大噪声背景下目标方位预处理算法

Preparation Algorithm of Target Bearing in Background of Strong Noise

针对水下纯方位目标运动分析中方位信息存在较大观测误差的问题,提出了在大噪声背景下基于灰色系统的GM模型以及多项式模型的方位预处理算法,以减小目标方位观测的误差,提高水下目标运动参数解算的精度,并对比分析算法在不同初始距离和初始方位上的仿真效果,指出了不同模型的适用范围,最后根据仿真结果对模型的实际应用给出合理的建议。

According to the problem of large observation error existing in bearing information of underwater BTMA （ Bearingonly Target Motion Analysis） , preparation algorithms of bearing using the GM model based on grey system and the polynomial model are proposed to reduce the target bearing observation error in background strong noise, and to improve the computational accuracy of target state parameter of motion. The simulation results of algorithm are analysed by contrast in different initial ranges and bearings, and to get the suitable scope of different models, finally the reasonable advantages of application of the model are pointed out according to the simulation results.