EI / SCOPUS / CSCD 收录

中文核心期刊

联合多站阵元域数据的水下目标检测与跟踪

Underwater target detection and tracking based on array element domain data from multi-arrays

  • 摘要: 为了提高复杂海洋环境中目标的检测、跟踪性能,提出一种联合多站阵元域数据的水下目标检测与跟踪方法.该方法采用序列马尔科夫链蒙特卡洛思想对目标进行采样更新,通过对接收概率中的后验概率以及采样函数进行分解展开,并根据多站阵元域数据计算采样粒子的联合似然,在迭代过程中实现目标数目和目标状态的联合估计.研究结果表明,该方法对单目标的平均定位误差在较高信噪比下能够稳定在50 m以内,对多目标随机出入场景中新生及消失目标实现有效检测,同时对强干扰下弱目标及交叉目标实现有效检测跟踪。仿真结果和海试数据均验证该方法具有良好的目标检测与跟踪性能。

     

    Abstract: An algorithm of underwater target detection and tracking based on array element domain data from multiarrays is presented in order to improve the target detection and tracking ability in the complex marine environment.Sequential Markov chain Monte Carlo method is used to sample and update the target parameters.By decomposing the posterior probability and sampling function in the received likelihood ratio,and calculating the joint likelihood function of the sampled particles according to the multi-array element domain data,a joint estimate of the target number and states is achieved during the iterative process.The research results show that the average positioning error of the single target can be stabilized within 50 m at a high SNR,the new and vanishing targets can be effectively detected under the situation of multiple targets going in and out randomly,and both the weak targets and crosses targets can achieve effective detection and tracking.The simulation and Sea trial results show that the algorithm is able to detect and track the targets functionally.

     

/

返回文章
返回