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Tang L, Jia X, Ma H, Liu S, Chen Y, Tao T, Chen L, Wu J, Li C, Wang X, Weng J. Microwave Absolute Distance Measurement Method with Ten-Micron-Level Accuracy and Meter-Level Range Based on Frequency Domain Interferometry. Sensors (Basel) 2023; 23:7898. [PMID: 37765955 PMCID: PMC10537313 DOI: 10.3390/s23187898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 09/12/2023] [Accepted: 09/13/2023] [Indexed: 09/29/2023]
Abstract
A microwave absolute distance measurement method with ten-micron-level accuracy and meter-level range based on frequency domain interferometry is proposed and experimentally demonstrated for the first time. Theoretical analysis indicates that an interference phenomenon occurs instantaneously in the frequency domain when combining two homologous broad-spectrum microwave beams with different paths, and the absolute value of the distance difference between the two paths is only inversely proportional to the period of frequency domain interference fringes. The proof-of-principle experiments were performed to prove that the proposed method can achieve absolute distance measurement in the X-band with standard deviations of 15 μm, 17 μm, and 26 μm and within ranges of 1.69 m, 2.69 m, and 3.75 m. Additionally, a displacement resolution of 100 microns was realized. The multi-target recognition performance was also verified in principle. Furthermore, at the expense of a slight decrease in ranging accuracy, a fast distance measurement with the single measurement time of 20 μs was achieved by using a digitizer combined with a Fourier transform analyzer. Compared with the current microwave precision ranging technologies, the proposed method not only has the advantages of high precision, large range, and rapid measurement capability, but the required components are also easily obtainable commercial devices. The proposed method also has better complex engineering applicability, because the ten-micron-level ranging accuracy is achievable only by using a simple Fourier transform without any phase estimation algorithm, which greatly reduces the requirement for signal-to-noise ratio.
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Affiliation(s)
- Longhuang Tang
- Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China; (X.J.); (H.M.); (S.L.); (Y.C.); (T.T.); (L.C.); (J.W.); (C.L.); (X.W.)
- National Key Laboratory of Shock Wave and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
| | - Xing Jia
- Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China; (X.J.); (H.M.); (S.L.); (Y.C.); (T.T.); (L.C.); (J.W.); (C.L.); (X.W.)
- National Key Laboratory of Shock Wave and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
| | - Heli Ma
- Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China; (X.J.); (H.M.); (S.L.); (Y.C.); (T.T.); (L.C.); (J.W.); (C.L.); (X.W.)
- National Key Laboratory of Shock Wave and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
| | - Shenggang Liu
- Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China; (X.J.); (H.M.); (S.L.); (Y.C.); (T.T.); (L.C.); (J.W.); (C.L.); (X.W.)
- National Key Laboratory of Shock Wave and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
| | - Yongchao Chen
- Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China; (X.J.); (H.M.); (S.L.); (Y.C.); (T.T.); (L.C.); (J.W.); (C.L.); (X.W.)
- National Key Laboratory of Shock Wave and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
| | - Tianjiong Tao
- Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China; (X.J.); (H.M.); (S.L.); (Y.C.); (T.T.); (L.C.); (J.W.); (C.L.); (X.W.)
- National Key Laboratory of Shock Wave and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
| | - Long Chen
- Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China; (X.J.); (H.M.); (S.L.); (Y.C.); (T.T.); (L.C.); (J.W.); (C.L.); (X.W.)
- National Key Laboratory of Shock Wave and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
| | - Jian Wu
- Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China; (X.J.); (H.M.); (S.L.); (Y.C.); (T.T.); (L.C.); (J.W.); (C.L.); (X.W.)
- National Key Laboratory of Shock Wave and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
| | - Chengjun Li
- Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China; (X.J.); (H.M.); (S.L.); (Y.C.); (T.T.); (L.C.); (J.W.); (C.L.); (X.W.)
- National Key Laboratory of Shock Wave and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
| | - Xiang Wang
- Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China; (X.J.); (H.M.); (S.L.); (Y.C.); (T.T.); (L.C.); (J.W.); (C.L.); (X.W.)
