Modified sequential processing terrain referenced navigation considering slant range measurement

Modified sequential processing terrain referenced navigation considering slant range measurement

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This study proposes a modified terrain referenced navigation (TRN) algorithm considering slant range measurement. The TRN estimates a vehicle's position by comparing the measured terrain information with digital elevation map data. A conventional TRN assumes that a vertical range is measured by a radar altimeter and the measurement error exists only in the vertical direction. Recently, many researches have focused on applying the slant range sensor data, such as light detection and ranging or interferometric radar altimeter data to improve the TRN performance. In such cases, not only the vertical error but also the horizontal error components are generated by slant range measurement errors and the effect of these error components increases significantly as the flight altitude and the slant range measurement errors increase. Therefore, a proper TRN algorithm should be considered to estimate the vehicle position in a stable and accurate manner. In this study, a modified extended Kalman filter [EKF]-based TRN algorithm (ETRN) considering the slant range measurement and the corresponding measurement variance is proposed. The proposed algorithm converts the ETRN measuring the slant range to the conventional ETRN measuring the vertical range. Also, the proposed algorithm provides robust and accurate TRN results by accounting for the vertical and horizontal error components generated by the slant range errors.

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