自適應(yīng)混合多模算法在機(jī)動(dòng)目標(biāo)跟蹤中的應(yīng)用
APPLICATION OF ADAPTIVE INTERACTING MULTIPLE MODEL ALGORITHM FOR TRACKING A MANOEUVRING TARGET
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摘要: 本文介紹了用于機(jī)動(dòng)目標(biāo)跟蹤的自適應(yīng)混合多模算法。這個(gè)算法不需要預(yù)先定義模型。它利用一個(gè)二級(jí)卡爾曼濾波器來估計(jì)目標(biāo)的加速度。這個(gè)加速度被用于混合多模算法中具有不同確定性加速度的子濾波器中。文中給出了自適應(yīng)混合多模算法的一個(gè)計(jì)算機(jī)模擬結(jié)果并與無自適應(yīng)混合多模算法的結(jié)果進(jìn)行了比較。
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關(guān)鍵詞:
- 機(jī)動(dòng)目標(biāo); 算法; 跟蹤
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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