在充分研究了超寬帶無線傳輸技術特性的基礎上, 對超寬帶無線定位的原理進行了探討。首先詳細介紹了超寬帶測距和定位的原理, 對超寬帶定位的精度進行了仿真分析。然后, 針對超寬帶 Ad Hoc 網絡實際應用中節點數目比較多的情況, 引入了節點的相關性來提高超寬帶的定位精度, 并進行了仿真分析。仿真結果顯示了此算法在網絡節點數比較多的情況下對定位精度有比較好的提高效果。
We consider the problem of target localization by a
network of passive sensors. When an unknown target emits an
acoustic or a radio signal, its position can be localized with multiple
sensors using the time difference of arrival (TDOA) information.
In this paper, we consider the maximum likelihood formulation
of this target localization problem and provide efficient convex
relaxations for this nonconvex optimization problem.We also propose
a formulation for robust target localization in the presence of
sensor location errors. Two Cramer-Rao bounds are derived corresponding
to situations with and without sensor node location errors.
Simulation results confirm the efficiency and superior performance
of the convex relaxation approach as compared to the
existing least squares based approach when large sensor node location
errors are present.
