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1

Benani, Abdelmoumen, Andre Carr, and Martin Quenneville. "Doppler spread technique." IEEE Vehicular Technology Magazine 4, no. 1 (2009): 78–86. http://dx.doi.org/10.1109/mvt.2008.931621.

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2

Dang, Qun, and Xiao Li Lei. "Doppler Frequency Shift Tolerance Extension in Burst Spread Spectrum Communication System." Advanced Materials Research 443-444 (January 2012): 237–40. http://dx.doi.org/10.4028/www.scientific.net/amr.443-444.237.

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A method to extend Doppler frequency discrimination tolerance is proposed for quick acquirement PN-code and Doppler frequency in TDMA burst spread spectrum communication system. According to Doppler’s different impacts on the correlation Peak and data demodulation, PN-code is acquired through single channel matched-filters, and parallel multi-channel correlators are used in the data demodulation branch channel. Thus, with using frame head prior information in data channel instead of traditional Cross-Product Automatic Frequency Control (CPAFC), the Doppler frequency shift discrimination tolera
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3

Bu, Linsheng, Wanyu Chang, Defeng Chen, and Tuo Fu. "Deep learning-based Doppler-spread target detection with attention mechanism." Journal of Physics: Conference Series 2906, no. 1 (2024): 012023. https://doi.org/10.1088/1742-6596/2906/1/012023.

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Abstract In radar systems, Doppler spread issues commonly arise in space small target detections when integration is adopted during a long coherent processing interval (CPI). Even with precise compensation for translational effects, phase variations introduced by changes in target observation attitudes (TOA) can still cause the target’s echo energy to spread across multiple Doppler cells. As the TOA undergoes several periods over a CPI, the echo energy disperses into equidistant Doppler cells within a range cell in the range-Doppler (RD) map, which poses challenges for traditional methods and
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4

Krasny, L., H. Arslan, D. Koilpillai, and S. Chennakeshu. "Doppler spread estimation in mobile radio systems." IEEE Communications Letters 5, no. 5 (2001): 197–99. http://dx.doi.org/10.1109/4234.922758.

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5

Howard, S. J., and K. Pahlavan. "Doppler spread measurements of indoor radio channel." Electronics Letters 26, no. 2 (1990): 107. http://dx.doi.org/10.1049/el:19900074.

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6

KO, Y. C. "Doppler Spread Estimation in Mobile Communication Systems." IEICE Transactions on Communications E88-B, no. 2 (2005): 724–28. http://dx.doi.org/10.1093/ietcom/e88-b.2.724.

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7

Hines, Colin O. "The Doppler spread theory and parameterization revisited." Journal of Atmospheric and Solar-Terrestrial Physics 66, no. 11 (2004): 949–56. http://dx.doi.org/10.1016/j.jastp.2004.02.005.

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8

Zhang, Yan, Zunwen He, Wancheng Zhang, Limin Xiao, and Shidong Zhou. "Measurement-Based Delay and Doppler Characterizations for High-Speed Railway Hilly Scenario." International Journal of Antennas and Propagation 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/875345.

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This paper presents results for delay and Doppler spread characterization in high-speed railway (HSR) hilly scenario. To investigate the propagation characteristics in this specific terrain, a measurement campaign is conducted along the “Guangzhou-Shenzhen” HSR in China. A wideband channel sounder with 40 MHz bandwidth is used to collect raw data at 2.4 GHz band. The delay spread and Doppler frequency features are analyzed based on measured data. It is found that there are abundant multipath components (MPCs) in this scenario. We present the relationship between the delay spreads and the trans
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9

Bhadouria, Vijay Singh, Monika Agrawal, and Ritesh Kumar. "An unsupervised clustering-based scale-lag receiver design approach for the doubly selective underwater acoustic channel." Journal of the Acoustical Society of America 152, no. 1 (2022): 342–53. http://dx.doi.org/10.1121/10.0012349.

