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Journal articles on the topic 'Radar cross section'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2025

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1

Tran, N., O.-Z. Zanife, B. Chapron, D. Vandemark, and P. Vincent. "Absolute Calibration of Jason-1 and Envisat Altimeter Ku-Band Radar Cross Sections from Cross Comparison with TRMM Precipitation Radar Measurements." Journal of Atmospheric and Oceanic Technology 22, no. 9 (September 1, 2005): 1389–402. http://dx.doi.org/10.1175/jtech1791.1.

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Abstract One year of collocated, rain-free nadir Ku-band backscatter cross-section measurements from the Tropical Rainfall Mapping Mission (TRMM) precipitation radar (PR) and both Jason-1 and Envisat RA-2 altimeter measurements have been compiled to compare these three sources of Ku-band radar cross section. With the exception of a +1.46 dB relative offset between Jason-1 and PR measurements and a −1.40 dB offset between Envisat and PR ones, all three Ku-band measurements compare very well in terms of dependencies upon model wind speed estimates and significant wave height measurements. The altimeter radars and the rain radar thus provide consistent measurements, and observed biases can be rationalized as differences in the radar calibration. The precipitation radar, which also covers off-nadir measurements, has been absolutely calibrated using an active radar calibrator. Consequently, the observed relative offsets can be used to indirectly calibrate both Jason-1 and Envisat altimeter Ku-band radar cross sections in an absolute sense.

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2

Tian, Zhi-Fu, Di Wu, and Tao Hu. "Theoretical study of single-photon quantum radar cross-section of cylindrical curved surface." Acta Physica Sinica 71, no. 3 (2022): 034204. http://dx.doi.org/10.7498/aps.71.20211295.

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To examine the single-photon quantum radar cross-section of cylindrical surface and its specific advantages over the classical radar cross-section, a photon wave function in which the distance vectors causing interference are decomposed is introduced in this study. A closed-form expression of the single-photon quantum radar cross-section of cylindrical surface is derived. The influences of the length and curvature radius of cylindrical surfaces with different electrical sizes are analyzed, and the closed-form expressions of the quantum and classical radar cross-sections of cylindrical surface are compared with each other. The analyses of the closed-form expression and simulation results show that the electrical length of the cylindrical surface determines the number of side lobes of the quantum radar cross-section; meanwhile, the curvature radius has a linear relation with the overall strength of the quantum radar cross-section, and the electrical size of the curvature radius determines the envelope of the quantum radar cross-section curve. Compared with the classical radar cross-section, the quantum radar cross-section of a cylindrical surface has the advantage of side-lobe enhancement, which is beneficial for detecting stealth targets.

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3

Dybdal, R. B. "Radar cross section measurements." Proceedings of the IEEE 75, no. 4 (1987): 498–516. http://dx.doi.org/10.1109/proc.1987.13757.

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4

Grant, P. M. "Editorial: Radar cross-section." IEE Proceedings F Radar and Signal Processing 137, no. 4 (1990): 213. http://dx.doi.org/10.1049/ip-f-2.1990.0032.

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5

Liao, Wen-Jiao, Yuan-Chang Hou, Chin-Che Tsai, Tai-Heng Hsieh, and Hao-Ju Hsieh. "Radar Cross Section Enhancing Structures for Automotive Radars." IEEE Antennas and Wireless Propagation Letters 17, no. 3 (March 2018): 418–21. http://dx.doi.org/10.1109/lawp.2018.2793307.

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6

Iwaszczuk, Krzysztof, Henning Heiselberg, and Peter Uhd Jepsen. "Terahertz radar cross section measurements." Optics Express 18, no. 25 (December 1, 2010): 26399. http://dx.doi.org/10.1364/oe.18.026399.

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7

Zdunek, Adam, and Waldemar Rachowicz. "Cavity Radar Cross Section Prediction." IEEE Transactions on Antennas and Propagation 56, no. 6 (June 2008): 1752–62. http://dx.doi.org/10.1109/tap.2008.923357.

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8

Borkar, V., A. Ghosh, R. Singh, and N. Chourasia. "Radar Cross-section Measurement Techniques." Defence Science Journal 60, no. 2 (March 25, 2010): 204–12. http://dx.doi.org/10.14429/dsj.60.341.

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9

Riley, J. R. "Radar cross section of insects." Proceedings of the IEEE 73, no. 2 (1985): 228–32. http://dx.doi.org/10.1109/proc.1985.13135.

