Real‐time failure detection in the carrier phase measurements of GPS by robust and conventional kalman state estimates

Abstract

Among the fastest‐growing applications of high‐precision GPS positioning are those which are kinematic in nature. Carrier phase‐based GPS positioning of a moving antenna—for example, attached to a ship, an aircraft, or a land vehicle—is now commonplace. Recent software innovations make use of advanced ambiguity resolution “on the fly” and real‐time kinematic data processing algorithms to emulate the ease of operation of conventional differential GPS (DGPS) based on transmitted pseudo‐range corrections. However, as much higher accuracy must now be assured compared to DGPS, greater attention must be focused on the quality control aspects of GPS positioning. This study describes two methods for detecting failures or changes of small magnitude in real time in GPS measurements. Examination of the overlap or disjointedness of robust and conventional confidence intervals and studentized normal variates have been used as failure detection tools. These methods are based on testing the performance of the differences between the conventional (nonrobust) Kalman state estimates and the robust Kalman filler estimates. Detection of cycle slips in carrier phase data, outliers in phase rate or in code ranges, or any other type of disorder in the measurements of the GPS system can be addressed with these failure detection methods. Application and evaluation of the algorithms has been carried out using raw carrier‐phase and phase‐rate GPS measurements. It has been demonstrated that these failure detection tools provide powerful and efficient diagnostics for detecting small changes in the measurements of the GPS system.