结合Sage-Husa滤波的合成孔径声呐多传感器组合运动补偿算法

在运动测量设备噪声统计特性不确定的情况下,提出结合Sage-Husa滤波的合成孔径声呐多传感器组合运动补偿方法。使用Sage-Husa卡尔曼滤波处理多种异类运动传感器的数据,自适应估计声呐速度的最优值,计算实际航迹与理想航迹之间的横荡误差和升沉误差,最后通过时延校正原始回波数据。仿真结果表明,Sage-Husa滤波对运动误差估计精度至少提高37%,运动补偿后,目标峰值旁瓣比和积分旁瓣比有所降低,峰值旁瓣比接近理论值.湖试数据处理结果表明,目标能量分散的情况有所改善,能量集中在主瓣,散焦得到抑制。Sage-Husa滤波在多传感器系统噪声先验知识缺失的条件下,能减小运动数据估计误差,提高运动补偿的准确性。 

Motion compensation algorithm with integrated multi-sensor for synthetic aperture sonar via Sage-Husa filter

With the noise statistics of motion measurement devices unknown,a motion compensation method for synthetic aperture sonar based on integrated multi-sensor via Sage-Husa filter is proposed.The Sage-Husa filter is taken to deal with the data from the different types of sensors,estimating the optimal value of the sonar velocity adaptively.Then the sway and heave errors between the actual track and the ideal track are calculated.Raw data can be corrected on the basis of time delay transformed from the track deviation at last.Simulation results confirm that the estimation accuracy of motion errors by Sage-Husa filter gets improved at least thirty-seven percent.Both the peak side lobe ratio and the integral side lobe ratio of the target decline obviously,the peak side lobe ratio is close to the ideal value.The field experiment results confirm that the problem of the target energy dispersion gets solved effectively and the energy are focused at the main lobe,the defocusing gets restrained.The Sage-Husa filter reduces the estimation error of the motion data without the priori knowledge of the multi-sensor system's noise statistics,which results in a better performance of the motion compensation.