Gravity gradient sensor speed selection method based on inertial technology

Abstract

The invention relates to a gravity gradient sensor speed selection method based on the inertial technology, which is characterized by comprising the following steps: S1, determining a frequency interval with low noise energy at a low frequency; S2, analyzing the Allan variance of a combined signal of static accelerometers, and finding out the relevant time period of white noise under a double-logarithmic coordinate system; and converting the relevant time period of white noise into a frequency interval dominated by white noise; and S3, taking the intersection of the frequency interval with lownoise energy at a low frequency determined through a power spectral density analysis method in S1 and the frequency interval dominated by white noise judged through an Allan variance analysis methodin S2 to obtain the final frequency interval of the rotation frequency of a gravity gradient sensor. By using the method, the influence of the noise of accelerometers on the gravity gradient observation signal can be reduced, and the resolution of measurement can be improved.

Description

technical field [0001] The invention belongs to the technical field of a rotational accelerometer type gravity gradient sensor, and relates to a speed selection method for a gravity gradient sensor, in particular to a speed selection method for a gravity gradient sensor based on inertia technology. Background technique [0002] At present, the rotational accelerometer-type gravity gradiometer is an instrument for continuous measurement of the tiny gravity gradient changes on the earth's surface. Among them, the gravity gradient measurement component as the core sensor is composed of four quartz flexible accelerometers arranged in pairs with equal distances installed on the rotating disk. The detection centroid of each accelerometer is equal to the distance from the center of the disc, and the sensitive axis of the accelerometer is tangent to the circle. figure 1 shown. Among them, No. 1 accelerometer is opposite to No. 3, and No. 2 is opposite to No. 4. In actual work, th...

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Problems solved by technology

The traditional rotation speed selection method only determines the frequency point with the smallest noise capability in the low frequency band through the power spectral density analysis of the accelerometer combined signal, but there are the following two shortcomings: 1. The method of power spectral density analysis theoretically analyzes the signal in the low frequency band The discrimination of noise energy is not strong, frequency leakage is prone to occur, and it is impossible to find the frequency point with the obvious minimum noise energy; 2. The power spectral density analysis method can only determine the amplitude of noise energy in low frequency bands, and cannot identify noise patterns

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