CAJ | 학술논문

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。
수하수성배경구유복잡성화불학정성，조성단개전감기접수신식불전화불가고，정위수하목표정도불고，채용다전감기연합정위성위일개추세。침대채용다전감기수거융합제고수성정위정도，제출료량충수거융합적방법，우화가권평균법화자괄응가권평균법，당대융합수거위량개시，통과이론분석득출료계산가권인자적공식。유수치방진득도료량충방법적융합정도，결과표명우화가권평균법화자괄응가권평균법도가이유효지개선정위정도，단시후자적효과명현우우전자。
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.