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This paper details the architecture of a novel scale-lag rake receiver for the doubly selective underwater acoustic (UWA) channel. The shallow UWA channel is known to have a large Doppler spread. The cause of this is primarily due to the large spread of the angle of arrival of the received signal's paths. The Doppler scale value is dependent on the angle of arrival of the received signal. The Doppler spread is significant, and multiple Doppler scales are present in the UWA channel. Therefore, the receivers operating with only a single Doppler scale compensation perform sub-optimally. The optim
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10

Rice, Joseph, Paul Baxley, Homer Bucker, et al. "Doppler spread in an undersea acoustic transmission channel." Journal of the Acoustical Society of America 103, no. 5 (1998): 2782. http://dx.doi.org/10.1121/1.422266.

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11

Baddour, K. E., and N. C. Beaulieu. "Robust Doppler spread estimation in nonisotropic fading channels." IEEE Transactions on Wireless Communications 4, no. 6 (2005): 2677–82. http://dx.doi.org/10.1109/twc.2005.858362.

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12

Huang, Pengda, Dinesh Rajan, and Joseph Camp. "An Autoregressive Doppler Spread Estimator for Fading Channels." IEEE Wireless Communications Letters 2, no. 6 (2013): 655–58. http://dx.doi.org/10.1109/wcl.2013.091113.130593.

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13

Okada, Minoru, Hideaki Takayanagi, and Heiichi Yamamoto. "Array antenna assisted doppler spread compensator for OFDM." European Transactions on Telecommunications 13, no. 5 (2002): 507–12. http://dx.doi.org/10.1002/ett.4460130511.

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14

Frigyes, I., B. G. Molnár, R. Vallet, Z. Herczku, and Z. Bodnár. "Doppler spread characteristics of satellite personal communication channels." International Journal of Satellite Communications 19, no. 3 (2001): 251–62. http://dx.doi.org/10.1002/sat.685.

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15

Lee, Chan-Ho, Young-Gwang Seo, and Ji-Won Park. "PRF Selection Algorithm to Avoid Clutter Doppler Spread." Journal of Korean Institute of Electromagnetic Engineering and Science 36, no. 1 (2025): 31–37. https://doi.org/10.5515/kjkiees.2025.36.1.31.

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16

Bu, Linsheng, Tuo Fu, Defeng Chen, Huawei Cao, Shuo Zhang, and Jialiang Han. "Doppler-Spread Space Target Detection Based on Overlapping Group Shrinkage and Order Statistics." Remote Sensing 16, no. 18 (2024): 3413. http://dx.doi.org/10.3390/rs16183413.

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The Doppler-spread problem is commonly encountered in space target observation scenarios using ground-based radar when prolonged coherent integration techniques are utilized. Even when the translational motion is accurately compensated, the phase resulting from changes in the target observation attitude (TOA) still leads to extension of the target’s echo energy across multiple Doppler cells. In particular, as the TOA change undergoes multiple cycles within a coherent processing interval (CPI), the Doppler spectrum spreads into equidistant sparse line spectra, posing a substantial challenge for
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17

Wang, Ke, Chan-Tong Lam, and Benjamin K. Ng. "Positioning Information Based High-Speed Communications with Multiple RISs: Doppler Mitigation and Hardware Impairments." Applied Sciences 12, no. 14 (2022): 7076. http://dx.doi.org/10.3390/app12147076.

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In this paper, we consider a multiple reconfigurable intelligent surface (RIS)-assisted system using positioning information (PI) to explore the potential of Doppler effect mitigation and spectral efficiency (SE) enhancement in high-speed communications (HSC) in the presence of hardware impairments (HWI). In particular, we first present a general multi-RIS-assisted system model for HSC with HWI. Then, based on PI, different phase shift optimization strategies are designed and compared for maximizing SE, eliminating Doppler spread, and maintaining a very low delay spread. Moreover, we compare t
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18

Yang, Guang, Feng Zhou, Gang Qiao, et al. "Optimized Doppler Estimation and Symbol Synchronization for Mobile M-ary Spread Spectrum Underwater Acoustic Communication." Journal of Marine Science and Engineering 9, no. 9 (2021): 1001. http://dx.doi.org/10.3390/jmse9091001.

