线性等式约束下的纯方位目标运动分析

Bearings-only target motion analysis with linear equality constraints

对于匀速直线运动的声源目标,为了缩短解算目标运动要素的时间,提高解算目标运动要素的精度,本文利用距离特征量导出了不同时刻间的目标距离关系,并将该距离关系转化为状态变量的两种线性约束,即硬约束和软约束。结合伪线性法,给出了两种改进的Kalman滤波算法,在理论上证明了硬约束条件下的状态估计优于软约束条件下的状态估计,软约束条件下的状态估计优于无约束条件下的状态估计。数值模拟和实验验证表明了新方法的可行性和有效性,随着目标方位方差变大,新方法的收敛时间和精度越来越优于经典方法。

In order to shorten the time and improve the precision of target motion analysis for a sound source target with constant velocity along a straight line, based on the distance characteristic variable, the target distance relation between two different times was derived. Moreover, this distance relation was transformed as linear constraints of state vector, named as strong constraints and soft constraints, respectively. Combining them with pseudo linear algorithm, two kind of improved Kalman filtering algorithms were obtained. They have theoretically demonstrated that the state estimator with soft constraint condition is not better than that with strong constraint condition, while it is better than that with unconstraint condition. The simulation results and experimental verification show that the new methods are feasible and the time and precision of the new algorithms are better than the conventional algorithm. It demonstrates that the new algorithms are effective.