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[Software Engineering] documentation DL : 0: 详细讲解了卡尔曼滤波器及EKF,UKF,IMM等滤波器，有例子，有仿真-Explain in detail the Kalman filter and EKF, UKF, IMM and other filters, there are examples, a simulation
Date : 2026-01-01 Size : 808kb User : 李雨石
[Software Engineering] IMM DL : 0: 本文针对SMM中著名的交互式多模型(IMM)估计器，通过将IMM看作是输人交互和子滤波器申联，分析了具有m个参数的MTP矩阵，给出了六条不依赖于应用环境及子滤波器设计的结论-In this paper, SMM Interacting Multiple Model (IMM) estimator, analyzed by the IMM as input interaction and sub-filters Shenlian MTP matrix with m parameters, six does not depend on the application environment and sub-filter design to the conclusion
Date : 2026-01-01 Size : 209kb User : tc
[Software Engineering] IMM_UKF DL : 1: 在主/被动雷达双传感器目标跟踪背景下, 提出一种基于IMM- UKF 滤波的加权数据融合算法。-A data fusion algorithm using IMM-UKF is presented based on active/ passive radar target tracking. The algorithm is established in terms of IMM( interact ing mult iple model) and UKF( unscented Kalman filter) .
Date : 2026-01-01 Size : 326kb User : 成晓东
[Software Engineering] IMM-track DL : 0: 在滤波估计方面，针对增益矩阵计算运算量大的问题，采用并行滤波器，提出基于机动检测理论的算法。算法复杂度低，易于工程实现，算法在复杂度上有很大的降低，但过程噪声对跟踪性能影响较大。因此，引进机动检测策略，结合不同过程噪声下的算法，能有效降低运算时间，提高跟踪精度。 -Adaptive template update strategy which can adjust the reference template based on the changes of the tracking target is used to improve the stability of target tracking. The simulation results indicate that the algorithm can quickly adjust the reference template according to the changes of the shape size and position and the target is tracked stably and real-time. The target also can be tracked efficaciously， when it is occluded.
Date : 2026-01-01 Size : 6.5mb User : 陈想
[Software Engineering] doc DL : 0: 交互多模型，该算法在机动目标跟踪的效果仿真，理论清晰简洁，初学者必选论文-IMM for applicatin
Date : 2026-01-01 Size : 1.54mb User : yuan