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In mobile underwater acoustic (UWA) communications, the Doppler effect causes severe signal distortion, which leads to carrier frequency shift and compresses/broadens the signal length. This situation has a more severe impact on communication performance in the case of low signal-to-noise ratio and variable-speed movement. This paper proposes a non-data-aided Doppler estimation method for M-ary spread spectrum UWA communication systems in mobile scenarios. The receiver uses the spread spectrum codes dedicated to transmitting signals with different frequency offsets as local reference signals.
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19

Li, Jie, Fangjiong Chen, Songzuo Liu, Hua Yu, and Fei Ji. "Estimation of Overspread Underwater Acoustic Channel Based on Low-Rank Matrix Recovery." Sensors 19, no. 22 (2019): 4976. http://dx.doi.org/10.3390/s19224976.

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In this paper, the estimation of overspread, i.e., doubly spread underwater acoustic (UWA) channels of strong dispersion is considered. We show that although the UWA channel dispersion causes the degeneration of channel sparsity, it leads to a low-rank structure especially when the channel delay-Doppler-spread function is separable in delay and Doppler domain. Therefore, we introduce the low-rank criterion to estimate the UWA channels, which can help to improve the estimation performance in the case of strong dispersion. The estimator is based on the discrete delay-Doppler-spread function repr
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20

TAO, X., C. ZHANG, and J. LU. "Doppler Diversity in MC-CDMA Systems with T-ZCZ Sequences for Doppler Spread Cancelation." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E90-A, no. 11 (2007): 2361–68. http://dx.doi.org/10.1093/ietfec/e90-a.11.2361.

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21

Wu, Xing Cun, Ping Gong, Hai Jun Song, and Hui Zhi Zou. "An FFT-Based Approach for Carrier Frequency Domain Acquisition in Spread Spectrum TT&C System." Applied Mechanics and Materials 135-136 (October 2011): 211–16. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.211.

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Acquisition time of precision ranging code is long under the conditions of large Doppler shift, the carrier frequency domain FFT-based fast acquisition theory was analyzed, and the method of carrier Doppler compensation estimates to complete the PN code Doppler compensation was directly used in spread spectrum ranging signal acquisition. Comparing with the traditional parallel acquisition approach, the Doppler frequency estimation accuracy and acquisition speed is greatly improved, the acquisition time is shorter than long code segment with the traditional parallel acquisition method. Comparin
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22

Liu, Bei Jia, Xiao Wang, Xue Zhi Tan, and Yang Yu. "An Adaptive Channel Estimation Based on Polynomial Fitting for LTE Uplink in High Doppler Spread Scenario." Advanced Materials Research 756-759 (September 2013): 3522–26. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.3522.

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Channel estimation plays a crucial role in improving the overall system performance in long term evolution (LTE) systems. However, it is demonstrated that conventional channel estimation algorithms have poor performance in the presence of a large Doppler frequency shift. To mitigate the adverse effect of Doppler frequency shift on transmission signals, an adaptive anti-Doppler shift method based on polynomial fitting for LTE uplink is proposed in this paper. Furthermore, an adaptive strategy is exploited to improve estimation accuracy and reduce estimation mean square error (MSE), achieving be
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23

Cai, Fei, and Meiyu Tang. "Dim Range-Spread Target Detection for Stepped-Frequency Radar Using a Bernoulli Extended Target Filter." Sensors 25, no. 5 (2025): 1426. https://doi.org/10.3390/s25051426.

