Assessment of the Impact of the Measurement Noise on the Gravity Anomaly Matching Technique

The gravity anomaly matching technique is one of the key technologies in gravity aided inertial navigation, which is a totally passive method to correct the accumulated system error. The gravity anomaly measurement with a gravimeter operates in the real position of a vehicle are compared with the data picked up from a gravity map with the position indicated by the inertial system. The difference contains the position error information which can be estimated in a kalman filter as well as in other system. In consideration of the nonlinearity of the gravity anomaly distribution, nonlinear filtering algorithms are applied into the gravity anomaly matching technique. The measurement noise which is the difference between the gravimeter data and the map data in the same position affect the estimating result a lot, while former studies usually use the white noise to simulate the measurement noise, which cannot represent the real situation. In this paper, the measurement noises are analyzed in detail based on the real gravimeter data and the existing gravity map. According to the applications of the shipborne inertial attitude measurement system, which moves in a relatively low speed, the characteristics of the measurement noises are discussed. Different from the former studies in which the measurement noises are simply treated as the white noise, the noise intensity and the correlation time are both considered as the parameters when modelling the measurement noise. The impact of the measurement noise on the gravity anomaly matching technique are also analyzed with different model parameters. Based on the parameter identification of the global gravity anomaly model, the frequency domain analysis are applied to the gravity anomaly signal that the shipborne inertial attitude measurement system sensed. The gravity anomaly signal along the trace are simulated as the Gauss-Markov process with different parameters, while the measurement noise are also generated independently. The impact of the measurement noise on the gravity anomaly matching technique are studied in detail with changing the parameter. Semi-physical simulations are operated with the real movement parameters of a shipborne inertial attitude measurement system and the simulated gravimeter data. With the cubature kalman filtering algorithm used in a single-axis rotation attitude & heading measurement system, the matching results show that the attitude estimation accuracy and the convergence rate improves with the measurement noise intensity decreasing, which indicates that the measuring accuracy of the gravity anomaly data should be enhanced. On the other hand, with the correlation time increasing, the filter becomes much easier to diverge, which means the resolution power of the measuring data should be improved. Methods to decrease the time correlation of the gravity anomaly data are also discussed. Simulation results show that by extending the sample time or enhancing the space frequency, the diverging of the filter can both be well restrained. The optimal parameters are existed with given accuracy of the system and the movement.