水下传感网络中基于BELLHOP模型的声测距算法

Bellhop-based Real-time Acoustic Ranging in Underwater Sensor Networks

水域环境对声信号的强衰减特性加大了测距的难度。然而,现存的测距算法要求多次的射线踪迹迭代才能达到一定测距精度。而在实时的测距环境很难实现多次迭代。为此,提出基于BELLHOP的实时声测距(real-time acoustic ranging,RAR)算法。RAR算法对声速时变和声射线轨迹进行补偿,降低了搜索空间,减少了计算开销。实验数据表明,与基于射线的根搜索测距(raybased root finding ranging,RRFR)算法相比,提出的RAR算法能够在测距精度和计算开销获取了更好的平衡。

The strong attenuation characteristics of acoustic signals in water environment make the ranging more difficult. However,the existing ranging algorithms require multiple iterations of ray tracks to achieve certain ranging accuracy. However,it is difficult to achieve multiple iterations in the real-time ranging environment. Therefore,BELLHOP-based Real-time Acoustic Ranging( RAR) is proposed in this paper. RAR compensate for the sound speed variations and acoustic ray trajectories,and reduce the search space,in order to reduce computational overhead. Compared with,Our experimental studies verified that the RAR scheme can achieve better tradeoff between accuracy and computational overhead than Ray-based Root Finding Ranging( RRFR) algorithm.