- National Key Laboratory of Shock Wave and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
| | - Jidong Weng
- Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China; (X.J.); (H.M.); (S.L.); (Y.C.); (T.T.); (L.C.); (J.W.); (C.L.); (X.W.)
- National Key Laboratory of Shock Wave and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
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Shui H, Geng H, Li Q, Du L, Du Y. A Low-Power High-Accuracy Urban Waterlogging Depth Sensor Based on Millimeter-Wave FMCW Radar. Sensors 2022; 22:s22031236. [PMID: 35161981 PMCID: PMC8838444 DOI: 10.3390/s22031236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 01/24/2022] [Accepted: 02/01/2022] [Indexed: 02/01/2023]
Abstract
The method of making precise measurements of remote water depth using mmWave technology has great potential for preventing urban waterlogging. To achieve waterlogging prevention, the mmWave system needs to measure the water depth change accurately with a short acquisition time. This paper demonstrates a new accurate mmWave water depth measurement system based on Frequency Modulated Continuous Wave (FMCW) Radar with a center frequency of 77 GHz. To improve distance resolution and lower acquisition time, the Swept Frequency-Cross Correlation (SFCC) algorithm is proposed for the first time to improve the distance computation resolution by 9× and lower time complexity from O(n·logn) to O(n) compared to traditional FFT-based FMCW radar distance computation. A prototype system equipped with a humidity sensor, a processor module and TI’s FMCW radar module is designed for monitoring urban floods in cities. Using the prototype system with the proposed SFCC, the depth measurement error is reduced from 4.5 cm to less than 5 mm, compared to the default radar post-processing algorithm embedded in the radar module.
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Affiliation(s)
| | | | | | - Li Du
- Correspondence: (L.D.); (Y.D.)
| | - Yuan Du
- Correspondence: (L.D.); (Y.D.)
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Li S, Ding J, Liu W, Li H, Zhou F, Zhu Z. Railway Track Recognition Based on Radar Cross-Section Statistical Characterization Using mmWave Radar. Remote Sensing 2022; 14:294. [DOI: 10.3390/rs14020294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The track settlement has a great influence on the safe operation of high-speed trains. The existing track settlement measurement approach requires sophisticated or expensive equipments, and the real-time performance is limited. To address the issue, an ultra-high resolution track settlement detection method is proposed by using millimeter wave radar based on frequency modulated continuous wave (FMCW). Firstly, by constructing the RCS statistical feature data set of multiple objects in the track settlement measurement environment, a directed acyclic graph-support vector machine (DAG-SVM) based method is designed to solve the problem of track recognition in multi-object scenes. Then, the adaptive chirp-z-transform (ACZT) algorithm is used to estimate the distance between the radar and the track surface, which realizes automatic real-time track settlement detection. An experimental platform has been constructed to verify the effectiveness of the proposed method. The experimental results show that the accuracy of track classification and identification is at least 95%, and the accuracy of track settlement measurement exceeds 0.5 mm, which completely meets the accuracy requirements of the railway system.
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Gambi E, Ciattaglia G, De Santis A, Senigagliesi L. Millimeter wave radar data of people walking. Data Brief 2020; 31:105996. [PMID: 32685639 PMCID: PMC7358722 DOI: 10.1016/j.dib.2020.105996] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 06/23/2020] [Accepted: 07/02/2020] [Indexed: 12/01/2022] Open
Abstract
This dataset contains complex signals coming from a mmWave FMCW radar system. Signals were acquired during a measurement campaign taken indoor and aimed to assess people's different ways of walking. Measurement setup and devices are described. The dataset consists of the acquisitions of six different types of activities, performed by 29 subjects who repeat each activity several times. Therefore, the dataset contains multiple different experiments for each activity, for a total of 231 acquisitions. The subjects walk without any constraint or do not follow any pattern, thus making this dataset useful not only for human gait recognition but also to evaluate the performance of different radar data processing algorithms.
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Affiliation(s)
- Ennio Gambi
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
| | - Gianluca Ciattaglia
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
| | - Adelmo De Santis
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
| | - Linda Senigagliesi
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
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