Error Compensation And Signal Processing Of A Rotating Accelerometer Gravity Gradiometer

Moving base gravity gradiometry is an advanced technology for surveying a gravity field;it acquires gravity field information with high efficiency and high spatial resolution.Gravity gradient information is important for mapping of the Earth's gravity field,the analysis of geologic structures,exploration of natural resources,autonomous navigation,etc.,and it has important economic,national defense and scientific research value.To date,rotating accelerometer gravity gradiometer(RAGG)is the only commercial moving base gravity gradiometer.This study systematically and deeply studies the input-output modeling,calibration,error compensation and signal processing of a rotating accelerometer gravity gradiometer.The major research works of this dissertation are as follows:Based on the configuration and principle of the RAGG,taking into account almost all of the error factors,such as accelerometer mounting errors,circuit gain mismatch,accelerometer linear scale factor imbalances,and accelerometer second-order error coefficients,three RAGG models are established: a RAGG analytical model,a simplified RAGG analytical model,and a RAGG numerical model.In the development of a RAGG,the analytical model is the theoretical basis of signal processing,error compensation,calibration,fault diagnosis etc.;the numerical model can be used to verify various technical solutions.The signal processing of the RAGG is studied,including generation of a multifrequency gravitational-gradient excitation,integral amplitude demodulator modeling,based on the RAGG performance indicator(survey speed,spatial resolution,spatial cutoff frequency,cutoff frequency)to design the gravitational gradient extraction module.Considering the position change with respect to the RAGG measurement frame,selfgradient model is established.This study provides detailed procedures and mathematical formulations for calibrating parameters of self-gradient model.Calibrating the self-gradient model before the advent of gravity gradiometry,recording the RAGG attitude in gravity gradiometry,the self-gradient model could calculate the self-gradient and compensate it.A calibration method of RAGG scale factor is proposed.It uses a platform rotating the RAGG to generate centrifugal gradient excitation for calibration RAGG scale factors.In addition,the relationship between centrifugal gradient detection precision and gyro noise coefficients is deduced;based on it,suitable gyros can be selected as angular velocity sensors for centrifugal gradient detection and compensation.Based on the RAGG analytical model,an online error compensation technology is developed.On the one hand,the motion sensitivity of the RAGG is reduced directly through online balance of accelerometer scale factors and of accelerometer misalignment angles;on the other hand,detecting the motion state and the motion sensitivity of the RAGG in real time,based on the RAGG analytical model,a motion error compensation signal is generated to provide motion error compensation.Since the RAGG motion sensitivity is susceptible to the working environment,the motion sensitivity is detected and fed back to trim the error propagation coefficients to make the online error compensation system more robust.Based on the RAGG analytical model,a post-mission motion error compensation method is proposed.With linear regression method,the motion error coefficients and RAGG scale factors are estimated,and then the motion error is estimated and compensated.This method can remove the motion error and extract the gravitational gradient signal from the low signalto-noise-ratio(SNR)RAGG output.