Since both the position and the orientation of a rigid target can be estimated with a few sensors, which are mounted on the target, it is well known that the rigid body localization (RBL) has various potential applications. In this paper, we propose a new RBL scheme exploiting a participatory search algorithm to simultaneously estimate the unknown parameters for both the three-dimensional displacement and the rotation angles of the target with a single base station using direction of arrival measurements. The performance of the proposed scheme is compared with that of the RBL scheme using a particle swarm optimization algorithm over various conditions such as different noise levels, iterations, various sizes of target, and various search space. According to the results of simulation, the proposed scheme provides higher hit success rate for the optimal solution, lower root mean squared errors in estimation, even with less computational complexity.

中文翻译：

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一种利用参与式搜索算法的新刚体定位方案

由于刚性目标的位置和方向都可以通过安装在目标上的几个传感器来估计，因此众所周知，刚体定位（RBL）具有各种潜在的应用。在本文中，我们提出了一种新的 RBL 方案，利用参与式搜索算法，使用到达方向测量同时估计目标的三维位移和旋转角度的未知参数。将所提出的方案的性能与使用粒子群优化算法的 RBL 方案在各种条件下进行比较，例如不同的噪声水平、迭代、各种大小的目标和各种搜索空间。根据仿真结果，