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10

Jenn, David, and Cuong Ton. "Wind Turbine Radar Cross Section." International Journal of Antennas and Propagation 2012 (2012): 1–14. http://dx.doi.org/10.1155/2012/252689.

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The radar cross section (RCS) of a wind turbine is a figure of merit for assessing its effect on the performance of electronic systems. In this paper, the fundamental equations for estimating the wind turbine clutter signal in radar and communication systems are presented. Methods of RCS prediction are summarized, citing their advantages and disadvantages. Bistatic and monostatic RCS patterns for two wind turbine configurations, a horizontal axis three-blade design and a vertical axis helical design, are shown. The unique electromagnetic scattering features, the effect of materials, and methods of mitigating wind turbine clutter are also discussed.

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11

Ma, Yue, Weimin Huang, and Eric W. Gill. "Bistatic High Frequency Radar Ocean Surface Cross Section for an FMCW Source with an Antenna on a Floating Platform." International Journal of Antennas and Propagation 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/8675964.

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The first- and second-order bistatic high frequency radar cross sections of the ocean surface with an antenna on a floating platform are derived for a frequency-modulated continuous wave (FMCW) source. Based on previous work, the derivation begins with the general bistatic electric field in the frequency domain for the case of a floating antenna. Demodulation and range transformation are used to obtain the range information, distinguishing the process from that used for a pulsed radar. After Fourier-transforming the autocorrelation and comparing the result with the radar range equation, the radar cross sections are derived. The new first- and second-order antenna-motion-incorporated bistatic radar cross section models for an FMCW source are simulated and compared with those for a pulsed source. Results show that, for the same radar operating parameters, the first-order radar cross section for the FMCW waveform is a little lower than that for a pulsed source. The second-order radar cross section for the FMCW waveform reduces to that for the pulsed waveform when the scattering patch limit approaches infinity. The effect of platform motion on the radar cross sections for an FMCW waveform is investigated for a variety of sea states and operating frequencies and, in general, is found to be similar to that for a pulsed waveform.

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12

Silva, Murilo Teixeira, Weimin Huang, and Eric W. Gill. "Bistatic High-Frequency Radar Cross-Section of the Ocean Surface with Arbitrary Wave Heights." Remote Sensing 12, no. 4 (February 18, 2020): 667. http://dx.doi.org/10.3390/rs12040667.

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The scattering theory developed in the past decades for high-frequency radio oceanography has been restricted to surfaces with small heights and small slopes. In the present work, the scattering theory for bistatic high-frequency radars is extended to ocean surfaces with arbitrary wave heights. Based on recent theoretical developments in the scattering theory for ocean surfaces with arbitrary heights for monostatic radars, the electric field equations for bistatic high-frequency radars in high sea states are developed. This results in an additional term related to the first-order electric field, which is only present when the small-height approximation is removed. Then, the radar cross-section for the additional term is derived and simulated, and its impact on the total radar cross-section at different radar configurations, dominant wave directions, and sea states is assessed. The proposed term is shown to impact the total radar cross-section at high sea states, dependent on radar configuration and dominant wave direction. The present work can contribute to the remote sensing of targets on the ocean surface, as well as the determination of the dominant wave direction of the ocean surface at high sea states.

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13

Odendaal, J. W., and J. Joubert. "Radar cross section measurements using near-field radar imaging." IEEE Transactions on Instrumentation and Measurement 45, no. 6 (1996): 948–54. http://dx.doi.org/10.1109/19.543991.

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14

osman, Tarig ibrahim. "Algorithm for Radar cross section estimation." IOSR Journal of Engineering 4, no. 10 (October 2014): 48–50. http://dx.doi.org/10.9790/3021-041034850.

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15

Lanusse, Alain F., and Pierre Fuerxer. "Radar cross section of complex objects." Annales Des Télécommunications 50, no. 5-6 (May 1995): 472. http://dx.doi.org/10.1007/bf02995745.

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16

Veselovska, G. B., and G. I. Khlopov. "RADAR CROSS SECTION OF NONSPHERICAL RAINDROPS." Telecommunications and Radio Engineering 74, no. 12 (2015): 1085–97. http://dx.doi.org/10.1615/telecomradeng.v74.i12.40.

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17

Gordon, W. B. "Statistical moments of radar cross section." IEEE Transactions on Antennas and Propagation 41, no. 4 (April 1993): 506–8. http://dx.doi.org/10.1109/8.220985.

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18

Rino, Charles L. "Double-passage radar cross section enhancements." Radio Science 29, no. 2 (March 1994): 495–501. http://dx.doi.org/10.1029/93rs02733.

