3D angle-of-arrival positioning using von Mises-Fisher distribution
For positioning systems using angle-of-arrival, this offers a more accurate measurement model when measurements near the poles are common.
The paper proposes modeling angle-of-arrival measurements using a von Mises-Fisher distribution to avoid discontinuities and nonlinearity near poles, and shows via simulation that this approach outperforms normal-distribution-based filters in accuracy.
We propose modeling an angle-of-arrival (AOA) positioning measurement as a von Mises-Fisher (VMF) distributed unit vector instead of the conventional normally distributed azimuth and elevation measurements. Describing the 2-dimensional AOA measurement with three numbers removes discontinuities and reduces nonlinearity at the poles of the azimuth-elevation coordinate system. Our computer simulations show that the proposed VMF measurement noise model based filters outperform the normal distribution based algorithms in accuracy in a scenario where close-to-pole measurements occur frequently.