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Ultra-short baseline (USBL) is a mature navigation method for underwater applications. Acoustic outliers and the slant distance calculation error are the main challenges for improving positioning accuracy. The latter, in particular, is often overlooked. In this paper, the slant distance calculation errors due to the motion effect and acoustic outliers will be mainly investigated. To address the problem, the influence of the motion effect on localization in dynamic environments is analyzed first. Aiming at the two challenges, a new measurement model based on the round trip time delay and bearing angles is derived, which can avoid the influence of the motion effect. Besides, to improve the robustness against outliers, a novel robust Kalman filter is designed based on the mixture distribution model. Simulation tests prove that the designed Kalman filter can improve the positioning accuracy in a dynamic environment and overcome the influence of motion effect on slant distance calculation. The proposed method also plays superior performance than the traditional ones under the influence of outliers. The algorithm has also been verified by the river test, and it has better robustness and higher positioning accuracy under dynamic conditions. [ABSTRACT FROM AUTHOR]

In this letter, we comprehensively investigate the electrical properties of the 1200 V planner-gate 4H-SiC power metal–oxide–semiconductor field-effect transistors under the mechanical strains. Three kinds of strains, including the biaxial strain, uniaxial strain parallel to the gate channel, and uniaxial strain perpendicular to the gate channel, are applied using the wafer bending system. It is found that all kinds of compressive strains improve the drain current (Id) under the same gate voltage (Vg) and shift the threshold voltage (Vth) negatively, while the tensile strains decrease Id and shift Vth positively. The Vth shift mainly results from the strain modulated band structure in the poly-Si gate. Under the same overdrive gate voltage (Vov), biaxial strains merely change Id, while both the parallel and perpendicular uniaxial compressive strains enhance Id. The uniaxial compressive strain elevates the electron mobility in the inverted channel by repopulating more electrons into the valleys with a smaller conduction effective mass, which results in the current improvement. [ABSTRACT FROM AUTHOR]

Most of the visual inertial positioning accuracy is constrained by the calibration accuracy of the sensor, however, there are few navigation systems that take the time offset and extrinsic parameters into account at the same time. In this paper, an iterative-optimization-based calibration framework for VIO (visual-inertial odometry) with limited prior conditions is proposed. In particular, a three-stage calibration method is presented, which includes the time offset estimation stage, the extrinsic and intrinsic parameters calibration stage, and global temporal and IMU parameter optimization stage. In the first stage, the time offset calibration model is proposed, which estimates the time delay by iteratively optimizing the orientation residual equation. In the second stage, based on the assumption of constant angle velocity and linear velocity between two continuous keyframes, an iterative-based coarse-to-fine calibration strategy is presented to calibrate the initial extrinsic and IMU intrinsic parameters. In the third stage, a global optimization-based algorithm is introduced to obtain a more accurate time offset value and IMU intrinsic parameters. What’s more worth mentioning is that the proposed method does not require any prior parameters, which greatly improves the universality of the navigation system. To evaluate the effectiveness and accuracy of the proposed algorithm, the method is tested on both simulation and public dataset, and also compared with classical systems. Abundant experimental results illustrate that the proposed method can effectively estimate the time offset, the IMU intrinsic and extrinsic parameters. [ABSTRACT FROM AUTHOR]