A feedback weighted fusion algorithm with dynamic sensor bias correction for gyroscope array

Low-cost Micro-Electromechanical System (MEMS) gyroscopes are known to have a smaller size, lower weight,andlesspowerconsumptionthantheirmoretechnologicallyadvancedcounterparts.However,current low-gradeMEMSgyroscopeshavepoorperformanceandcannotcompetewithqualitysensorsinhigh accuracynavigationalandguidanceapplications.Themainfocusofthispaperistoinvestigateperformance improvementsbyfusingmultiplehomogeneousMEMSgyroscopes.Thesegyrosaretransformedinto avirtualgyrousingafeedbackweightedfusionalgorithmwithdynamicsensorbiascorrection.The gyroscopearraycombineseighthomogeneousgyroscopeunitsoneachaxisanddividesthemintotwo layersofdifferentialconfiguration.Thealgorithmusesthegyroscopearrayestimationvaluetoremovethe gyroscopebiasandthencorrectthegyroscopearraymeasurementvalue.Thenthegyroscopevarianceis recalculatedinrealtimeaccordingtotherevisedmeasurementvalueandtheweightedcoefficientsand stateestimationofeachgyroscopearededucedaccordingtotheleastsquareprinciple.Thesimulations andexperimentsshowedthattheproposedalgorithmcouldfurtherreducethedriftandimprovetheoverall accuracybeyondtheperformancelimitationsofindividualgyroscopes.Themaximumcumulativeangle errorwas − 2 . 09 degrees after 2000 seconds in the static test, and the standard deviation (STD) of the output fusion value of the proposed algorithm was 0.006 degrees/s in the dynamic test, which was only 1.7% of the STD value of an individual gyroscope.