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Stepped-frequency radar is an important high range resolution radar. It can achieve wide overall bandwidth with narrow instant bandwidth. When the signal-to-noise ratio is low, detection and tracking become challenging due to dense false alarms and the range-Doppler coupling problem. In this paper, a new methodology is presented to address this problem. A Bernoulli extended target filter is used for joint detection and tracking of a dim range-spread target. The results of coherent processing are thresholded firstly using a low threshold, and the range-Doppler coupled detections generated by mu
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24

Yoon, Eunchul, Soonbum Kwon, Unil Yun, and Sun-Yong Kim. "Doppler Spread Estimation Based on Machine Learning for an OFDM System." Wireless Communications and Mobile Computing 2021 (September 21, 2021): 1–15. http://dx.doi.org/10.1155/2021/5586029.

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In this paper, we propose a Doppler spread estimation approach based on machine learning for an OFDM system. We present a carefully designed neural network architecture to achieve good performance in a mixed-channel scenario in which channel characteristic variables such as Rician K factor, azimuth angle of arrival (AOA) width, mean direction of azimuth AOA, and channel estimation errors are randomly generated. When preprocessing the channel state information (CSI) collected under the mixed-channel scenario, we propose averaged power spectral density (PSD) sequence as high-quality training dat
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25

SHENG, Bin, Pengcheng ZHU, and Xiaohu YOU. "An Enhanced Doppler Spread Estimation Method for OFDM Systems." IEICE Transactions on Communications E95.B, no. 12 (2012): 3911–14. http://dx.doi.org/10.1587/transcom.e95.b.3911.

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26

Yanovsky, F. J., C. M. H. Unal, H. W. J. Russchenberg, and L. P. Ligthart. "Doppler-Polarimetric Weather Radar: Returns from Wide Spread Precipitation." Telecommunications and Radio Engineering 66, no. 8 (2007): 715–27. http://dx.doi.org/10.1615/telecomradeng.v66.i8.20.

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27

Eller, Anthony I., and Ellen M. Daley. "Effects of scattering‐induced frequency spread on Doppler performance." Journal of the Acoustical Society of America 98, no. 5 (1995): 2912. http://dx.doi.org/10.1121/1.414197.

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28

Mohammadkarimi, Mostafa, Ebrahim Karami, Octavia A. Dobre, and Moe Z. Win. "Doppler Spread Estimation in MIMO Frequency-Selective Fading Channels." IEEE Transactions on Wireless Communications 17, no. 3 (2018): 1951–65. http://dx.doi.org/10.1109/twc.2017.2787539.

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29

Zhang, Wei, Huiyong Li, Guohao Sun, and Zishu He. "Enhanced Detection of Doppler-Spread Targets for FMCW Radar." IEEE Transactions on Aerospace and Electronic Systems 55, no. 4 (2019): 2066–78. http://dx.doi.org/10.1109/taes.2019.2925433.

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30

Hong Zhang and A. Abdi. "Cyclostationarity-based doppler spread estimation in mobile fading channels." IEEE Transactions on Communications 57, no. 4 (2009): 1061–67. http://dx.doi.org/10.1109/tcomm.2009.04.070255.

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31

Reyes, Hector, Naima Kaabouch, and Wen-Chen Hu. "Spectrum Channel Characterization Using Delay and Doppler Spread Parameters." Journal of Communications 9, no. 3 (2014): 234–40. http://dx.doi.org/10.12720/jcm.9.3.234-240.

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32

Reddi, C. R., M. S. S. R. K. N. Sarma, and K. Niranjan. "HF Doppler radar observations of low-latitude spread F." Radio Science 44, no. 3 (2009): n/a. http://dx.doi.org/10.1029/2007rs003777.

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33

ZHANG, P., X. XU, G. BI, X. CAO, and J. ZHAO. "Iterative Joint Correlation Interval Selection and Doppler Spread Estimation." IEICE Transactions on Communications E89-B, no. 11 (2006): 3156–59. http://dx.doi.org/10.1093/ietcom/e89-b.11.3156.

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34

Capoglu, I. R., Ye Li, and A. Swami. "Effect of Doppler spread in OFDM-based UWB systems." IEEE Transactions on Wireless Communications 4, no. 5 (2005): 2559–67. http://dx.doi.org/10.1109/twc.2005.853978.

