(Publisher of Peer Reviewed Open Access Journals)

International Journal of Advanced Technology and Engineering Exploration (IJATEE)

ISSN (Print):2394-5443    ISSN (Online):2394-7454
Volume-10 Issue-98 January-2023
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Paper Title : Joint beat-spectrum averaging in a multi-frequency MIMO radar approach on a slow-fluctuating object range detection
Author Name : Suraya Zainuddin, Nur Emileen Abd Rashid, Idnin Pasya Ibrahim, Khairul Khaizi Mohd Shariff and Zahariah Manap
Abstract :

Radar is widely applied in detecting such as aircrafts, ships and motor vehicles, mainly for security and safety purposes. However, a small object is hard to be detected moreover if it is fluctuating. Meanwhile, utilisation of a multiple-input multiple-output (MIMO) in the radar configuration has been acknowledged in many recent works, benefiting from its waveform diversity. In this study, various processing schemes for a MIMO frequency modulated continuous waveform (FMCW) radar were evaluated in detecting a slow-fluctuating object due to water ripples. Employing small and lightweight commercial-off-the-shelf (COTS) modules, a 2×2 co-located MIMO radar configuration was constructed. Beat signals received were post-processed in MATLAB, applying a spectrum averaging (SA), beat averaging (BA) and finally, merging the BA together with SA (BA-SA) schemes. The performance was compared against various averaging methods for MIMO processing, and a single-input single-output (SISO) configuration. Performance was analysed in terms of probability of range error, range error means, root mean square error (RMSE) and scattering index (SI). It was observed that MIMO was performing against SISO, and the combination of BA-SA in MIMO signal processing yielded the best result in all performance indicators compared to other evaluated schemes.

Keywords : Slow-fluctuating object, Signal averaging, Signal processing, Radar, Accuracy.
Cite this article : Zainuddin S, Rashid NE, Ibrahim IP, Shariff KK, Manap Z. Joint beat-spectrum averaging in a multi-frequency MIMO radar approach on a slow-fluctuating object range detection. International Journal of Advanced Technology and Engineering Exploration. 2023; 10(98):21-36. DOI:10.19101/IJATEE.2022.1010015.
References :
[1]Zheng Y, Zheng C, Zhang X, Chen F, Chen Z, Zhao S. Detection, localization, and tracking of multiple MAVs with panoramic stereo camera networks. IEEE Transactions on Automation Science and Engineering. 2022:1-18.
[Crossref] [Google Scholar]
[2]Budisusila EN, Arifin B, Prasetyowati SA, Suprapto BY, Nawawi Z. Artificial neural network algorithm for autonomous vehicle ultrasonic multi-sensor system. In 10th electrical power, electronics, communications, controls and informatics seminar 2020 (pp. 128-31). IEEE.
[Crossref] [Google Scholar]
[3]Tang R, Duan G, Xie L, Bu Y, Zhao M, Lin Z, et al. Static obstacle detection based on acoustic signals. In INFOCOM conference on computer communications workshops (INFOCOM WKSHPS) 2022 (pp. 1-2). IEEE.
[Crossref] [Google Scholar]
[4]Tavanti E, Rizik A, Fedeli A, Caviglia DD, Randazzo A. A short-range FMCW radar-based approach for multi-target human-vehicle detection. IEEE Transactions on Geoscience and Remote Sensing. 2021; 60:1-16.
[Crossref] [Google Scholar]
[5]Kocur D, Porteleky T, Švecová M, Švingál M, Fortes J. A novel signal processing scheme for static person localization using m-sequence UWB radars. IEEE Sensors Journal. 2021; 21(18):20296-310.
[Crossref] [Google Scholar]
[6]Mhaiskar P, Lanjewar V, Shambharkar S, Bhude S, Sharma S, Kalbande M. Automated surveillance system using raspberry pi. In international conference on applied artificial intelligence and computing 2022 (pp. 1473-6). IEEE.
[Crossref] [Google Scholar]
[7]Gibbs G, Jia H, Madani I. Obstacle detection with ultrasonic sensors and signal analysis metrics. Transportation Research Procedia. 2017; 28:173-82.
[Crossref] [Google Scholar]
[8]Mercuri M, Sacco G, Hornung R, Zhang P, Visser HJ, Hijdra M, et al. 2-D localization, angular separation and vital signs monitoring using a SISO FMCW radar for smart long-term health monitoring environments. IEEE Internet of Things Journal. 2021; 8(14):11065-77.
