自适应混合多模算法在机动目标跟踪中的应用
APPLICATION OF ADAPTIVE INTERACTING MULTIPLE MODEL ALGORITHM FOR TRACKING A MANOEUVRING TARGET
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摘要: 本文介绍了用于机动目标跟踪的自适应混合多模算法。这个算法不需要预先定义模型。它利用一个二级卡尔曼滤波器来估计目标的加速度。这个加速度被用于混合多模算法中具有不同确定性加速度的子滤波器中。文中给出了自适应混合多模算法的一个计算机模拟结果并与无自适应混合多模算法的结果进行了比较。
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关键词:
- 机动目标; 算法; 跟踪
Abstract: The paper describes an Adaptive Interacting Multiple-model(AIMM) algorithm for use in manoeuvring target tracking. The algorithm does not need predefined models. A two-stage Kalman estimator is used to estimate the acceleration of the target. This acceleration value is then fed to the subfilters in an Interacting Multiple Model (IMM) algorithm where the subfilters have different acceleration parameters. The simulation results of the performance of the AIMM algorithm and that of the IMM algorithm are given. -
[1J Blackman S S. Multiple-target Tracking With Radar Applications, Dedham: Artech House, Inc. 1986, Chapter 3.[2]Blom H A, Bar-shalom Y. The interacting multiple model algorithm for systems with Markovian switching coefficients. IEEE Trans. on AC, 1988, AC-33(8): 780-785.[3]Munir A, et al. Adaptive interacting multiple model algorithm for tracking a manoeuvring target. IEE Proc-F, 1995, 142(1): 11-16.[4]Atherton D P, H J Lin. Parallel implemention of IMM tracking algorithm using transputers. IEE Proc-F,1994, F-141(6): 325-332.[5]Kalata P R. The tracking index: A generalized parameter for - and - target trackers[J].IEEE Trans. on Aerosp. Electron. Syst.1984, AES-20(2):174-182
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