利用信号自相关函数warping变换的浅海水下移动观测平台机动优化方法

水下移动观测平台的机动航路对纯方位目标运动分析方法的使用性能具有重要的影响。针对此问题,提出了一种利用信号自相关函数warping变换的浅海水下移动观测平台机动优化方法。该方法利用warping变换从接收信号自相关函数中提取与目标距离相关的简正波相干项的特征频率,进而估计距离特征量,再根据预估的目标初始距离范围估计目标运动态势范围。针对观测平台机动方式为匀速转弯运动的情况,以目标方位变化率为评价指标得到了观测平台在所估计的目标运动态势范围下的最优转弯角速率。在浅海Pekeris波导环境下的数值仿真结果和实验数据处理结果表明:方位变化率与纯方位扩展卡尔曼滤波算法的性能密切相关;利用warping变换可以有效地估计距离特征量;观测平台根据以方位变化率为评价指标得到的最优转弯角速率进行机动可以获得较好的目标跟踪性能,收敛时间较短,目标位置估计误差较小。 

Optimal mobile observation platform maneuver based on warping transform of signal autocorrelation function in shallow water

The underwater mobile observation platform maneuver trajectory has an important influence on the performance of the bearings-only target motion analysis method.Aiming at this problem,an optimal mobile observation platform maneuver method based on warping transform of signal autocorrelation function in shallow water is proposed.In order to estimate the distance characteristic,this method extracts the characteristic frequencies of the modal coherence items from signal's autocorrelation function using warping transform.Then this method estimates target motion situation based on the prior information of the initial target range.Aiming at the situation that the maneuvering mode of the observation platform is uniform turning motion,this method estimates the optimal turning angular rate within the estimated range of the target motion situation using the bearing rate as the evaluation index.The numerical simulation results in Pekeris waveguide and the sea trial results show that the bearing rate is closely related to the performance of bearings-only extended Kalman filter algorithm.Moreover,this method can estimate the distance characteristic effectively using warping transform.When the observation platform maneuvers with the optimal turning angular rate obtained by using the bearing rate as the evaluation index,this method can achieve better target tracking performance.The convergence time is shorter and the target position estimation error is smaller.