[Crossref] [Google Scholar]
[9]Komorčec D, Matika D. Small crafts role in maritime traffic and detection by technology integration. Pomorstvo. 2016; 30(1):3-11.
[Crossref] [Google Scholar]
[10]https://www.iala-aism.org/product/g1111/. Accessed 15 December 2022.
[11]Finkelman I, Teneh N, Lukovsky G. Detection probability calculations for fluctuating targets under clutter. In 2020 14th European conference on antennas and propagation (EuCAP) 2020 (pp. 1-4). IEEE.
[Crossref] [Google Scholar]
[12]Wang J, Liu J, Zhao W, Xiao N. Performance analysis of radar detection for fluctuating targets based on coherent demodulation. Digital Signal Processing. 2022; 122(2022):1-8.
[Crossref] [Google Scholar]
[13]Zainuddin S, Rashid NE, Ibrahim IP, Abdullah RS, Khan ZI. Spectrum averaging in a MIMO FMCW maritime radar for a small fluctuating target range estimation. Journal of Engineering Science and Technology. 2022; 17(5):3342-59.
[Google Scholar]
[14]https://apps.dtic.mil/dtic/tr/fulltext/u2/080638.pdf. Accessed 15 December 2022.
[15]Mcdonald M, Balaji B. Track-before-detect using swerling 0, 1, and 3 target models for small manoeuvring maritime targets. EURASIP Journal on Advances in Signal Processing. 2008; 2008:1-9.
[Crossref] [Google Scholar]
[16]Zuk J. Correlated noncoherent radar detection for gamma-fluctuating targets in compound clutter. IEEE Transactions on Aerospace and Electronic Systems. 2021; 58(2):1241-56.
[Crossref] [Google Scholar]
[17]De MA, Maffei M, Aubry A, Farina A. Effects of plasma media with weak scintillation on the detection performance of spaceborne radars. IEEE Transactions on Geoscience and Remote Sensing. 2021; 60:1-13.
[Crossref] [Google Scholar]
[18]Enma LP, Liu J, Wang J. Improvement of radar detection capabilities for fluctuating targets using convolutional error control coding technique. In journal of physics: conference series 2021 (pp. 1-7). IOP Publishing.
[Crossref] [Google Scholar]
[19]Addabbo P, Besson O, Orlando D, Ricci G. Adaptive detection of coherent radar targets in the presence of noise jamming. IEEE Transactions on Signal Processing. 2019; 67(24):6498-510.
[Crossref] [Google Scholar]
[20]Bergin J, Guerci JR. MIMO radar: theory and application. Artech House; 2018.
[Google Scholar]
[21]Waldschmidt C, Hasch J, Menzel W. Automotive radar-from first efforts to future systems. IEEE Journal of Microwaves. 2021; 1(1):135-48.
[Crossref] [Google Scholar]
[22]Reza M, Maresca S, Scotti F, Pandey G, Imran M, Serafino G, et al. Multi-static multi-band synthetic aperture radar (SAR) constellation based on photonic processing. In international topical meeting on microwave photonics 2022 (pp. 1-4). IEEE.
[Crossref] [Google Scholar]
[23]Zheng R, Wang C, He X, Li X. A correction method for the nonlinearity of FMCW radar sensors based on multisynchrosqueezing transform. IEEE Sensors Journal. 2022; 23(1):609-19.
[Crossref] [Google Scholar]
[24]Li C, Zhang F, Qu X. High-resolution frequency-modulated continuous-wave LiDAR using multiple laser sources simultaneously scanning. Journal of Lightwave Technology. 2022; 41(1): 367-73.
[Crossref] [Google Scholar]
[25]Ge H, Liu J, Ma Y, Dai P, Sun Z, Chen X, et al. A high-linearity and fast-response direct-modulated DFB laser for low-cost FMCW lidar. In 20th international conference on optical communications and networks 2022 (pp. 1-3). IEEE.
[Crossref] [Google Scholar]
[26]Xu W, Wang B, Xiang M, Song C, Wang Z. A novel autofocus framework for UAV SAR imagery: motion error extraction from symmetric triangular FMCW differential signal. IEEE Transactions on Geoscience and Remote Sensing. 2021; 60:1-5.
[Crossref] [Google Scholar]
[27]Fedotov AA, Badenko VL, Kuptsov VD, Ivanov SI, Eremenko DY. Estimation of spectral components parameters of the time series of raw FMCW radar data to determine the range and speed of location objects. In international conference on electrical engineering and photonics 2022 (pp. 154-7). IEEE.
