多传感器数据融合提高水声定位精度  

Improvement of water acoustic position precision by multi-sensor data fusion

作　　者：董真杰 郑琛瑶[1] 张国龙[1] 

机构地区：[1]中国人民解放军91388部队93分队

出　　处：《现代电子技术》2014年第18期127-129,共3页Modern Electronics Technique

基　　金：国家自然科学基金重点项目:基于联合决策与估计的高频超视距雷达信息处理与融合(61135001)

摘　　要：水下水声环境具有复杂性和不确定性,造成单个传感器接收信息不全和不可靠,定位水下目标精度不高,采用多传感器联合定位成为一个趋势。针对采用多传感器数据融合提高水声定位精度,提出了两种数据融合的方法,优化加权平均法和自适应加权平均法,当待融合数据为两个时,通过理论分析得出了计算加权因子的公式。由数值仿真得到了两种方法的融合精度,结果表明优化加权平均法和自适应加权平均法都可以有效地改善定位精度,但是后者的效果明显优于前者。Since underwater acoustic environment is complex and uncertain, the information received by single sensor is in- complete and unreliable, and the target position precision is low, the multi-sensor location becomes a tendency. Two data fusion approaches （optimization weighted average and self-adaptive weighted average） for multi-sensor data fusion are presented in this paper to improve the water acoustic position precision. Through theoretic analysis, the formula to calculate the weighted parame- ters for fusion of two uniform distribution data was obtained. The fusion precision of two approaches was got by numerical simula- tion. The result shows that both the optimization weighted average and self-adaptive weighted average can improve position preci- sion, and the latter is obviously superior to the former.

关 键 词：多传感器 数据融合 模糊理论 加权平均 定位精度 

分 类 号：TN911-34[电子电信—通信与信息系统] TP212[电子电信—信息与通信工程]