基于组合圆锥构型的水下声学定位系统布站优化

Station Layout Optimization for Underwater Acoustic Positioning SystemBased on Combined-cone Configuration

在水下目标定位中,布站构型的共面约束会导致目标单点定位的几何精度因子(GDOP)理论最小值不能达到。为改善水下布站的观测矩阵,将单圆锥扩展为组合圆锥构型布站模式。然而,传统的优化算法易陷入局部最优且存在收敛效率低等问题。针对以上问题,提出了一种改进的自适应粒子群算法。首先提出了一种有共面约束的水下声学定位系统组合圆锥构型,并证明了所提出的组合圆锥构型具有可叠加性、可旋转性以及GDOP旋转不变性;其次,针对布站优化指标单一的问题,构建了一种基于水下目标全局GDOP的布站优化准则;在此基础上提出了一种基于自适应粒子群的优化算法,并应用于组合圆锥构型下的水下声学定位系统布站优化。所提出的自适应粒子群算法能增强布站的全局最优性,提高算法收敛效率和水下目标的定位精度。

The theoretical minimum of the Geometric Dilution of Precision(GDOP)for target positioning cannot be achieved because of the coplanar constraint for the underwater station configuration.Therefore,the single-cone station configuration was extended to the combined-cone configuration to improve the observation matrix of underwater positioning system.However,the traditional optimization algorithms are still prone to local optimality and lower convergence efficiency.Therefore,an improved Adaptive Particle Swarm Optimization(APSO)algorithm was proposed.Firstly,a combined-cone configuration of underwater acoustic positioning system with coplanar constraints was proposed.The proposed configurations were theoretically proved to be superimposable,rotatable and GDOP rotation invariant.To address the problem of a single criterion for station layout optimization,a criterion based on the global GDOP for the underwater targets is constructed.Furthermore,an optimization algorithm based on APSO was introduced and applied to optimize the layout of the underwater acoustic positioning system in the combined-cone-shaped configuration.Finally,it is verified that the proposed APSO can enhance the global optimality and improve the convergence efficiency of the algorithm.And the positioning accuracy is improved.