The paper presents methodologies of airborne gravimetry surveying and data postprocessing when a strapdown airborne gravimeter is used. Both methodologies were developed based on our experience in processing raw data from state-of-the-art strapdown gravimeters flown in several aerogravimetry campaigns carried out in 2020-2022 using various carriers (including unmanned aerial vehicles). We also present the numerical results from some of the campaigns and provide the achieved accuracy and spatial resolution of airborne gravity data, from which it can be concluded that the data can be used in geophysical applications. For a survey based on an unmanned aerial vehicle, we show the possibility of reaching 1-km spatial resolution of gravity data. For one of the aircraft-based surveys, we also show the possibility of vector gravimetry with an accuracy of 2-3 mGal for the estimated gravity horizontal components.
The paper presents a comparison of Wiener stationary filters, which solves a on-line estimation problem, and Wiener smoothers built using the method of local power spectral densities approximation for estimated signal and interference, with Kalman nonstationary filters and smoothers used in processing the results of a marine gravimetric survey. The results of comparison of gravity anomaly estimates obtained with different filters using simulation and real data are presented. The advantages and disadvantages of the compared filters and smoothers are discussed.
Choosing four kinds of adhesives (A, B, C and D) with different parameters, we mainly analyze the influence of the thermal expansion coefficient and elastic modulus of adhesives on the variation in the fiber coil size based on ANSYS software. By measuring fiber coil loss, fiber coil polarization crosstalk and scale factor temperature sensitivity of FOGs, it has been found that A adhesive is the best for FOGs that use the fiber coil with skeleton. And the scale factor temperature sensitivity is only 23.52 ppm/℃ in the temperature range from −40 °C to 60 °C, which shows that correlation between scale factor and temperature is better than that of others. Moreover, the compensated scale factor variation of the FOG with A adhesive will reach to 200 ppm in the temperature range from −40 °C to 60 °C, which improves the performance by 60%.
Two types of locked angular motion of control object based on strapdown inertial navigation system are under consideration. The mentioned motions are given as a certain sequence of spatial turns relative to body (instrument) axes. Structural changes of angular position error of control object relative to instrument axes based on the results of typical motion are examined. Besides, it is supposed that angle-measuring channels are dominated by errors proportional to measuring signal. Possibility of instrument axes error redistribution by typical locked angular motion parameter setting is shown. Directions of improvement of the control object main characteristics based on strapdown inertial navigation system using such typical motion are described.
The paper describes a technique for designing and optimizing the bearing structure of a strapdown inertial navigation system aiming to reduce the instrumental errors of sensors caused by the deformation of the bearing structure under the complex action of an external and internal loads considering the mass minimization of an inertial measurement unit at the same time. In order to solve current tasks an algorithm that combines multi-objective parametric optimization and structural topological optimization was developed. As an illustration of the described technique application, the process of optimizing the bearing structure of a particular device of a strapdown inertial navigation system was considered. Two-stage multi-objective parametric optimization was performed in order to maximize the stiffness of the structure, and then, using topological optimization, the mass of parts was minimized. It was shown that the proposed combination of parametric and topological design optimization techniques allows us to switch from multi-objective optimization to single-objective optimization with the assumption of insignificant change of stiffness.
