MEMS IMU随机误差建模在SAR运动补偿中的应用

随着SAR小型化发展趋势，低精度小型化微机电系统惯性测量系统（MEMS IMU）在SAR运动补偿中越来越受到重视。鉴于MEMS IMU 中随机误差较大，为提高其短时间内相对运动测量精度，从IMU测量误差对SAR成像的影响分析出发，采用基于时间序列分析方法对MEMS IMU中随机误差进行建模，并构建Kalman方程对IMU原始数据进行了滤波处理，减小了随机误差，从而降低随机误差在合成孔径时间内对SAR运动补偿的影响。机载SAR飞行试验数据处理结果表明，此方法能够有效的减小随机误差，提高SAR图像聚焦质量。

Application of MEMS IMU random error modeling in SAR motion compensation

This is a kind of trend that the synthetic aperture radar (SAR) system needs mini aturization. With dramatically reduced cost, size, precision and weight, micro electromechanical system inertial measurement unit system (MEMS IMU) has played a major role in SAR motion compensation. It has to take measures to improve the measurement precision of the relative motion within a short time in view of a large random error in MEMS IMU. Firstly, the influence of measurement error on SAR imaging has been analyzed. Secondly, ARMA model has been set up by analyzed the unsystematic error using time series theory. And then, the Kalman equation has been designed and it has been used to filter the IMU raw data. It turns out that the method can be used to reduce the random error which can be helpful to reduce the influence of random noise on SAR motion compensation in a synthetic aperture time Airborne SAR flight test data processing result has proved that the method proposed in this paper can effectively decrease the random error, improve the SAR focusing image quality.