海洋声场中分布式无源定位系统的节点配置方法

A sensor configuration method for distributed passive localization system in ocean acoustic field

为了提高海洋声场中分布式无源定位系统的定位精度,提出一种基于自适应遗传算法的节点配置方法。首先,基于到达时间TOA(Time of Arrival)定位算法推导出均匀物理场与海洋声场中定位误差的CRLB(Cramer Rao Lower Bound)。之后,利用BELLHOP模型对海洋声场进行建模,获得任意位置处目标声源与节点接收信号相关的传递函数并对等效声速进行计算.以目标声源在观测区域内服从均匀分布为例,将定位误差的平均CRLB最小为优化准则,采用自适应遗传算法对节点进行优化配置。结果表明,该方法能够有效降低海洋声场中分布式无源定位系统的定位误差,并给出定位误差随节点个数增加呈非线性递减的变化趋势,可为工程应用提供理论指导。

In order to improve the localization accuracy of the distributed passive location system in the ocean acoustic field.A sensor deployment method is proposed based on adaptive genetic algorithm in this paper.Firstly,the CRLB(Cramer Rao Lower Bound)of location error is deduced based on the TOA(Time of Arrival)localization algorithmin the uniform field and the ocean acoustic field.Then the ocean acoustic field is modeled by BELLHOP model,the transfer function between the arbitrary target and the received signal of any sensor can be attained via this model,meanwhile the concept of the equivalent sound speed is given.When the target is uniform probability distribution in the ocean acoustic field,the adaptive genetic algorithm is adopted to obtain the optimal sensor configuration by minimizing the average CRLB.Simulation results show that the optimal sensor configuration method can effectively reduce the localization error,besides the non-linear decreasing trend of localization error with the increase of number of sensors is given,which provides theoretical guidance for engineering applications.