Sensitivity of Algorithms for Estimating the Gravity Disturbance Vector to Its Model Uncertainty

The work considers the results of filtering and smoothing of the gravity disturbance vector horizontal components and focuses on the sensitivity of these results to the model parameters in the case when the inertial-geodesic method is applied in the framework of a marine survey on a sea vessel.

Using spherical scaling functions in scalar and vector airborne gravimetry

<p>Airborne gravimetry is capable to provide Earth’s gravity data of high accuracy and spatial resolution for any area of interest, in particular for hard-to-reach areas. An airborne gravimetry measuring system consists of a stable-platform or strapdown gravimeter, and GNSS receivers. In traditional (scalar) airborne gravimetry, the vertical component of the gravity disturbance vector is measured. In actively developing vector gravimetry, all three components of the gravity disturbance vector are measured.</p><p>In this research, we aim at developing new postprocessing algorithms for estimating gravity from airborne data taking into account a priori information about spatial behavior of the gravity field in the survey area. We propose two algorithms for solving the following two problems:</p><p>1) <em>In scalar gravimetry:</em>  Mapping gravity at the flight height using the gravity disturbances estimated along the flight lines (via low-pass or Kalman filtering), taking into account spatial correlation of the gravity field in the survey area and statistical information on the along-line gravity estimate errors.</p><p>2) <em>In vector gravimetry:</em>  Simultaneous determination of three components of the gravity disturbance vector from airborne measurements at the flight path.</p><p>Both developed algorithms use an a priori spatial gravity model based on parameterizing the disturbing potential in the survey area by three-dimensional harmonic spherical scaling functions (SSFs). The algorithm developed for solving Problem 1 provides estimates of the unknown coefficients of the a priori gravity model using a least squares technique. Due to the assumption that the along-line gravity estimate errors at any two lines are not correlated, the algorithm has a recursive (line-by-line) implementation. At the last step of the recursion, regularization is applied due to ill-conditioning of the least squares problem. Numerical results of processing the GT-2A airborne gravimeter data are presented and discussed.</p><p>To solve Problem 2, one need to separate the gravity horizontal component estimates from systematic errors of the inertial navigation system (INS) of a gravimeter (attitude errors, inertial sensor bias). The standard method of gravity estimation based on gravity modelling over time is not capable to provide accurate results, and additional corrections should be applied. The developed algorithm uses a spatial gravity model based on the SSFs. The coefficients of the gravity model and the INS systematic errors are estimated simultaneously from airborne measurements at the flight path via Kalman filtering with regularization at the last time moment. Results of simulation tests show a significant increase in accuracy of gravity vector estimation compared to the standard method.</p><p>This research was supported by RFBR (grant number 19-01-00179).</p>

Two-dimensional Kalman filter approach to airborne vector gravimetry

The paper presents a new approach to the airborne vector gravimetry problem. The idea of the approach is to take into account spatial correlation of the gravity field to improve observability of horizontal components of the gravity disturbance vector (GDV). We consider the GDV determination problem given airborne data at a set of parallel survey lines assuming that lines are flown in the same direction at a constant height above the reference ellipsoid. We use a 2-D random field model for the gravity field at the flight height. The random field is governed by two autoregressive equations (one in the direction along the lines, the other across the lines). Then we pose the estimation problem simultaneously for the GDV horizontal components and systematic errors of an inertial navigation system at all the lines simultaneously. The developed estimation algorithm is based on 2D Kalman filtering and smoothing techniques. Numerical results obtained from simulated data processing showed improved accuracy of the gravity horizontal component determination.

Signatures of storm sudden commencements in geomagnetic H, Y and Z fields at Indian observatories during 1958−1992

The work describes an intensive study of storm sudden commencement (SSC) impulses in horizontal (H), eastward (Y) and vertical (Z) fields at four Indian geomagnetic observatories between 1958–1992. The midday maximum of ΔH has been shown to exist even at the low-latitude station Alibag which is outside the equatorial electrojet belt, suggesting that SSC is associated with an eastward electric field at equatorial and low latitudes. The impulses in Y field are shown to be linearly and inversely related to ΔH at Annamalainagar and Alibag. The average SC disturbance vector is shown to be about 10–20°W of the geomagnetic meridian. The local time variation of the angle is more westerly during dusk hours in summer and around dawn in the winter months. This clearly suggests an effect of the orientation of shock front plane of the solar plasma with respect to the geomagnetic meridian. The ΔZ at SSC have a positive impulse as in ΔH. The ratio of ΔZ/ΔH are abnormally large exceeding 1.0 in most of the cases at Trivandrum. The latitudinal variation of ΔZ shows a tendency towards a minimum over the equator during the nighttime hours. These effects are explained as (1) resulting from the electromagnetic induction effects due to the equatorial electrojet current in the subsurface conducting layers between India and Sri Lanka, due to channelling of ocean currents through the Palk Strait and (2) due to the concentration of induced currents over extended latitude zones towards the conducting graben between India and Sri Lanka just south of Trivandrum.Key words. Interplanetary physics (interplanetary shocks) · Ionosphere (equatorial ionosphere) · Magnetospheric physics (storms and substorms)

Gravity gradiometer survey errors

Gradiometer system noise, sampling effects, downward continuation, and limited data extent are the important contributors to moving‐base gravity gradiometer survey error. We apply a two‐dimensional frequency‐domain approach in simulations of several sets of airborne survey conditions to assess the significance of the first two sources. A special error allocation technique is used to account for the downward continuation and limited extent effects. These two sources cannot be modeled adequately as measurement noise in a linear error estimation algorithm. For a typical characterization of the Earth’s gravity field, our modeling indicates that limited data extent generally contributes about one‐half of the total error variance associated with recovery of the gravity disturbance vector at the Earth’s surface; gradiometer system noise typically contributes about one‐third. However, sampling effects are also very important (and are controlled through the survey track spacing). A 5 km track spacing provides a reasonable tradeoff between survey cost and errors due to track spacing. Furthermore, our results indicate that a moving‐base gravity gradiometer system can recover each component of the gravity disturbance vector with an rms accuracy better than 1.0 mGal.