Localizing moving targets in unknown harsh environments has always been a severe challenge. This letter investigates a novel localization system based on multi-agent networks, where multiple agents serve as mobile anchors broadcasting their time-space information to the targets. We study how the moving target can localize itself using the sequential time of arrival (TOA) of the one-way broadcast signals. An extended two-step weighted least squares (TSWLS) method is proposed to jointly estimate the position and velocity of the target in the presence of agent information uncertainties. We also address the large target clock offset (LTCO) problem for numerical stability. Analytical results reveal that our method reaches the Cramer-Rao lower bound (CRLB) under small noises. Numerical results show that the proposed method performs better than the existing algorithms.
翻译:将移动目标定位在未知的严酷环境中一直是一个严峻的挑战。 这封信调查了基于多试剂网络的新型本地化系统, 多剂作为流动锚,向目标广播时间空间信息。 我们研究移动目标如何使用单向广播信号的连续到达时间(TOA)使自己本地化。 提议采用扩大的两步加权最小方块(TSWLS)方法,在存在代理剂信息不确定性的情况下,共同估计目标位置和速度。 我们还解决了数字稳定性方面的大型目标时钟偏移(LTCO)问题。 分析结果显示,我们的方法在小噪音下到达Cramer-Rao较低约束范围(CRLB)。 数字结果显示,拟议的方法比现有算法效果更好。