应用两步回归迭代算法校正数字式磁罗经误差

基于椭圆假设的参数估计目前是解决数字式磁罗经误差校正问题的较为先进的方法，然而对该方法中的非线性参数估计问题采取了扩展卡尔曼滤波的办法来解决，这造成误差在测量过程中的发散。提出了两步回归迭代算法来解决此问题的思路，即把待估计的非线性参数组合成线性参数，用卡尔曼滤波进行状态估计后，通过Causs-Newton法解得原非线性参数。实验结果证明了新方法的优越性。

Using Two-Step Regression Iterative Algorithm in Calibrating Digital Magnetometer's Error

Parameter estimation based on ellipse hypothesis is an advanced algorithm to calibrate error in digital compass, but it results in divergence in measurement due to linearise the non - linear parameter estimation using EKF. This paper proposes an error calibration strategy, using the two - step iterafive parameter estimation algorithm to solve this problem, which is combining the non - linear parameters into linear parameter, estimating fire states using Kalman Filter and then getting the original parameter using Gauss- Newton iterative algorithm. The emulational result proved its superiority.