[Crossref] [Google Scholar]
[28]Meena D, Dhavamani V, Nethravathi KA. Mathematical analysis and modelling of a novel photonic based FMCW signal generation for long range radar applications. In IEEE international conference on electronics, computing and communication technologies 2022 (pp. 1-6). IEEE.
[Crossref] [Google Scholar]
[29]Jeon SY, Ka MH, Shin S, Kim M, Kim S, Kim S, et al. W-band MIMO FMCW radar system with simultaneous transmission of orthogonal waveforms for high-resolution imaging. IEEE Transactions on Microwave Theory and Techniques. 2018; 66(11):5051-64.
[Crossref] [Google Scholar]
[30]https://www.geo.uzh.ch/microsite/rsl-documents/research/SARlab/GMTILiterature/PDF/Skolnik90.pdf. Accessed 15 December 2022.
[31]http://www.hawk.com.au/downloads.asp?cat_id=3&id=35&title=Technical info&subtitle=Technical Info. Accessed 15 December 2022.
[32]Hinz JO, Zölzer U. A MIMO FMCW radar approach to HFSWR. Advances in Radio Science. 2011; 9(C. 4-2):159-63.
[Google Scholar]
[33]Noor AM, Pasya I, Abd RNE, Abdullah RS. MIMO FM-CW radar using beat signal averaging method. In international workshop on antenna technology 2020 (pp. 1-3). IEEE.
[Crossref] [Google Scholar]
[34]Endo K, Member GS, Ishikawa T. Multi-person position estimation based on correlation between received signals using MIMO FMCW radar. IEEE Access. 2023; 11: 2610–20.
[Crossref] [Google Scholar]
[35]Kumbul U, Petrov N, Vaucher CS, Yarovoy A. Phase-coded FMCW for coherent MIMO radar. IEEE Transactions on Microwave Theory and Techniques. 2022:1-3.
[Crossref] [Google Scholar]
[36]Suryana J, Ridha M. Design and implementation of S-Band MIMO FMCW radar. In 10th international conference on telecommunication systems services and applications 2016 (pp. 1-5). IEEE.
[Crossref] [Google Scholar]
[37]Wang R, Wei Y, Zhang S. Signal fusion for multi-target on distributed MIMO radar system. In 2019 international conference on control, automation and information sciences 2019 (pp. 1-4). IEEE.
[Crossref] [Google Scholar]
[38]Lu J, Zhou S, Wang J, Li D, Feng T, Liu H, et al. Signal fusion-based detection with an intuitive weighting method. In radar conference 2020 (pp. 1-6). IEEE.
[Crossref] [Google Scholar]
[39]http://www.industrial-electronics.com/ew_1971-05_avg.html. Accessed 15 December 2022.
[40]Campbell J, Leandri M. Using correlation analysis to assess the reliability of evoked potential components identified by signal averaging. Journal of Neuroscience Methods. 2020; 340:1-9.
[Crossref] [Google Scholar]
[41]Koivumäki P. Triangular and ramp waveforms in target detection with a frequency modulated continuous wave radar. Aalto University; 2017:1-84.
[Google Scholar]
[42]https://www.infineon.com/cms/en/product/evaluation-boards/demo-distance2go/. Accessed 15 December 2022.
[43]Zawawi TN, Abdullah AR, Jopri MH, Sutikno T, Saad NM, Sudirman R. A review of electromyography signal analysis techniques for musculoskeletal disorders. Indonesian Journal of Electrical Engineering and Computer Science. 2018; 11(3):1136-46.
[Crossref] [Google Scholar]
[44]Abdullah AR, Norddin N, Abidin NZ, Aman A, Jopri MH. Leakage current analysis on polymeric and non-polymeric insulating materials using time-frequency distribution. In international conference on power and energy 2012 (pp. 979-84). IEEE.
[Crossref] [Google Scholar]
[45]Rippl P, Iberle J, Walter T. Classification of vulnerable road users based on spectrogram autocorrelation features. In 18th European radar conference 2022 (pp. 293-6). IEEE.
[Crossref] [Google Scholar]
[46]Ren K, Du L, Wang B, Li Q, Chen J. Statistical compressive sensing and feature extraction of time-frequency spectrum from narrowband radar. IEEE Transactions on Aerospace and Electronic Systems. 2019; 56(1):326-42.
[Crossref] [Google Scholar]