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14 pages, 2625 KiB

Open AccessArticle

Phase Error Evaluation via Differentiation and Cross-Multiplication Demodulation in Phase-Sensitive Optical Time-Domain Reflectometry

by Xin Lu and Peter James Thomas

Photonics 2023, 10(5), 514; https://doi.org/10.3390/photonics10050514 - 28 Apr 2023

Cited by 5 | Viewed by 2039

Abstract

Phase-sensitive optical time-domain reflectometry (φOTDR) is a technology for distributed vibration sensing, where vibration amplitudes are determined by recovering the phase of the backscattered light. Measurement noise induces phase errors, which degrades sensing performance. The phase errors, using a differentiation and cross-multiplication (DCM) algorithm, are investigated theoretically and experimentally in a φOTDR system based on a phase retrieval configuration consisting of an imbalanced Mach–Zehnder interferometer (IMZI) and a 3 × 3 coupler. Analysis shows that phase error is highly dependent on the AC component of the obtained signal, essentially being inversely proportional to the product of the power of the light backscattered from two locations. An analytical expression was derived to estimate the phase error and was confirmed by experiment. When applied to the same measurement data, the error is found to be slightly smaller than that obtained using in-phase/quadrature (I/Q) demodulation. The error, however, increases for longer measurement times. Full article

(This article belongs to the Special Issue Advances of Optical Fiber Sensors)

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12 pages, 24181 KiB

Open AccessArticle

Machine Learning Based Object Classification and Identification Scheme Using an Embedded Millimeter-Wave Radar Sensor

by Homa Arab, Iman Ghaffari, Lydia Chioukh, Serioja Tatu and Steven Dufour

Sensors 2021, 21(13), 4291; https://doi.org/10.3390/s21134291 - 23 Jun 2021

Cited by 16 | Viewed by 4876

Abstract

A target’s movements and radar cross sections are the key parameters to consider when designing a radar sensor for a given application. This paper shows the feasibility and effectiveness of using 24 GHz radar built-in low-noise microwave amplifiers for detecting an object. For this purpose a supervised machine learning model (SVM) is trained using the recorded data to classify the targets based on their cross sections into four categories. The trained classifiers were used to classify the objects with varying distances from the receiver. The SVM classification is also compared with three methods based on binary classification: a one-against-all classification, a one-against-one classification, and a directed acyclic graph SVM. The level of accuracy is approximately 96.6%, and an F1-score of 96.5% is achieved using the one-against-one SVM method with an RFB kernel. The proposed contactless radar in combination with an SVM algorithm can be used to detect and categorize a target in real time without a signal processing toolbox. Full article

(This article belongs to the Special Issue Women in Sensors)

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12 pages, 3187 KiB

Open AccessArticle

An Ultra-Wideband Microwave Photonic Channelized Receiver with Zero-IF Architecture

by Bo Chen, Yangyu Fan, Zhou Tian, Wuying Wang, Bochao Kang, Wei Jiang and Yongsheng Gao

Appl. Sci. 2020, 10(1), 30; https://doi.org/10.3390/app10010030 - 19 Dec 2019

Cited by 13 | Viewed by 4317

Abstract

A scheme for realizing a zero-intermediate frequency (IF) channelized receiver using a dual-polarization quadrature phase-shift keying (DP-QPSK) modulator and a narrow-band optical filter is proposed. The channelized system only requires one optical frequency comb to achieve zero-IF multi-channel reception of wideband signals, and the spacing of the optical frequency comb only needs to be equal to the sub-channel width, which is very easy to implement. It is found that using photonic IQ demodulation and balanced detection and reception technology can not only eliminate many disadvantages of the traditional zero-IF receiver, including local oscillator (LO) leakage, direct current (DC) offset, even-order distortion, and in-phase/quadrature (I/Q) imbalance, but also reduce the bandwidth and sample rate of the analog-to-digital converter (ADC). It is theoretically proven that the radio frequency (RF) signal with a bandwidth of 3 GHz can be divided into five sub-channels with a bandwidth of 600 MHz and finally demodulated to I/Q basebands, which are also verified with simulation. Full article

(This article belongs to the Special Issue Photonic Technology in 5G)

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