Estimating gravity acceleration from an atomic gravimeter by Kalman filtering

Double diffraction in an atomic gravimeter

We demonstrate the realization of a new scheme for cold atom gravimetry based on the use of double diffraction beamsplitters recently demonstrated in [1], where the use of two retro-reflected Raman beams allows symmetric diffraction in ±h̄keff momenta. Though in principle restricted to the case of zero Doppler shift, for which the two pairs of Raman beams are simultaneously resonant, we demonstr...

Extended Kalman Filtering by

The Electrostatic Gravimeter: An Alternate Way of Measuring Gravitational Acceleration

In the past, the gravitational acceleration on the surface of the Earth, g has been measured in many ways. Various methods include the use of a pendulum as well as models involving the use of a mass on a spring. We have designed a new method incorporating the mass-spring model with a capacitor, and a capacitance meter. This capacitor model still uses a hanging mass on a spring, but alters the m...

Quantum Kalman filtering and the Heisenberg limit in atomic magnetometry.

The shot-noise detection limit in current high-precision magnetometry [Nature (London) 422, 596 (2003)] is a manifestation of quantum fluctuations that scale as 1/sqrt[N] in an ensemble of N atoms. Here, we develop a procedure that combines continuous measurement and quantum Kalman filtering [Rep. Math. Phys. 43, 405 (1999)]] to surpass this conventional limit by exploiting conditional spin squ...

Estimating model error covariance matrix parameters in extended Kalman filtering

The extended Kalman filter (EKF) is a popular state estimation method for nonlinear dynamical models. The model error covariance matrix is often seen as a tuning parameter in EKF, which is often simply postulated by the user. In this paper, we study the filter likelihood technique for estimating the parameters of the model error covariance matrix. The approach is based on computing the likeliho...