顾及声线高度角的水下定位随机模型优化

Optimization on underwater positioning stochastic model based on sound ray elevation angle

先验随机模型本身的误差会给参数估计带来随机性影响,水下定位等权随机模型简单却不符合实际。基于这一事实,在水下声纳定位模型和随机模型基础上,讨论了随机模型不完善对参数估计的影响。考虑了影响定位主要误差源与高度角之间的关系,结合统计经验提出了基于声线高度角相关的水下定位随机模型。试验表明,优化后的高度角相关随机模型在定位精度上较等权随机模型有所提高。因此,在水下定位中,应减少低高度角观测值的权重,利用提出的随机模型可以减小高度角观测误差对定位精度的影响。

The error of the a priori random model itself will bring random influence to the parameter estimation,and the equal-weight Stochastic model for underwater positioning is simple but not practical.Based on the underwater sonar localization model and the stochastic model,this paper discusses the impact of the imperfect stochastic model on parameter estimation.Considering the relationship between the main error that affect the positioning accuracy and the elevation angle,combined with statistical experience,a stochastic model of underwater positioning based on the elevation angle is established.Experimental results show that the optimized elevation-angle-related random model has a greater improvement in positioning accuracy than the equal-weight random model.Therefore,the weight of low elevation angle observations should be reduced in underwater positioning.Using the random model proposed in this paper can reduce the impact of elevation angle observation errors on positioning accuracy.