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19

Sihvola, Sarkar, and Kolundzija. "From radar cross section to electrostatics." IEEE Antennas and Wireless Propagation Letters 3 (2004): 324–27. http://dx.doi.org/10.1109/lawp.2004.839459.

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20

Nagl, A., D. Ashrafi, and H. Uberall. "Radar cross section of thin wires." IEEE Transactions on Antennas and Propagation 39, no. 1 (1991): 105–8. http://dx.doi.org/10.1109/8.64443.

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21

Youssef, N. N. "Radar cross section of complex targets." Proceedings of the IEEE 77, no. 5 (May 1989): 722–34. http://dx.doi.org/10.1109/5.32062.

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22

Swarnalingam, N., W. K. Hocking, and P. S. Argall. "Radar efficiency and the calculation of decade-long PMSE backscatter cross-section for the Resolute Bay VHF radar." Annales Geophysicae 27, no. 4 (April 7, 2009): 1643–56. http://dx.doi.org/10.5194/angeo-27-1643-2009.

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Abstract. The Resolute Bay VHF radar, located in Nunavut, Canada (75.0° N, 95.0° W) and operating at 51.5 MHz, has been used to investigate Polar Mesosphere Summer Echoes (PMSE) since 1997. PMSE are a unique form of strong coherent radar echoes, and their understanding has been a challenge to the scientific community since their discovery more than three decades ago. While other high latitude radars have recorded strong levels of PMSE activities, the Resolute Bay radar has observed relatively lower levels of PMSE strengths. In order to derive absolute measurements of PMSE strength at this site, a technique is developed to determine the radar efficiency using cosmic (sky) noise variations along with the help of a calibrated noise source. VHF radars are only rarely calibrated, but determination of efficiency is even less common. Here we emphasize the importance of efficiency for determination of cross-section measurements. The significant advantage of this method is that it can be directly applied to any MST radar system anywhere in the world as long as the sky noise variations are known. The radar efficiencies for two on-site radars at Resolute Bay are determined. PMSE backscatter cross-section is estimated, and decade-long PMSE strength variations at this location are investigated. It was noticed that the median of the backscatter cross-section distribution remains relatively unchanged, but over the years a great level of variability occurs in the high power tail of the distribution.

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23

Lee, Samuel. "The Role of Radar Cross-Section in Advanced Aircraft Stealth Design." Highlights in Science, Engineering and Technology 120 (December 25, 2024): 283–89. https://doi.org/10.54097/b56kmh05.

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This paper aims to give an introduction into the radar cross-section of objects. Specifically, it goes into the importance that the radar cross-section has on the design of stealth aircraft. It provides the importance of the radar cross-section in the construction of stealth aircraft and why it is such an important factor, outlines the definition of radar cross-section, and describes multiple methods of calculating it. This paper will cover three methods of calculating radar cross-section, being Geometric Optics, Physical Optics and the Method of Moments. It details how the methods function, what they should be used for when calculating radar cross-section of aircraft, and steps and formulas that will solve the RCS of the target object. Finally, it gives an insight into the future design direction of sixth-generation stealth aircraft, what a future sixth-gen fighter would have compared to the current fifth-generation fighters of today, and other fields where radar stealth is an important factor, such as the creation of stealth warships.

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24

Phruksahiran, N., and M. Chandra. "Polarimetric radar cross section under SAR geometry." Advances in Radio Science 11 (July 4, 2013): 277–82. http://dx.doi.org/10.5194/ars-11-277-2013.

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Abstract. In this paper, the radar cross section of canonical scatter, with perfectly conducting surface, under the synthetic aperture radar geometry and polarized electromagnetic wave, has been considered and a new approach of polarized scattered electric field approximation for its evaluation has been developed.

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25

Persson, B. "Radar Target Modeling Using In-Flight Radar Cross-Section Measurements." Journal of Aircraft 54, no. 1 (January 2017): 284–91. http://dx.doi.org/10.2514/1.c033932.

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26

Theron, I. P., E. K. Walton, and S. Gunawan. "Compact range radar cross-section measurements using a noise radar." IEEE Transactions on Antennas and Propagation 46, no. 9 (1998): 1285–88. http://dx.doi.org/10.1109/8.719971.

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27

Choi, Won‐Ho, Byeong‐Su Kwak, and Young‐Woo Nam. "Radar absorbing serrated edge for broadband radar cross‐section reduction." Microwave and Optical Technology Letters 62, no. 3 (November 11, 2019): 1112–16. http://dx.doi.org/10.1002/mop.32152.

