Rs to the maximum attitude error. two The bias estimation error refers towards the biggest of the 3 gyros or accelerometers.Table two. The relative error, primarily based on the non-covariance transformation in six experiments. Experiment Quantity 1 two three 4 five 6 average Attitude Error/ three.34 2.89 five.56 4.45 two.56 5.56 four.06 Position Error/m two.four two.09 1.26 two.47 1.76 0.89 1.811667 Accelerometer Bias Estimation Error/ 59.3 62.0 20.0 62.five 61.7 22.8 48.1 Gyro Bias Estimation Error/( /h) 0.0091 0.0094 0.0215 0.0069 0.0038 0.0019 0.To sum up, when the navigation frame changes directly, the integrated navigation outcomes show serious fluctuation, taking extra than an hour to reach stability again. The lower the observability with the error state, the bigger the error amplitude. The integrated navigation results, based around the covariance transformation technique, do not fluctuate in the course of the alter of your navigation frame, which is consistent with the reference results. Experimental final results confirm the effectiveness with the proposed algorithm. four.2. Semi-Physical Simulation Experiment Pure mathematical simulation is hard to use to accurately simulate an actual circumstance. As a result, a virtual polar-region method is used to convert the measured aviation information to 80 latitude, to acquire semi-physical simulation information [20]. Within this way, the reliability from the algorithm at higher latitudes is usually verified. In this simulation, the navigation outcome primarily based on the G-frame is utilized as a reference, that will avoid the reduce of algorithm accuracy brought on by the rise in latitude. The simulation results, based around the covariance transformation and non-covariance transformation, are shown in Figure 4. As could be seen in Figure 4a, amongst the attitude errors, the relative yaw error is definitely the largest. The relative yaw error reaches five `without covariance transformation. The integrated navigation Monobenzone MedChemExpress result with covariance transformation includes a less relative yaw error of 0.2′. As shown in Figure 4b, the relative position error is 12 m, without the need of covariance transformation. The integrated navigation result with covariance transformation shows better stability along with a smaller relative position error of 8 m. As shown in Figure 4c,d, the maximum bias error on the gyroscope with and without the need of covariance transformation reached 0.001 /h and 0.02 /h, respectively. The maximum bias error from the accelerometer, with and with out covariance transformation, reached 0.1 and 25 , respectively.Appl. Sci. 2021, 11,scenario. Hence, a virtual polar-region process is made use of to convert the measured aviation data to 80latitude, to acquire semi-physical simulation data [20]. In this way, the reliability on the algorithm at higher latitudes might be verified. In this simulation, the navigation result based on the G-frame is used as a reference, that will avoid the decrease of algorithm 10 of 11 accuracy triggered by the rise in latitude. The simulation benefits, based on the covariance transformation and non-covariance transformation, are shown in Figure 4.Appl. Sci. 2021, 11,11 of(a)(b)(c)(d)Figure four. The simulation outcomes, based around the covariance transformation and non-covariance transformation. (a) Figure four. The simulation results, primarily based on the covariance transformation and non-covariance transformation. (a) The The relative error of attitude; (b) the relative error of position; (c) the relative error of gyro bias estimation; (d) the relative error relative error of attitude; (b) the relative error of position; (c) the relative error of gyro bias e.