Satellite abnormal data identification method and device

Abstract

The invention discloses a satellite abnormal data identification method and device. The method comprises the following steps of acquiring the speed and position calculated by an inertial navigation system, and acquiring the speed and position outputted by a satellite positioning system; obtaining the measurement variables according to the speed and position calculated by the inertial navigation system and the speed and position outputted by the satellite positioning system; predicting the information data according to the measurement variables, calculating a mean value and a standard deviationaccording to an information data flow, and then calculating the Grubbs test statistics; constraining the test statistics according to a set detection level; and if the detected test statistics afterlevel constraint is an abnormal value, rejecting the data of the satellite positioning system, otherwise, inputting the data of the satellite positioning system into a Kalman filter for filtering estimation. The method and the device can realize the real-time online detection, have the simple recursion relationship, are small in calculation amount, do not cause the additional burdens of the systems, have certain elasticity based on the historical statistical data, can overcome the the adverse effect of the abnormal data, enable a discrimination system to be quickly recovered under the influence of the abnormal data, avoid the deadlock, and improve the reliability of Kalman filtering estimation.

Description

technical field [0001] The present application relates to the field of information technology, in particular to a method and device for identifying satellite abnormal data. Background technique [0002] Existing satellite anomaly data judgment methods in engineering basically use measurement range judgment, combined with satellite positioning information, such as positioning marks, DOP values, etc. to make layer-by-layer state judgments. For example, "Arrowborne GPS Abnormal Data Detection and Elimination", aiming at the different characteristics of the arrowborne GPS original measurement data, combined with algorithms such as time series difference and threshold detection, the status bit detection, time scale misalignment detection, and CodeTime detection of measurement data are given. and Doppler frequency detection and other abnormal data detection and elimination algorithms; or according to the statistical characteristics of the observed values, set the threshold to judg...

AI Technical Summary

Problems solved by technology

[0003] The method of layer-by-layer discrimination of GNSS (Global Navigation Satellite System Positioning) receiver output information is a relatively common method in current GNSS abnormal data discrimination. However, due to the large number of GNSS receiver models on the market, it is difficult to output status information. Uniform and strict and accurate, and the judgment process is complicated, which is easy to lead to misjudgment; calculating the standard deviation to set the threshold also requires the designer to have some prior information and gain enough experience to ensure that the designed threshold is reliable and safe; adaptive filtering and Although the method of combining other filtering algorithms has strong adaptability, the algorithm is complicated, which causes an additional burden on the system

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