TY - JOUR
T1 - Manifold Optimization for High Accuracy Spacial Location Estimation Using Ultrasound Waves
AU - AlSharif, Mohammed H.
AU - Douik, Ahmed
AU - Ahmed, Mohanad
AU - Al-Naffouri, Tareq Y.
AU - Hassibi, Babak
N1 - KAUST Repository Item: Exported on 2021-09-06
PY - 2021
Y1 - 2021
N2 - This paper designs a high accuracy spatial location estimation method using ultrasound waves by exploiting the fixed geometry of the transmitters. Assuming an equilateral triangle antenna configuration, where three antennas are placed as the vertices of an equilateral triangle, the spatial location problem can be formulated as a non-convex optimization problem whose interior is shown to admit a Riemannian manifold structure. The investigation of the geometry of the newly introduced manifold, i.e. the manifold of all equilateral triangles in R^3, allows the design of highly efficient optimization algorithms. Simulation results are presented to compare the performance of the proposed approach against popular methods from the literature. The results suggest that the proposed Riemannian-based methods outperform the state-of-the-art methods. Furthermore, the proposed Riemannian methods require much smaller computation time as compared with popular generic non-convex approaches.
AB - This paper designs a high accuracy spatial location estimation method using ultrasound waves by exploiting the fixed geometry of the transmitters. Assuming an equilateral triangle antenna configuration, where three antennas are placed as the vertices of an equilateral triangle, the spatial location problem can be formulated as a non-convex optimization problem whose interior is shown to admit a Riemannian manifold structure. The investigation of the geometry of the newly introduced manifold, i.e. the manifold of all equilateral triangles in R^3, allows the design of highly efficient optimization algorithms. Simulation results are presented to compare the performance of the proposed approach against popular methods from the literature. The results suggest that the proposed Riemannian-based methods outperform the state-of-the-art methods. Furthermore, the proposed Riemannian methods require much smaller computation time as compared with popular generic non-convex approaches.
UR - http://hdl.handle.net/10754/668512
UR - https://ieeexplore.ieee.org/document/9528945/
U2 - 10.1109/TSP.2021.3109792
DO - 10.1109/TSP.2021.3109792
M3 - Article
SN - 1941-0476
SP - 1
EP - 1
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
ER -