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35

Robertson, Patrick, and Stefan Kaiser. "Analysis of Doppler Spread Perturbations in OFDM(A) Systems." European Transactions on Telecommunications 11, no. 6 (2000): 585–92. http://dx.doi.org/10.1002/ett.4460110609.

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36

Ra, HyungIn, Changhyun Youn, and Kiman Kim. "High-Reliability Underwater Acoustic Communication Using an M-ary Cyclic Spread Spectrum." Electronics 11, no. 11 (2022): 1698. http://dx.doi.org/10.3390/electronics11111698.

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Multipath propagation, frequency selective fading, low-propagation velocity, and narrow bandwidth are all characteristics of underwater acoustic channels. Doppler shifts and diffusions can occur as a result of the low transmission speed of an acoustic signal, which can be caused by the movement of ocean currents or the transceiver. Furthermore, frequency selective fading and excessive noise interference can disrupt underwater acoustic communication on a continual basis. Because of its high anti-interference ability and high confidentiality, spread spectrum technology is commonly adopted in und
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37

Zhao, Pengyu, Xiaoyong Wang, Kai Zhang, Yanliang Jin, and Guoxin Zheng. "Doppler Modeling and Simulation of Train-to-Train Communication in Metro Tunnel Environment." Sensors 22, no. 11 (2022): 4289. http://dx.doi.org/10.3390/s22114289.

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The communication system of urban rail transit is gradually changing from train-to-ground (T2G) to train-to-train (T2T) communication. The subway can travel at speeds of up to 200 km/h in the tunnel environment, and communication between trains can be conducted via millimeter waves with minimum latency. A precise channel model is required to test the reliability of T2T communication over a non-line-of-sight (NLoS) Doppler channel in a tunnel scenario. In this paper, the description of the ray angle for a T2T communication terminal is established, and the mapping relationship of the multipath s
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38

Tu, Xingbin, Shaojian Yang, Jie Xi, Yulin Jiang, Wei Yan, and Fengzhong Qu. "Doubly-spread channel equalization based on channel shortening in mobile underwater acoustic communications." Journal of the Acoustical Society of America 154, no. 4_supplement (2023): A249. http://dx.doi.org/10.1121/10.0023447.

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The shallow water environments and the movement of autonomous underwater vehicles contribute to the distortion of acoustic signals in both the delay and Doppler domains. Numerous studies have focused on eliminating the distortion in underwater acoustic communications but have struggled to find an optimal trade-off between performance and computational complexity, rendering them impractical for marine engineering applications. In our research, we propose a channel-shortening equalization scheme based on frequency-domain decision feedback equalization (FD-DFE) to address this issue. This approac
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39

Ricci, Stefano. "Switching Power Suppliers Noise Reduction in Ultrasound Doppler Fluid Measurements." Electronics 8, no. 4 (2019): 421. http://dx.doi.org/10.3390/electronics8040421.

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Ultrasound Doppler techniques are widely employed in detecting the velocity of moving fluids both in medical and industrial applications. Echo Doppler electronics systems include a highly sensitive front-end suitable to processing the very low power ultrasound echoes received by the transducer. Moreover, the front-end input bandwidth typically ranges between 100 kHz and 10 MHz, which is the same frequency range where modern switching regulators work. Thus, the front-end is particularly prone to the noise produced by the suppliers that power the board itself. Electromagnetic interference (EMI)
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40

Sadrieh, Seyed Nima, Ali Broumandan, and Gérard Lachapelle. "Doppler Characterization of a Mobile GNSS Receiver in Multipath Fading Channels." Journal of Navigation 65, no. 3 (2012): 477–94. http://dx.doi.org/10.1017/s037346331200015x.

