弹道环境下的陀螺/GPS组合姿态测量方法研究
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摘要
发展低成本的有控弹箭是提高常规火炮武器系统射击精度的重要途径之一。为提高制导炮弹外弹道姿态测量精度,从而对其实施精准的弹道控制,本文围绕低成本MEMS陀螺姿态测量以及姿态非线性滤波技术中遇到的一些基础理论和问题,结合弹道学理论展开分析和研究。
首先建立了制导炮弹的刚体运动模型。通过对模型进行数值计算,解算出一条理论弹道,该弹道一方面为后面模拟弹载传感器测量值提供依据,另一方面也作为考虑测量误差的姿态标定值与估计值的对比基准,以评定标定与滤波算法精度。
针对低速旋转尾翼弹的弹道特性,分别提出基于忽略攻角和动力平衡角近似攻角假设条件下的飞行姿态空中标定方法。根据建立的弹道模型,研究低旋尾翼弹攻角运动特性,充分利用地面弹道试验数据和飞行测量数据,提出了由动力平衡角近似攻角来求解弹丸飞行姿态,推导出近似攻角假设下的姿态标定数学模型。同样基于忽略攻角假设,建立了弹箭简易飞行姿态标定模型,并通过仿真对比两种模型精度。在弹道滑翔段考虑平衡攻角的影响,研究了稳态飞行条件下的姿态角标定方法。本文简要分析研究了适用于全弹道的陀螺积分算法,并提出了利用姿态标定抑制陀螺积分产生的累积误差的方法。
建立了炮弹攻角、侧滑角与滚转角的非线性姿态滤波模型。以炮弹飞行时的攻角、侧滑角与滚转角为状态变量,结合弹道飞行参数与MEMS陀螺/GPS测量数据,建立了非线性姿态滤波估计状态方程与量测方程。模型充分考虑了弹道参数的可变性和随机测量噪声,通过多种滤波估计方法对模型进行数值仿真,对比仿真结果得到了适用于姿态估计模型的最优算法。
研究了MEMS角速率陀螺的一般工作原理与测量误差形成的原因,利用时间序列方法对陀螺随机误差进行建模补偿,去除噪声中的周期项、趋势项等,获得了正态分布的随机噪声序列,以便利用滤波方法进行补偿。提出了利用小波神经网络方法对陀螺输出数据进行建模分析的思路,通过仿真建模得到了陀螺输出预测值。利用小波滤波与多分辨率分解理论,对陀螺输出噪声进行滤波补偿,进行仿真试验获取了最优小波基函数和尺度函数。
在有限条件下开展了半实物仿真试验研究。利用三轴飞行姿态仿真转台和MEMS角速率陀螺,设计仿真试验方法。以弹道模型理论计算数据作为转台控制参数,对陀螺输出数据进行采样和预处理,并将结果代入姿态标定数学模型和非线性滤波估计模型,得到了令人满意的姿态标定与滤波估计结果,在半实物仿真环境下验证了姿态标定模型和滤波估计模型的有效性及精度。
The development of low-cost controlled missile is one important way to improve firing accuracy of conventional gun weapon systems. In order to improve the guided projectile flight attitude measurement precision then to achieve accurately trajectory control, this paper focuses on some of the basic theory and problems encountered in the low-cost MEMS gyroscope attitude measurement and attitude nonlinear filtering techniques, combined with ballistics theory to analyze and research.
This paper firstly established a model of rigid body motion of the guided projectile. By the numerical calculation of the model to obtain a theoretical trajectory, the theoretical trajectory on the one hand provide the basis for the simulation of the onboard sensor measurements, on the other hand, also as an attitude comparison benchmark of estimated and calibration values considering measurement error, to assess the precision of the calibration and filter.
