针对多目标的分布式多边融合定位

针对基于接收信号强度指数(Received Signal Strength Indicator,RSSI)的多目标定位问题,结合点估计与椭圆估计算法,提出一种新的分布式多边融合定位(Distributed Multi-lateral Fusion Localization,DMFL)算法.首先,通过多边定位算法进行粗定位,估计目标的大致位置.其次,基于区间分析理论在线获取泰勒展式高阶余项的边界,并通过集员递归算法求解多目标定位问题.最后,通过实验和仿真验证该算法的定位性能.结果表明,在相同的节点布置条件下,与最新的RSSI定位算法相比,该算法的定位精度更高,最大误差小于0.3 m,并可提供保证包含目标真实位置的最优区域.

Distributed Multilateral Fusion Localization for Multi-Target

To realize the multi-target localization based on Received Signal Strength Indicator (RSSI), this study proposes a new Distributed Multilateral Fusion Localization (DMFL) algorithm with point estimation and ellipse estimation. Firstly, the rough locations of targets are estimated by the multilateral localization algorithm. Then, in light of the interval analysis theory, the higher-order remainder bound of Taylor series expansion is obtained and the set-membership recursive algorithm is used to solve the problem of multi-target localization. Finally, the performance of the localization algorithm is verified through experiments and simulations. The results show that, under the same nodes layout conditions, the algorithm improves the accuracy of localization compared with the latest localization algorithms, with the maximum error being less than 0.3 m. Moreover, it can determine the optimal regions that contain the real locations of targets.