GPS/DVL/MEMS‐INS smartphone sensors integrated method to enhance USV navigation system based on adaptive DSFCF

Abstract

Although the inertial navigation system (INS) can provide a continuous navigation solution for most of unmanned surface vehicles (USVs), its reliability decreases over time due to the accelerometer and gyroscope drifts. The authors’ study introduces a novel method based on integrated micro electric mechanical system (MEMS)-INS smartphone sensors with global positioning system (GPS) and Doppler velocity log (DVL). Since the GPS and DVL are used as reference systems to correct MEMS-INS errors, their accuracies are decreased due to the bad weather and the noise of DVL, which effect on the efficiency of a whole navigation system. To resolve this problem, the adaptive data sharing factor combined filter (DSFCF) is used as integrated method. According to adaptive DSFCF integrated method, the reference system which has the beast accuracy is used to correct the USV navigation errors, and at the same time the least accuracy system will be detected and avoided. The proposed GPS/DVL/MEMS-INS using adaptive DSFCF integrated method was tested on a surface reference trajectory in Mukalla city-Yemen. The estimated results by this proposed method could provide a reliable navigation solution and give the least error compared by the GPS/DVL/MEMS-INS Centralised Kalman filter and the GPS/DVL/MEMS-INS constant DSFCF integrated methods.