Aiming at the low-speed rotary projectile ballistic characteristics, this paper presents an inflight calibration method based on the assumptions of the approximate attack angle with dynamic balance angle and zero. According to the established trajectory model, motion characteristics of low-spin tail projectile angle of attack were studied. Make full use of the ground ballistic test data and flight measurement data, the approximate angle of attack by the dynamic balance angle was used to solve the bullet attitude, and then attitude calibration mathematical model is derived under the assumption. Also based on the assumption of zero angle of attack, establish the missile simple flight attitude of the calibration model, and contrast the precision of the models through simulation. In the trajectory of gliding, the initial calibration method of attitude angles has been proposed by consider the impact of the balanced angle of attack. The article also analyzed the gyro integration algorithm for the whole trajectory and a method to suppress gyro integral accumulated error with attitude calibration.
The nonlinear attitude filter model has been built with the angle of attack, sideslip angle and roll angle. With the angle of attack, the sideslip angle and roll angle as the state variables, the nonlinear attitude filter estimated state equations and measurement equations were established combined with ballistic parameters and the MEMS gyroscope and GPS measurement data. The models take full account of the variability of the trajectory parameters and gyro random measurement noise. Optimal algorithm for attitude estimation model has been obtained by comparing a variety of numerical simulation results.
Researched on MEMS angular rate gyro general principle and measurement error causes, using the time series method for gyro random error modeling and compensation, removed the periodic terms and the trend term in the noise, this article has received a normal distribution random noise sequence in order to take advantage of filtering methods to compensate. Putting forward the idea of using wavelet neural network modeling and analysis of the gyro output data, a high-precision of predictive value for gyro output has been given through simulation modeling. Using of wavelet filtering and multi-resolution decomposition theory for the gyro output noise filter compensation, simulation experiments have been made to obtain the optimal wavelet basis function and scaling function.
Semi physical simulation research has been conducted under laboratory conditions. Using three axis flight attitude simulation platform and MEMS angular rate gyro designed simulation test method. According to the theory of ballistic data as control parameters, the gyro output data was sampled and pretreated. The results were brought into the attitude calibration model and nonlinear filtering estimation model, and it obtained the satisfactory attitude calibration and estimation results. The semi-physical simulation test verified the validity and accuracy of the attitude calibration model and filtering the estimated model.
首先建立了制导炮弹的刚体运动模型。通过对模型进行数值计算,解算出一条理论弹道,该弹道一方面为后面模拟弹载传感器测量值提供依据,另一方面也作为考虑测量误差的姿态标定值与估计值的对比基准,以评定标定与滤波算法精度。
针对低速旋转尾翼弹的弹道特性,分别提出基于忽略攻角和动力平衡角近似攻角假设条件下的飞行姿态空中标定方法。根据建立的弹道模型,研究低旋尾翼弹攻角运动特性,充分利用地面弹道试验数据和飞行测量数据,提出了由动力平衡角近似攻角来求解弹丸飞行姿态,推导出近似攻角假设下的姿态标定数学模型。同样基于忽略攻角假设,建立了弹箭简易飞行姿态标定模型,并通过仿真对比两种模型精度。在弹道滑翔段考虑平衡攻角的影响,研究了稳态飞行条件下的姿态角标定方法。本文简要分析研究了适用于全弹道的陀螺积分算法,并提出了利用姿态标定抑制陀螺积分产生的累积误差的方法。
建立了炮弹攻角、侧滑角与滚转角的非线性姿态滤波模型。以炮弹飞行时的攻角、侧滑角与滚转角为状态变量,结合弹道飞行参数与MEMS陀螺/GPS测量数据,建立了非线性姿态滤波估计状态方程与量测方程。模型充分考虑了弹道参数的可变性和随机测量噪声,通过多种滤波估计方法对模型进行数值仿真,对比仿真结果得到了适用于姿态估计模型的最优算法。
研究了MEMS角速率陀螺的一般工作原理与测量误差形成的原因,利用时间序列方法对陀螺随机误差进行建模补偿,去除噪声中的周期项、趋势项等,获得了正态分布的随机噪声序列,以便利用滤波方法进行补偿。提出了利用小波神经网络方法对陀螺输出数据进行建模分析的思路,通过仿真建模得到了陀螺输出预测值。利用小波滤波与多分辨率分解理论,对陀螺输出噪声进行滤波补偿,进行仿真试验获取了最优小波基函数和尺度函数。
在有限条件下开展了半实物仿真试验研究。利用三轴飞行姿态仿真转台和MEMS角速率陀螺,设计仿真试验方法。以弹道模型理论计算数据作为转台控制参数,对陀螺输出数据进行采样和预处理,并将结果代入姿态标定数学模型和非线性滤波估计模型,得到了令人满意的姿态标定与滤波估计结果,在半实物仿真环境下验证了姿态标定模型和滤波估计模型的有效性及精度。
