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2下载:
文件夹中NPFMain.m为滤波算法主运行程序,CRLBCompute.m为计算CRLB并且画出CRLB、NPF、EKF/IMM-EKF滤波误差(均值和均方差)曲线。-folder NPFMain.m filtering algorithm for the main operating procedures, CRLBCompute.m estimator to calculate and paint estimator, NPF, EKF / IMM - EKF filter error (m
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根据二维空间内目标作匀速直线运动和匀速圆周运动的特点,在建立目标运动模型和观测模型的基础上采用基于交互多模算法(IMM)的卡尔曼滤波器对机动目标进行跟踪。仿真结果表明,该算法不仅能够对匀速直线运动和匀速圆周运动的目标进行跟踪,而且在运动模型发生变化时,滤波误差也比较小。
关键词:卡尔曼滤波器;目标跟踪;机动;交互多模(IMM)
-two-dimensional space under target for uniform linear motion and uniform circula
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本程序是matlab编写的imm(交互式多模型算法)目标跟踪程序。这种方法的特点是在各模型之间“转换”,自动调节滤波带宽,和适合机动目标的跟踪。,This program is matlab written imm (interacting multiple model algorithm) target tracking program. This method is characterized among the various models " conversion" ,
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交互式多模型算法卡尔曼滤波仿真代码,程序中采用了两个模型-Interacting multiple model Kalman filter algorithm simulation code, the program uses two models
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用于机动目标跟踪的交互式多模型算法完整实现程序,无BUG-For maneuvering target tracking interactive multiple model algorithm for the full realization of program, no BUG
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使用EKF、UKF、PF、EKPF算法实现简单的单个目标跟踪滤波-Using EKF, UKF, PF, EKPF simple tracking algorithm filter
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信息融合滤波算法,基于IMM完成匀速—加速—匀速单运动目标跟踪。-Information fusion filter algorithm based on IMM to complete the uniform and accelerate uniform single moving target tracking.
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结合雷达跟踪的空中目标的实际情况,针对目标运动模型中的线性运动和非线性运动,分别设计了两种模型,并用马尔科夫状态转移矩阵实现IMM算法。最后对交互多模型卡尔曼滤波算法进行了Matlab仿真及结果分析。-Combined with radar tracking air targets, for linear and non-linear movement of target motion model, two models were designed and used a Markov state
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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 f
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IMMKF算法MATLAB程序,基于IMM算法的目标跟踪,包括INTERACTING,卡尔曼滤波,模型跟新-MATLAB IMMKF algorithm, based on IMM algorithm of target tracking, including INTERACTING, kalman filter, with the new model
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目标跟踪算法,运用交互多模型算法的卡尔曼滤波器。有文档,有程序,适用于初学者-Target tracking algorithm, using interactive multiple model Kalman filter algorithm
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1.IMM.m
主要功能:
(1)IMM算法的实现;
(2)画出目标轨迹与利用IMM算法跟踪目标的轨迹;
(3)画出位置误差与速度误差;
(4)画出模型混合概率图。
2.Target_track.m
主要功能:
实现目标轨迹的产生。
3.Model_mix.m
主要功能:
实现IMM算法下,各模型的估计融合。
4.Kalman.m
主要功能:
实现模型的条件滤波,以及似然函数的输出。-1.IMM.m main functions: (1)
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载机跟踪高速高机动目标时,使用交互式多模型算法,该算法中又用平方根容积卡尔曼滤波器进行滤波。-When the carrier aircraft tracking high-speed maneuvering targets, using interactive multiple model algorithm in the Kalman filter is also used to filter the square root of the volume.
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采用组合权重的交互多模型算法,实现基于KALMAN滤波的而模型滤波,并与常规IMM算法对比。(The model is filtered by the KALMAN filter based on the interacting multiple model algorithm with combination weights, and compared with the conventional IMM algorithm.)
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