In this paper, we introduce a new high-resolution reflectometry technique that operates simultaneously in both the time and frequency domains. The approach rests upon timefrequency signal analysis and utilizes a chirp signal multiplied by a Gaussian time envelope. The Gaussian envelope provides time localization, while the chirp allows one to excite the system under test with a swept sinewave covering a frequency band of interest. This latter capability is of particular interest when testing communication cables and systems. Sensitivity in detecting the reflected signal is provided by a time-frequency cross-correlation function. The approach is verified by experimentally locating various types of faults, located at various distances, in RG 142 and RG 400 coaxial cables.

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A novel vertical channel damping loop design method that uses not only a depth sensor but also a Doppler velocity log (DVL) for underwater vehicles is proposed. In the proposed method, the loop gains are calculated by adopting the steady-state Kalman filter gain with consideration of characteristics of the depth sensor and the DVL. The simulation results demonstrate that the proposed method achieves better performance than the conventional method.

Abstract:In this paper, we propose a new load impedance measurement system based on time-frequency domain reflectometry. The proposed system was able to measure the load impedances that were realized with using various terminal resistors and connected at the end of a cable. The experimental results show that the proposed system allows us to know where the connected terminal resistor is on the cable, and how much the impedance of the terminal resistor is. Through real experiments, it is possible for the proposed system to acquire more accurate results in wide range of impedance than conventional commercial time domain reflectometry instrument. Keywords: fault detection, time-frequency domain reflectometry, time-frequency cross-correlation function, phase difference spectrum, load impedance Classification: Science and engineering for electronics

An obstacle detection method for unmanned ground vehicle in outdoor environment is proposed. The proposed method uses range data acquired by laser range finders (LRFs) and FMCW radars. LRFs and FMCW radars are used for distinguishing ground and obstacles on uneven terrain, and for detecting obstacles in dusty environment. The proposed obstacle detection algorithm is broadly composed of three steps: 1) 1D virtual range data generation which ground information is removed by range data of LRFs, 2) 1D virtual range data generation acquired by fusion of multiple FMCW radars, 3) 1D virtual range data generation which dust information is removed by fusion of step 1) and step 2). The proposed method is verified by real experiments.