The development of low-cost controlled missile is one important way to improve firing accuracy of conventional gun weapon systems. In order to improve the guided projectile flight attitude measurement precision then to achieve accurately trajectory control, this paper focuses on some of the basic theory and problems encountered in the low-cost MEMS gyroscope attitude measurement and attitude nonlinear filtering techniques, combined with ballistics theory to analyze and research.
This paper firstly established a model of rigid body motion of the guided projectile. By the numerical calculation of the model to obtain a theoretical trajectory, the theoretical trajectory on the one hand provide the basis for the simulation of the onboard sensor measurements, on the other hand, also as an attitude comparison benchmark of estimated and calibration values considering measurement error, to assess the precision of the calibration and filter.
Aiming at the low-speed rotary projectile ballistic characteristics, this paper presents an inflight calibration method based on the assumptions of the approximate attack angle with dynamic balance angle and zero. According to the established trajectory model, motion characteristics of low-spin tail projectile angle of attack were studied. Make full use of the ground ballistic test data and flight measurement data, the approximate angle of attack by the dynamic balance angle was used to solve the bullet attitude, and then attitude calibration mathematical model is derived under the assumption. Also based on the assumption of zero angle of attack, establish the missile simple flight attitude of the calibration model, and contrast the precision of the models through simulation. In the trajectory of gliding, the initial calibration method of attitude angles has been proposed by consider the impact of the balanced angle of attack. The article also analyzed the gyro integration algorithm for the whole trajectory and a method to suppress gyro integral accumulated error with attitude calibration.
The nonlinear attitude filter model has been built with the angle of attack, sideslip angle and roll angle. With the angle of attack, the sideslip angle and roll angle as the state variables, the nonlinear attitude filter estimated state equations and measurement equations were established combined with ballistic parameters and the MEMS gyroscope and GPS measurement data. The models take full account of the variability of the trajectory parameters and gyro random measurement noise. Optimal algorithm for attitude estimation model has been obtained by comparing a variety of numerical simulation results.
Researched on MEMS angular rate gyro general principle and measurement error causes, using the time series method for gyro random error modeling and compensation, removed the periodic terms and the trend term in the noise, this article has received a normal distribution random noise sequence in order to take advantage of filtering methods to compensate. Putting forward the idea of using wavelet neural network modeling and analysis of the gyro output data, a high-precision of predictive value for gyro output has been given through simulation modeling. Using of wavelet filtering and multi-resolution decomposition theory for the gyro output noise filter compensation, simulation experiments have been made to obtain the optimal wavelet basis function and scaling function.
Semi physical simulation research has been conducted under laboratory conditions. Using three axis flight attitude simulation platform and MEMS angular rate gyro designed simulation test method. According to the theory of ballistic data as control parameters, the gyro output data was sampled and pretreated. The results were brought into the attitude calibration model and nonlinear filtering estimation model, and it obtained the satisfactory attitude calibration and estimation results. The semi-physical simulation test verified the validity and accuracy of the attitude calibration model and filtering the estimated model.
引文
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