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Global Navigation Satellite Systems (GNSS) Doppler measurements are commonly used for velocity-based relative positioning and aiding Inertial Navigation Systems (INS) in signal degraded environments. The aim of this paper is to characterise the Doppler measurements in GNSS harsh multipath environments. In multipath fading situations such as indoor and urban canyon environments, multipath components arrive to the receiver antenna from different paths and directions. These give rise to various Doppler shifts that cause errors in the velocity solution. In this work the Doppler measurements discre
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41

Amalia, Nisa Noor, Khoirul Anwar, and Nachwan Mufti Adriansyah. "PENINGKATAN KINERJA FUTURE RAILWAY MOBILE COMMUNICATION SYSTEM UNTUK KERETA CEPAT INDONESIA DENGAN SINGLE INPUT MULTIPLE OUTPUT - DOPPLER SPREAD COMPENSATOR." TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika 6, no. 1 (2022): 28. http://dx.doi.org/10.25124/tektrika.v6i1.4071.

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Future railway mobile communication system (FRMCS) merupakan sistem pensinyalan kereta cepat berbasis the fifth telecommunication generation new radio (5G NR) third generation partnership project (3GPP) TS 22.289 dan European telecommunication standard institute (ETSI) TR 103 459. Pergerakan kereta yang cepat mengakibatkan kerusakan sinyal akibat adanya pergeseran frekuensi yang dirasakan oleh penerima, sehingga mengganggu sistem komunikasi kereta cepat. Untuk mendukung pensinyalan kereta cepat yang baik dan berkapasitas besar, makalah ini mengusulkan single input multiple output (SIMO) dengan
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42

Kumar, B. T. Vikram, P. Velayudhan Nair, and P. B. Rao. "HF doppler observations on the occurrence of equatorial spread-F." Journal of Earth System Science 94, no. 3 (1985): 261–67. http://dx.doi.org/10.1007/bf02839203.

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43

Ghogho, M., A. Swami, and T. S. Durrani. "Frequency estimation in the presence of Doppler spread: performance analysis." IEEE Transactions on Signal Processing 49, no. 4 (2001): 777–89. http://dx.doi.org/10.1109/78.912922.

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44

Hagfors, T., and E. Tereshchenko. "Two-dimensional chirp mapping of delay and Doppler spread targets." Radio Science 26, no. 5 (1991): 1199–203. http://dx.doi.org/10.1029/91rs01414.

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45

Marsden, R. F., and R. G. Ingram. "Correcting for Beam Spread in Acoustic Doppler Current Profiler Measurements." Journal of Atmospheric and Oceanic Technology 21, no. 9 (2004): 1491–98. http://dx.doi.org/10.1175/1520-0426(2004)021<1491:cfbsia>2.0.co;2.

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46

Po-Ying Chen and Hsueh-Jyh Li. "An iterative algorithm for Doppler spread estimation in LOS environments." IEEE Transactions on Wireless Communications 5, no. 6 (2006): 1223–28. http://dx.doi.org/10.1109/twc.2006.1638638.

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47

Castrellon, Mario, David Muñoz, Cesar Vargas, Claudio Lopez, and David Covarrubias. "Doppler spread for Gaussian scatter density environments employing smart antennas." AEU - International Journal of Electronics and Communications 61, no. 9 (2007): 631–36. http://dx.doi.org/10.1016/j.aeue.2006.12.010.

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48

Ramakrishnan, D., and J. Krolik. "Adaptive Radar Detection in Doubly Nonstationary Autoregressive Doppler Spread Clutter." IEEE Transactions on Aerospace and Electronic Systems 45, no. 2 (2009): 484–501. http://dx.doi.org/10.1109/taes.2009.5089536.

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49

Roy, Sébastien, Huu Tuê Huynh, and Paul Fortier. "Compound Doppler Spread Effects of Subscriber Motion and Scatterer Motion." AEU - International Journal of Electronics and Communications 57, no. 4 (2003): 237–46. http://dx.doi.org/10.1078/1434-8411-54100166.

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50

Luo, T., Z. Wen, J. Li, and H. H. Chen. "Saturation throughput analysis of WAVE networks in Doppler spread scenarios." IET Communications 4, no. 7 (2010): 817. http://dx.doi.org/10.1049/iet-com.2009.0071.

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