Validation of vehicle detection and distance measurement method using virtual vehicle approach

2021 ◽  
Author(s):  
Lan Du ◽  
Taida Lyu ◽  
Huijuan Zhu ◽  
Xiaoqi Wang
Keyword(s):  
Measurement Method ◽  
Vehicle Detection ◽  
Distance Measurement ◽  
Virtual Vehicle

Acoustic Distance Measurement Method Using 2ch Microphones Measurable from 0m Based on Phase Interference and Removal of DC Component

2015 ◽  
Vol 135 (11) ◽  
pp. 1349-1350
Author(s):  
Kazuhiro Suzuki ◽  
Noboru Nakasako ◽  
Masato Nakayama ◽  
Toshihiro Shinohara ◽  
Tetsuji Uebo
Keyword(s):  
Measurement Method ◽  
Distance Measurement ◽  
Phase Interference ◽  
Dc Component

Distance Measurement Method Effective from 0 m Using Phase Interference of Audible Sound

2014 ◽  
Vol 97 (8) ◽  
pp. 24-31
Author(s):  
Noboru Nakasako ◽  
Toshihiro Shinohara ◽  
Keiji Kawanishi ◽  
Tetsuji Uebo
Keyword(s):  
Measurement Method ◽  
Distance Measurement ◽  
Audible Sound ◽  
Phase Interference

Mode Number Determination of Distance Measurement Method Based on Optoelectronic Oscillators

2014 ◽  
Vol 41 (3) ◽  
pp. 0308004
Author(s):  
邾继贵 Zhu Jigui ◽  
郭庭航 Guo Tinghang ◽  
林嘉睿 Lin Jiarui ◽  
张涛 Zhang Tao ◽  
崔鹏飞 Cui Pengfei
Keyword(s):  
Measurement Method ◽  
Distance Measurement ◽  
Mode Number ◽  
Optoelectronic Oscillators

scholarly journals A Parallel-Phase Demodulation-Based Distance-Measurement Method Using Dual-Frequency Modulation

2019 ◽  
Vol 10 (1) ◽  
pp. 293
Author(s):  
In-Gyu Jang ◽  
Sung-Hyun Lee ◽  
Yong-Hwa Park
Keyword(s):  
Frequency Modulation ◽  
Measurement Method ◽  
Continuous Wave ◽  
Measurement Range ◽  
Distance Measurement ◽  
Measurement Technology ◽  
Dual Frequency ◽  
Distance Measurements ◽  
Time Required ◽  
Phase Demodulation

Time-of-flight (ToF) measurement technology based on the amplitude-modulated continuous-wave (AMCW) model has emerged as a state-of-the-art distance-measurement method for various engineering applications. However, many of the ToF cameras employing the AMCW process phase demodulation sequentially, which requires time latency for a single distance measurement. This can result in significant distance errors, especially in non-static environments (e.g., robots and vehicles) such as those containing objects moving relatively to the sensors. To reduce the measurement time required for a distance measurement, this paper proposes a novel, parallel-phase demodulation method. The proposed method processes phase demodulation of signal in parallel rather than sequentially. Based on the parallel phase demodulation, 2π ambiguity problem is also solved in this work by adopting dual frequency modulation to increase the maximum range while maintaining the accuracy. The performance of proposed method was verified through distance measurements under various conditions. The improved distance measurement accuracy was demonstrated throughout an extended measurement range (1–10 m).

A Mahalanobis Distance Measurement Method to Analyze Current Waveform for Determining the Motor’s Quality Types

2017 ◽  
Vol 870 ◽  
pp. 317-322
Author(s):  
Yun Chi Yeh ◽  
Tsung Fu Chien ◽  
Cheng Yuan Chang ◽  
Tsui Shiun Chu
Keyword(s):  
Mahalanobis Distance ◽  
Classification Accuracy ◽  
Measurement Method ◽  
Signal Amplitude ◽  
Distance Measurement ◽  
Digital Converter ◽  
Current Waveform ◽  
Analog To Digital ◽  
Motor Current ◽  
Good Detection

This study proposes a Mahalanobis Distance Measurement (MDM) method to analyze current waveform for determining the motor’s quality types. The MDM method consists of three major stages: (i) the preprocessing stage which is for enlarging motor current waveforms’ amplitude and eliminating noises, and includes signal amplitude amplifier, filter circuit (eliminating noises), and analog-to-digital converter (ADC) parts, (ii) the qualitative features stage which is for qualitative feature selection on motor current waveforms, and (iii) the classification stage which is for determining motor quality types using the MDM method. It can recognize defective motors and their defective types in less than 0.5 second. In the experiment, the total classification accuracy (TCA) was approximately 99.03% in average. The proposed method has the advantages of good detection results, no complex mathematic computations, hi-speed, and hi-reliability.

Scene distance measurement method based on light field imaging

2015 ◽  
Vol 54 (20) ◽  
pp. 6237 ◽  
Author(s):  
Wenxing Fu ◽  
Fei Yan ◽  
Kang Chen ◽  
Zijun Ren
Keyword(s):  
Measurement Method ◽  
Light Field ◽  
Distance Measurement ◽  
Light Field Imaging ◽  
Field Imaging
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