从卫星SAR海洋图像中检测船目标

船在卫星ＳＡＲ海洋图像中一般是以亮点的形式出现。本文先简要地介绍了船目标在卫星ＳＡＲ海洋图像中的成像原理，在此基础上介绍了三种检测船目标的方法——窗口滤波方法、自适应阈值法、概率密度函数法，并运用实际的卫星ＳＡＲ海洋图像对这三种算法进行了测试。测试结果表明，后两种方法效果比较好。     

Robust cubature Kalman filter method for the nonlinear alignment of SINS

Nonlinear initial alignment is a significant research topic for strapdown inertial navigation system(SINS).Cubature Kalman filter(CKF)is a popular tool for nonlinear initial alignment.Standard CKF assumes that the statics of the observation noise are pre-given before the filtering process.Therefore,any unpredicted outliers in observation noise will decrease the stability of the filter.In view of this problem,improved CKF method with robustness is proposed.Multiple fading factors are introduced to rescale the obser-vation noise covariance.Then the update stage of the filter can be autonomously tuned,and if there are outliers exist in the observations,the update should be less weighted.Under the Gaussian assumption of KF,the Mahalanobis distance of the innovation vector is supposed to be Chi-square distributed.Therefore a judging index based on Chi-square test is designed to detect the noise outliers,determining whether the fading tune are required.The proposed method is applied in the nonlinear alignment of SINS,and vehicle experiment proves the effective of the proposed method.