反潜CGF系统中吊声传感器的建模方法

Modeling Method of Dipping Sonar Sensor in Anti-submarine CGF System

提出一种计算机生成兵力(CGF)系统中传感器模型的建模方法。以声纳方程为基础,综合考虑海洋环境及目标声特性,分别建立主、被动式的吊声传感器模型。利用海洋环境数据训练径向基神经网络(简称RBF网络),实时解算不同环境参数时的噪声级。在主动式吊声模型中,考虑声纳的波束方向,便于对目标进行定向等运动分析。通过MATLAB仿真,验证此模型的性能指标优于现有模型的性能,有效为反潜CGF系统服务。

The modeling method of the sensors was proposed in the Computer Generate Force (short for CGF) system. Considering the state of the target and oceanic circumstance synthetically, the active and passive dipping sonar sensor models were brought forward based on the sonar equation. To train the Radial Based Function nerve network (for short RBF network) using the datum of the oceanic circumstance, noise level was as the result of the network when the different oceanic circumstance inputs the network in time. The Orientation of the sonar beam was considered in the active dipping sonar sensor model to complete the target movement analysis such as differentiating orientation. The models were simulated and validated by using MATLAB. The results of the simulation precede the capability of the existing models; furthermore, the model is good for the anti-submarine CGF system.