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28

Kazantsev, A. A., B. A. Samorodov, and A. M. Terentev. "Methodological Approach to Reducing the Radar Cross Section of Local Scatterer under Given Frequency-Angular Observation Conditions." Ural Radio Engineering Journal 5, no. 2 (2021): 162–78. http://dx.doi.org/10.15826/urej.2021.5.2.005.

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This paper focuses on application of spectral estimation methods for scattering center’s radar cross section estimation and reduction under given frequency-angular observation conditions. A methodological approach has been developed to reduce the local center’s radar cross section with given object overall dimensions. The developed methodological approach is based on parametric optimization of object geometry, firstly, to reduce the local scatterer radar cross section and, secondly, to maximize object payload. The problem overview is presented in the introduction. The first section is devoted to mathematical formulation of the problem. The following section includes the comparison analysis of the different types of geometrical shapes. As a result, the object with exponential profile is chosen as the best one due to the ability to manage rear vertex local scatterer amplitude by changing the curvature parameter. In the third section the optimal curvature parameter value of the exponential profile is justified for the given object overall dimensions and frequency-angular observation conditions. It is demonstrated that the main characteristic to analysis is two-dimension functional dependence of the local scatterer mean radar cross section from geometrical parameter and angle of observation. It is proved that this mentioned dependence may be received by the implementation such well-known spectral estimation method as CLEAN to the object sinogram. The recognition range is calculated for two different hypothetical radars to assert the efficiency. It is offered in the conclusion to complicate the developed approach with radio absorption materials implementation as the direction of the future investigations.

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29

Sautin, O., M. Solodchuk, S. Kozak, L. Zozulia, and M. Gerashchenko. "UNMANNED AERIAL VEHICLE RADAR VISIBILITY ESTIMATION PROCEDURE DURING THE FLIGHT TEST." Наукові праці Державного науково-дослідного інституту випробувань і сертифікації озброєння та військової техніки, no. 10 (December 30, 2021): 124–28. http://dx.doi.org/10.37701/dndivsovt.10.2021.14.

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The calculation and accurate determination of the main indicator of radar visibility - radar cross-section is a complex problem for which theoretical and experimental methods have been developed. Theoretical methods for determining the radar cross-section at this time are quite accurate, but the priority area of research is still to determine the radar cross-section by the experimental method. One of such practical methods for determining the radar cross-section is a model (and for small unmanned aerial vehicles - full-scale) experiment in a anechoic screened chamber, but this experiment does not take into account the propagation properties of radio wave in real conditions. The most reliable characteristics of the unmanned aerial vehicle (UAV) radar visibility are obtained in a full- scale experiment during a testing ground experiment by test flight. Determination of the radar cross-section by the test flight method is carried out in real conditions under the influence of all available factors for the radio detection and location, methods of its processing, the presence of spurious reflection, the real jamming environment. A signals training area is used as a test range. A signals training area is an spatial region (sector of the terrain) where the instrumentation radar set and certain spatio measuring points arе located and the signal-noise-rate of the radar sеt receive path is measured when the unmanned aerial vehicle to be in the spatio measuring points. It should be noted that any radar set can be used as a instrumentation radar set, subject to conformity with the measurement accuracy meets the specified requirements. Given the above, the UAV radar visibility evaluation procedure during testing ground experiment by test flight allows to determine the radar cross-section in the absence of a perfect measuring system and provides a high level of measurement accuracy.

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30

Volosyuk, Valeriy, Simeon Zhyla, Vladimir Pavlikov, Dmitriy Vlasenko, Vladimir Kosharskiy, Denis Kolesnikov, Olga Inkarbaeva, and Kseniya Nezhalskaya. "Optimal radar cross section estimation in synthetic aperture radar with planar antenna array." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 1 (February 27, 2021): 50–59. http://dx.doi.org/10.32620/reks.2021.1.04.

