基于新型主成分加权平均归一化法优选水下重力匹配导航适配区

本文开展了水下潜器重力匹配导航的匹配区适配性评价研究.第一，本文综合考虑了重力异常标准差、坡度标准差、粗糙度、重力异常差异熵、分形维数等重力场主要特征参数，联合主成分分析准则和加权平均原理，提出了新型主成分加权平均归一化法；第二，基于新型主成分加权平均归一化法，计算可评价重力异常基准图各区域匹配效果的总体特征参数指标，依据总体特征参数指标进行优良适配区、一般适配区和非适配区划分；第三，在相同条件下，在划分的优良适配区、一般适配区和非适配区内，分别进行重力匹配数值模拟验证比较，结果表明，优良适配区的重力匹配效果显著，匹配概率约为98%，匹配稳定性高，位置误差小于1个重力异常基准图格网.

Optimizing suitability area of underwater gravity matching navigation based on a new principal component weighted average normalization method

The suitability evaluation study of the matching area of underwater gravity matching navigation is carried out in this paper. Firstly, we comprehensively consider the main characteristic parameters of the gravity field such as standard deviation of gravity anomaly, standard deviation of slope, roughness, differential entropy of gravity anomaly and fractal dimension. And a new Principal Component Weighted Average Normalization (PCWAN) method is proposed based on principal component analysis guideline and weighted average principle. Secondly, according to the new PCWAN method, we obtain the overall characteristic parameter index that can evaluate the matching results of each area of the gravity anomaly reference map, in order to divide excellent suitability area, general suitability area and non-suitability area. Finally, in the same condition, we compare the numerical simulation results of gravity matching in three different matching areas. It is shown by the results that the gravity matching effect is significant in excellent suitability area. For example, the matching probability is about 98% as well as high matching stability, and the matching accuracy is less than 1 gravity anomaly grid.