A Method of Aerogravity Downward Continuation Based on Integral Iterative Algorithm

Abstract

The invention discloses an airborne gravity downward continuation method based on integral iteration algorithm. The method comprises the following steps of when the airborne gravity measurement data of a measured area is subjected to downwards continuation, taking the airborne gravity measurement data as the original value of integral iteration and performing upwards continuation on the airborne gravity measurement data; calculating the difference between an upward continuation result obtained by upward continuation and the airborne gravity measurement data, and taking the difference as the feedback quantity of a downward continuation result; and superposing the feedback quantity and the original value to obtain a new iterative original value, and performing next iteration on the new iterative original value. The method has the advantages of simple principle, simple and convenient operation, easiness in popularization, capability of improving data precision and confidence degree, and the like.

Description

technical field [0001] The invention mainly relates to the technical field of aviation gravity measurement, in particular to a downward extension method of aviation gravity based on an integral iterative algorithm. Background technique [0002] The earth's gravitational field is a basic physical field of the earth, which has great strategic and fundamental significance in the fields of basic science, military and national security. Aerial gravity measurement is a method of determining regional and local gravity fields by aircraft as a carrier. It has fast measurement speed, wide range and low cost. It is the most effective means to obtain high-precision, medium-high-resolution gravity field information in the region. [0003] Airborne gravity measurement obtains the gravity anomaly data at the altitude of the airline, and these measurement data are usually hundreds of meters or even thousands of meters above the earth's surface. The data obtained from this cannot be directl...

AI Technical Summary

Problems solved by technology

[0005] The method of the virtual point mass model is simple, but it is greatly affected by the boundary effect

The gradient method cannot combine the existing ground data, and it is difficult to accurately obtain the vertical gradient of the gravity anomaly in practical applications

The least squares configuration method can take into account the error of the observed quantity and calculate the error covariance matrix to be estimated, but this method needs to solve the inverse matrix of a very large covariance matrix, which is difficult to implement

The direct representation method requires finer terrain height data in the survey area as a reference value, and it cannot achieve rapid continuation for areas lacking terrain data

The regularization algorithm of downward continuation can effectively suppress the influence of observation noise and gravity anomaly high-frequency components on the continuation accuracy, but the key to this method is to find the appropriate regularization parameters, and the calculation is relatively complicated

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