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The optimization problem of statistical synthesis of the method for radar cross section estimation in synthetic aperture radar with planar antenna array is solved. The desired radar cross section is given as a statistical characteristic of a spatially inhomogeneous complex scattering coefficient of the studying media. In fact it is developed new methods of inverse problems solution not with respect to the restoration of coherent images in the form of spatial distribution of complex scattering coefficient but with respect to the statistical characteristics of inhomogeneous (spatially nonstationary) random processes. The electrophysical parameters of surfaces and their statistical characteristics are considered as functions of spatial coordinates. The maximum likelihood method was chosen as the optimization method. The obtained results make it possible to determine the multichannel structure, the optimal method of surface observation and the potential spatial resolution in aerospace scatterometric radars with antenna array. Optimal operations for processing space-time signals are determined and a modified method for synthesizing antenna aperture is proposed, which in contrast to the classical algorithm for synthesizing antenna aperture that integrates the product of the received signal and the reference signal equal to a single signal additionally implements the decorrelation of signals reflected from the earth's surface, The new operation of the scattered signals decorrelation consists in their integration with the space-time inverse correlation function. To confirm the reliability of the results obtained, simulation modeling of the classical method for the synthesis of coherent images and the proposed optimal one was carried out. From the analysis of the results it flows that propose method has higher quality and smaller size of spackle noise. The results obtained in the article can be used to develop and substantiate the requirements for the tactical and technical characteristics of promising aerospace-based scatterometric radars with planar phased antenna arrays.

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31

Vinh, Hoang, C. P. van Dam, and Harry A. Dwyer. "Airfoil shaping for reduced radar cross section." Journal of Aircraft 31, no. 4 (July 1994): 787–93. http://dx.doi.org/10.2514/3.46562.

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32

Jan Melin. "Measuring radar cross section at short distance." IEEE Transactions on Antennas and Propagation 35, no. 8 (August 1987): 991–96. http://dx.doi.org/10.1109/tap.1987.1144212.

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33

Bokhari, S. A., J. R. Mosig, and F. E. Gardiol. "Radar Cross Section Computation of Microstrip Patches." Electromagnetics 14, no. 1 (January 1994): 19–32. http://dx.doi.org/10.1080/02726349408908367.

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34

Sanford, J. R. "Analysis of spherical radar cross-section enhancers." IEEE Transactions on Microwave Theory and Techniques 43, no. 6 (June 1995): 1400–1403. http://dx.doi.org/10.1109/22.390205.

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35

Esmaeli, S. H., and S. H. Sedighy. "Wideband radar cross‐section reduction by AMC." Electronics Letters 52, no. 1 (January 2016): 70–71. http://dx.doi.org/10.1049/el.2015.3515.

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36

Lekic, Nikola. "Radar cross section analysis of rotating objects." Vojnotehnicki glasnik 51, no. 4-5 (2003): 465–71. http://dx.doi.org/10.5937/vojtehg0305465l.

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37

Li, H. J., N. H. Farhat, and Y. Shen. "Radar Cross Section Reduction by Absorber Covering." Journal of Electromagnetic Waves and Applications 3, no. 3 (January 1, 1989): 219–35. http://dx.doi.org/10.1163/156939389x00467.

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38

White, M. O. "Radar cross-section: measurement, prediction and control." Electronics & Communication Engineering Journal 10, no. 4 (August 1, 1998): 169–80. http://dx.doi.org/10.1049/ecej:19980403.

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39

Zaporozhets, A. A., and M. F. Levy. "Radar cross-section calculation with marching methods." Electronics Letters 34, no. 20 (1998): 1971. http://dx.doi.org/10.1049/el:19981342.

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40

Sevgi, Levent, Zubair Rafiq, and Irfan Majid. "Radar cross section (RCS) measurements [Testing ourselves]." IEEE Antennas and Propagation Magazine 55, no. 6 (December 2013): 277–91. http://dx.doi.org/10.1109/map.2013.6781745.

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41

Smith, F. C. "Measurement of diffraction radar cross-section (RCS)." Electronics Letters 36, no. 9 (2000): 830. http://dx.doi.org/10.1049/el:20000591.

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42

Şeker, Ş S. "Radar cross-section of thin dielectric bodies." IEE Proceedings H Microwaves, Antennas and Propagation 133, no. 4 (1986): 305. http://dx.doi.org/10.1049/ip-h-2.1986.0053.

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43

Shuhui, Deng, and Ruan Yingzheng. "Monostatic radar cross section for reflector antennas." Journal of Electronics (China) 8, no. 1 (January 1991): 28–35. http://dx.doi.org/10.1007/bf02784410.

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44

Ongareau, Eric, Alain Roussaud, Eric Marouby, and Jean-René Levrel. "Radar cross-section reduction by polarization rotation." Microwave and Optical Technology Letters 8, no. 6 (April 20, 1995): 316–18. http://dx.doi.org/10.1002/mop.4650080616.

