AUV长基线定位算法研究

发布时间：2018-03-08 11:51

本文选题：水声传感器网络(UASNs)　切入点：自主潜航器(AUV)定位　出处：《河北师范大学》2016年硕士论文　论文类型：学位论文

【摘要】：近年水声传感器网络(UANs)掀起研究热潮,作为其核心技术之一,自主潜航器(AUV)定位问题亟需节能高精度的解决方案,基于海底应答器的长基线(LBL)定位系统满足UASNs中智能高效,独立高精度的设计目标,是较为合理的选择。本文通过对经典AUV定位技术的利弊分析,结合国内外研究现状,剖析出LBL系统面临着时间同步困难、双向测距(TRT)技术测距不精、和水下声速时变的问题。为解决这些问题,本文针对浅海海域,在基于海底应答器的LBL机制下,提出了无需时间同步的,基于精确声传播时延估计的AUV自定位算法(SL-STTS)。SL-STTS算法通过分析声信号到达角度和AUV的航向角及纵摇角来计算声信号由AUV传向海底应答器的单向传播时延。提出使用数学期望来逼近水下声速,并在理论上证明了其合理性。利用LMA算法来优化测距从而计算出AUV的位置信息。仿真证明,本算法定位误差符合克拉美罗界(CRB),且在时延测量噪声与角度测量噪声的影响下,其定位精度较对比算法提高了约8%～79%。平均测距误差也比RTR算法减小了42%。为节约成本,减少对应答器的使用,进一步提出了序列相似度匹配的滤波定位算法(SCLSS)。SCLSS算法利用格栅式测量将三维定位区域进行格形划分,形成虚拟位置点来辅助定位。由声信号滤波法过滤出任务应答器及可代表AUV位置区域的任务位置点。为进一步提高定位精度,对任务位置点进行合理衍生形成衍生点。通过与AUV的距离序列进行Pearson相似度匹配,二次过滤出衍生点,利用质心加权法其位置进行相似度加权求取AUV的位置。仿真证明,在较少应答器做辅助的情况下,本算法的定位精度较对比算法提升约49%,在时延测量噪声与角度测量噪声的影响下,其定位精度较对比算法提升约35%。
[Abstract]:As one of the core technologies of underwater acoustic sensor network (underwater acoustic sensor network), the localization problem of autonomous submersible vehicle (AUV) is in urgent need of energy saving and high precision solution. The long baseline UASNs positioning system based on submarine transponder meets the requirement of intelligence and high efficiency in UASNs. By analyzing the advantages and disadvantages of the classical AUV positioning technology and combining the current research situation at home and abroad, this paper analyzes that the LBL system is faced with the difficulty of time synchronization, and the bidirectional ranging technology is not very good. In order to solve these problems, in this paper, in the LBL mechanism based on submarine transponder, we propose a time-free method for solving these problems. The AUV self-location algorithm based on accurate acoustic propagation time delay estimation (SL-STTS SL-STTS algorithm) calculates the one-way propagation delay of acoustic signals from AUV to submarine transponders by analyzing the arrival angle of acoustic signals and the heading and pitch angles of AUV. To approach the underwater speed of sound, The rationality of the algorithm is proved theoretically. The location information of AUV is calculated by using LMA algorithm to optimize the ranging. The simulation results show that the location error of this algorithm accords with the Clemero boundary, and under the influence of time-delay measurement noise and angle measurement noise, Its positioning accuracy is improved by about 8 / 79. The average ranging error is 42 less than that of RTR algorithm. In order to save cost and reduce the use of transponder, Furthermore, the filter location algorithm of sequence similarity matching is proposed. The grid measurement is used to divide the three dimensional location region into three dimensions, and the algorithm of SCLSS.SCLSS is used to partition the lattice shape of the three dimensional location area. The task transponder and the task position point which can represent the AUV position area can be filtered out by acoustic signal filtering method. In order to further improve the positioning accuracy, The task location points are reasonably derived to form derivative points. By matching the Pearson similarity with the distance sequence of AUV, the derivative points are filtered out twice, and the position of AUV is weighted by the centroid weighting method. The simulation results show that, In the case of fewer transponders, the positioning accuracy of this algorithm is about 49% higher than that of the contrast algorithm. Under the influence of the delay measurement noise and the angle measurement noise, the positioning accuracy is about 35% higher than that of the contrast algorithm.
【学位授予单位】：河北师范大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U666.7

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