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| Optimal condition analysis of target localization usingmulti-agents with uncertain positions |
| YiHou1,NingHao1,FenghuaHe1,ChenXie1,YuYao1 |
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| (1 School of Aerospace, Harbin Institute of Technology, Harbin 150001, Heilongjiang, China) |
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| 摘要: |
| This paper delves into the problem of optimal placement conditions for a group of agents collaboratively localizing a target
using range-only or bearing-only measurements. The challenge in this study stems from the uncertainty associated with the
positions of the agents, which may experience drift or disturbances during the target localization process. Initially, we derive
the Cramer–Rao lower bound (CRLB) of the target position as the primary analytical metric. Subsequently, we establish the
necessary and sufficient conditions for the optimal placement of agents. Based on these conditions, we analyze the maximal
allowable agent position error for an expected mean squared error (MSE), providing valuable guidance for the selection of
agent positioning sensors. The analytical findings are further validated through simulation experiments. |
| 关键词: Cramer–Rao lower bound (CRLB) · Target localization · Uncertain sensor position · Multi-agent systems |
| DOI：https://doi.org/10.1007/s11768-024-00235-5 |
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| 基金项目: |
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| Optimal condition analysis of target localization usingmulti-agents with uncertain positions |
| Yi Hou1,Ning Hao1,Fenghua He1,Chen Xie1,Yu Yao1 |
| (1 School of Aerospace, Harbin Institute of Technology, Harbin 150001, Heilongjiang, China) |
| Abstract: |
| This paper delves into the problem of optimal placement conditions for a group of agents collaboratively localizing a target
using range-only or bearing-only measurements. The challenge in this study stems from the uncertainty associated with the
positions of the agents, which may experience drift or disturbances during the target localization process. Initially, we derive
the Cramer–Rao lower bound (CRLB) of the target position as the primary analytical metric. Subsequently, we establish the
necessary and sufficient conditions for the optimal placement of agents. Based on these conditions, we analyze the maximal
allowable agent position error for an expected mean squared error (MSE), providing valuable guidance for the selection of
agent positioning sensors. The analytical findings are further validated through simulation experiments. |
| Key words: Cramer–Rao lower bound (CRLB) · Target localization · Uncertain sensor position · Multi-agent systems |