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45

Selleri, Stefano. "On the radar cross section of dragons." URSI Radio Science Bulletin 2021, no. 378 (September 2021): 59–61. http://dx.doi.org/10.23919/ursirsb.2021.10292814.

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46

Zhao, Hangyu, Yeping Lai, Yuhao Wang, and Hao Zhou. "High-Frequency Radar Cross Section of Ocean Surface for an FMICW Source." Journal of Marine Science and Engineering 9, no. 4 (April 15, 2021): 427. http://dx.doi.org/10.3390/jmse9040427.

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The frequency-modulated interrupted continuous waveform (FMICW) has been widely used in remotely sensing sea surface states by high-frequency ground wave radar (HFGWR). However, the radar cross section model of the sea surface for this waveform has not yet been presented. Therefore, the first- and second-order cross section models of the sea surface about this waveform are derived in this study. The derivation begins with the general electric field equations. Subsequently, the FMICW source is introduced as the radar transmitted signal to obtain the FMICW-incorporated backscattered electric field equations. These equations are used to calculate range spectra by Fourier transforming. Therefore, Fourier transformation of the range spectra calculated from successive sweep intervals gives the Doppler spectra or the power spectral densities. The radar cross section model is obtained by directly comparing the Doppler spectra with the standard radar range equation. Moreover, the derived first- and second-order radar cross section models for an FMICW source are simulated and compared with those for a frequency-modulated continuous waveform (FMCW) source. Results show that the cross section models for the FMICW and FMCW cases have different analytical expressions but almost the same numerical results.

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47

Briggs, J. N. "Specifications for Reflectors and Radar Target Enhancers to Aid Detection of Small Marine Radar Targets." Journal of Navigation 55, no. 1 (January 2002): 23–38. http://dx.doi.org/10.1017/s0373463301001564.

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This paper considers the need for better detectability of small targets at sea using marine radars in the 3 and 9 GHz bands. The problems of using radar reflectors and radar target enhancers to improve radar cross section, particularly when clutter is present, are discussed in detail. The IMO carriage requirement and the lack of suitably robust specifications are highlighted, and a proposal is made for a standard family of radar reflectors to meet the requirement. Radar target enhancers are also considered together with how these and radar reflectors should be mounted for best effect.

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48

Lipa, Barrick, and Whelan. "A Quality Control Method for Broad-Beam HF Radar Current Velocity Measurements." Journal of Marine Science and Engineering 7, no. 4 (April 19, 2019): 112. http://dx.doi.org/10.3390/jmse7040112.

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This paper describes a method to provide quality control for radial velocity maps derived from radar echo voltage cross spectra measured by broad-beam high frequency radars. The method involves the comparison of voltage cross spectra measured at Doppler frequencies in the Bragg region with values predicted from basic equations defining the complex voltage cross spectra in terms of the measured antenna patterns and the radar cross section. Poor agreement at a given Doppler frequency indicates contamination of the spectra, usually due to interference; velocity results from that Doppler frequency are then eliminated. Examples are given of its application to broad-beam radars operating at four sites.

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49

Oh, Soo Young, Kyu Ho Cha, Hayoung Hong, Hongsoo Park, and Sun K. Hong. "Measurement of Nonlinear RCS of Electronic Targets for Nonlinear Detection." Journal of Electromagnetic Engineering and Science 22, no. 4 (July 31, 2022): 447–51. http://dx.doi.org/10.26866/jees.2022.4.r.108.

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The conventional radar technology is based on linear detection—i.e., the same transmit and receive frequencies are used. However, with linear radars, difficulties arise when detecting electronic objects with relatively small radar cross section (RCS). To overcome these limitations, a nonlinear radar that can detect nonlinear responses (i.e., harmonic and intermodulation) scattered by electronic devices due to nonlinear interaction can be utilized. Nonlinear radars require a different analysis from linear radars for analyzing RCS. In this paper, we present an experimental analysis of the nonlinear RCS of various electronic devices. Unlike linear radars, RCS in nonlinear radars is determined by the amount of nonlinear responses backscattered to the radar. Therefore, we derive a radar equation accustomed to harmonic radars that consists of nonlinear RCS. We then obtain and analyze the nonlinear RCS of various targets from the measured harmonic responses of the targets based on the nonlinear radar equation.

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Hobbs, S. E., and A. C. Aldhous. "Insect ventral radar cross-section polarisation dependence measurements for radar entomology." IEE Proceedings - Radar, Sonar and Navigation 153, no. 6 (2006): 502. http://dx.doi.org/10.1049/ip-rsn:20060019.

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