基于多传感器多模型信息，给出了目标状态基于全局信息融合估计的一种新算法，并通过计算机仿真验证了这种算法的有效性。
Based on Multi_sensor Multi_model information, we present a new algorithm based on total information fusion estimation on target state. We prove the validity of this algorithm by computer.
采用卡尔曼滤波器对目标进行跟踪时，目标初始状态估计是影响初始阶段跟踪精度的一个重要原因。
When using Kalman Filter to track a target, estimation of the initial state of the target is an important factor influencing tracking precision in the initial phase.
由于选择了新的机动加速度量，从而得出线性的状态方程，由机动指令的实时估计得到机动目标自适应跟踪卡尔曼滤波器。
A linear state equation is got from selection of maneuvering acceleration. The adaptivity of adaptive tracking Kalman filter is represented by estimation of maneuvering commander at real time.
应用推荐