An Analytic Quantification Method of Matching Accuracy Based on Particle Filter in Gravity-Assisted Inertial Navigation

Gravity-aided inertial navigation system (GAINS) represents a crucial advancement in underwater navigation. And the matching areas selection algorithm is one of the key techniques. Different from previous researches, estimated overall matching biases (EOMBs), new indexes for matching area selection, are proposed, and consider the matching accuracy to be the capability of system rather than the feature of gravity anomaly map itself. The key factors affecting EOMBs are analyzed, such as gyro drifts, accelerometer biases, velocity, initial positioning errors, overall standard deviation of gravity anomaly observations, and so on. Taking these conditions as a prior information, the method to calculate EOMBs, which are able to quantify gravity-matching precision based on particle filter (PF), is proposed. The simulation results and practical tests show that the proposed method can select matching areas more accurately and efficiently than conventional algorithms. And the threshold is easy to set because it is directly related to matching accuracy.