本文导出了在惯性坐标系内利用线性测量卡尔曼滤波器(LMKF)来估值海上机动目标的状态估值器。LMKF 可以用于非线性测量条件下的目标状态估值。同时,LMKF 的公式比延伸的卡尔曼滤波器(EKF)要容易推导得多。在飞机坐标系里用蒙特卡罗方法进行了大量的数学模拟。模拟结果表明,两种滤波器的估值误差相同,但是LMKF 只需要比较少的计算量。应用线性测量的方法,导出了在飞机地理水平面坐标系内的LMKF。该滤波器有较高的溶液精度和较少的计算量。 This paper derives a state estimator that estimates the maneuvering target at sea using a linear measurement Kalman filter (LMKF) in an inertial coordinate system. LMKF can be used for the estimation of target states under non-linear measurement conditions. At the same time, the formula for LMKF is easier to derive than the extended Kalman filter (EKF). In the aircraft coordinate system using Monte Carlo method for a large number of mathematical simulation. The simulation results show that the estimation errors of the two filters are the same, but LMKF only needs less computation. Using the method of linear measurement, the LMKF in the geographic coordinate system of the aircraft is derived. The filter has higher solution accuracy and less computation.