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Relevant bibliographies by topics / Engineering. Radar. Signal processing

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Journal articles

Academic literature on the topic 'Engineering. Radar. Signal processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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Journal articles on the topic "Engineering. Radar. Signal processing"

1

Haykin, S. "Radar signal processing." IEEE ASSP Magazine 2, no. 2 (1985): 2–18. http://dx.doi.org/10.1109/massp.1985.1163737.

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2

Ou, Jianping, Jun Zhang, and Ronghui Zhan. "Processing Technology Based on Radar Signal Design and Classification." International Journal of Aerospace Engineering 2020 (January 17, 2020): 1–19. http://dx.doi.org/10.1155/2020/4673763.

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It is well known that the application of radar is becoming more and more popular with the development of the signal technology progress. This paper lists the current radar signal research, the technical progress achieved, and the existing limitations. According to radar signal respective characteristics, the design and classification of the radar signal are introduced to reflect signal’s differences and advantages. The multidisciplinary processing technology of the radar signal is classified and compared in details referring to adaptive radar signal process, pulse signal management, digital filtering signal mode, and Doppler method. The transmission process of radar signal is summarized, including the transmission steps of radar signal, the factors affecting radar signal transmission, and radar information screening. The design method of radar signal and the corresponding signal characteristics are compared in terms of performance improvement. Radar signal classification method and related influencing factors are also contrasted and narrated. Radar signal processing technology is described in detail including multidisciplinary technology synthesis. Adaptive radar signal process, pulse compression management, and digital filtering Doppler method are very effective technical means, which has its own unique advantages. At last, the future research trends and challenges of technologies of the radar signals are proposed. The conclusions obtained are beneficial to promote the further promotion applications both in theory and practice. The study work of this paper will be useful for choosing more reasonable radar signal processing technology methods.

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3

Hu, Guorong, Yueqiu Han, and Leonard Chin. "ASSP-based radar signal processing." Journal of Electronics (China) 17, no. 2 (2000): 146–52. http://dx.doi.org/10.1007/bf02903192.

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4

Sekine, Matsuo, and Shuji Sayama. "Advances in Radar Signal Processing Techniques." IEEJ Transactions on Fundamentals and Materials 124, no. 1 (2004): 31–34. http://dx.doi.org/10.1541/ieejfms.124.31.

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5

Pease, Herman. "Digital signal processing in airborne radar." Digital Signal Processing 2, no. 1 (1992): 44–46. http://dx.doi.org/10.1016/1051-2004(92)90023-r.

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6

Wardrop, B. "Book review: Aspects of Radar Signal Processing." IEE Proceedings F Radar and Signal Processing 136, no. 1 (1989): 62. http://dx.doi.org/10.1049/ip-f-2.1989.0009.

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7

Lainiotis, D. G., Paraskevas Papaparaskeva, and Kostas Plataniotis. "Nonlinear filtering for LIDAR signal processing." Mathematical Problems in Engineering 2, no. 5 (1996): 367–92. http://dx.doi.org/10.1155/s1024123x96000397.

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LIDAR (Laser Integrated Radar) is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis's multi-model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi-model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF), which has been the standard nonlinear filter in past engineering applications.

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8

Sytnik, Oleg. "SIGNAL PROCESSING ALGORITHM IN MULTICHANNEL RESCUE RADAR." Telecommunications and Radio Engineering 78, no. 17 (2019): 1537–47. http://dx.doi.org/10.1615/telecomradeng.v78.i17.30.

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9

Barbarossa, S., M. Capece, and G. Picardi. "Complex autocorrelation estimators in radar signal processing." Electronics Letters 21, no. 17 (1985): 752. http://dx.doi.org/10.1049/el:19850530.

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10

Kulpa, K., K. Lukin, W. Miceli, and T. Thayaparan. "Editorial: Signal processing in noise radar technology." IET Radar, Sonar & Navigation 2, no. 4 (2008): 229–32. http://dx.doi.org/10.1049/iet-rsn:20089017.

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