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基于MS-IMMIKF的MEMS陀螺輸出信號(hào)消噪處理
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國(guó)家自然科學(xué)基金項(xiàng)目(51175267,、51475243)


MEMS Gyro’s Output Signal De-noising Processing Based on MS-IMMIKF
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    摘要:

    陀螺用于感知穩(wěn)定平臺(tái)相對(duì)于慣性空間的角速率,,進(jìn)而得到穩(wěn)定平臺(tái)在慣性空間的姿態(tài),通過(guò)反饋穩(wěn)定平臺(tái)伺服控制機(jī)構(gòu)相應(yīng)的控制量來(lái)實(shí)現(xiàn)對(duì)穩(wěn)定平臺(tái)的穩(wěn)定控制。通過(guò)分析陀螺隨機(jī)誤差對(duì)穩(wěn)定平臺(tái)精度影響,,提出了一種新的陀螺隨機(jī)漂移處理方法。首先針對(duì)機(jī)動(dòng)跟蹤領(lǐng)域的Singer模型中人為設(shè)定機(jī)動(dòng)頻率α的不合理性,,對(duì)機(jī)動(dòng)頻率α進(jìn)行在線估計(jì),,提出基于Modified Singer(MS)模型直接對(duì)陀螺輸出進(jìn)行建模的方法,;在此基礎(chǔ)上建立基于交互式多模型(IMM)的改進(jìn)卡爾曼濾波算法(MS-IMMIKF)對(duì)陀螺輸出隨機(jī)誤差進(jìn)行處理,,并對(duì)交互式多模型的改進(jìn)卡爾曼濾波(IKF)進(jìn)行理論分析和推導(dǎo);通過(guò)數(shù)值仿真分析和穩(wěn)定平臺(tái)中某型號(hào)陀螺試驗(yàn)驗(yàn)證和仿真計(jì)算得出,,靜態(tài)濾波后均方根誤差達(dá)到0.0227°/s,,證明了該方法對(duì)陀螺漂移處理的有效性與可行性;最后通過(guò)穩(wěn)定平臺(tái)動(dòng)靜態(tài)穩(wěn)定試驗(yàn)表明,,MS-IMMIKF濾波算法對(duì)提高穩(wěn)定平臺(tái)精度有效且實(shí)用,。

    Abstract:

    By controlling the amount of feedback to the corresponding stable platform servo control mechanism to achieve stability control for stabilizing the platform, gyro is used to measure angular velocity of stabilized platform with respect to inertial space and then get the gesture of stabilized platform in inertial space. By analyzing the influence of gyro random error on the stabilized platform accuracy in detail, a processing method for gyro random drift was proposed. Firstly, owing to the values of the parameter α is artificially unreasonable of the Singer model in the field of motor tracking, the parameter of α in real time was estimated adaptively, and a new method of gyro modeling output module directly was established based Modified Singer (MS); secondly, on the basis of the established output model, an improved Kalman filter (IKF) based on interacting multiple model (IMM) was applied to the gyros output random error processing, and the theoretical analysis and derivation of the algorithm were explained in detail. Through numerical simulations and verification experiments of a certain type of gyro stabilized platform analysis, the static filter root mean square error is only 0.0227°/s, and this method was proved to be feasible and effective with the gyro drift treatments;finally, through the dynamic and static steady experiments of gyro stabilized platform, the MS-IMMIKF filtering algorithm was proved to be effective and practical for improving the accuracy of the stable platform. The dynamic and static steady experiments of gyro stabilized platform results show that the accuracy of the stable platform could be controlled within error of 3° and 25° respectively after the MS-IMMIKF algorithm filtering.

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孟紅波,王昌明,張愛(ài)軍,包建東,何博俠.基于MS-IMMIKF的MEMS陀螺輸出信號(hào)消噪處理[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2016,47(5):372-379. Meng Hongbo, Wang Changming, Zhang Aijun, Bao Jiandong, He Boxia. MEMS Gyro’s Output Signal De-noising Processing Based on MS-IMMIKF[J]. Transactions of the Chinese Society for Agricultural Machinery,2016,47(5):372-379.

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  • 收稿日期:2015-12-15
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  • 在線發(fā)布日期: 2016-05-10
  • 出版日期: 2016-05-10
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