。
based on the linear unbiased minimum variance estimation theory, an asynchronous fusion algorithm that fused the state vector of linear system with arbitrary correlated noises is developed.
针对机动目标跟蹤中常见的量测转换问题,提出了一种基于球坐标系下最优线性无偏估计滤波的交互多模型算法。
the track association and fusion technique of synchronized multi-sensor tracking system in case of correlated noises is developed.
本文研究了量测噪声与系统噪声相关情况下同步多传感跟蹤系统的航迹关联及融合技术。
based on the linear unbiased minimum variance estimation theory, an asynchronous fusion algorithm that fused the state vector of linear system with arbitrary correlated noises is developed.
基于线性无偏最小方差估计理论,提出了一种任意相关噪声异类传感器非线性系统状态矢量融合算法。
based on linear unbiased minimum variance estimation theory, a fusion algorithm which fused the state vector of nonlinear systems with dissimilar sensors with arbitrary correlated noises is developed.
提出了具有一般相关量测噪声的线性系统的平滑估计算法 ,该算法是在系统正向和逆向滤波估计结果的基础上 ,利用线性无偏最小方差估计获得的 。
based on linear unbiased minimum variance estimation theory, a fusion algorithm which fused the state vector of nonlinear systems with dissimilar sensors with arbitrary correlated noises is developed.
基于线性无偏最小方差估计理论,提出了一种任意相关噪声异类传感器非线性系统状态矢量融合算法。