Radar Sensors

Principle

• SAR techniques provide high-resolution remote sensing images, independent of flight altitude, and independent of weather, as SAR can select frequencies to avoid weather-caused signal attenuation. SAR has day and night imaging capability as illumination is provided by the SAR (Moreira et al., Gao, Yue et al.)

• Radar sensors can be classified into the following categories: monostatic SAR (SAR), Bistatic SAR (BiSAR), Interferometry SAR (InSAR), Polarimetry SAR (PolSAR) and UWB SAR.

Synthetic-Aperture Radar (SAR)

• Synthetic-aperture radar (SAR) is a form of radar sensor that allows to create two-dimensional images or three-dimensional reconstructions of objects.

• SAR employs the motion of the radar antenna over a target region to provide spatial resolution which is finer than conventional stationary beam-scanning radars. 

Bistatic SAR (BiSAR/BSAR)

• BiSAR is a SAR system whose transmitter and receiver are spatially separated. 

• This separation improves the system’s capability, reliability and flexibility, making it a promising and useful supplement to a classical monostatic SAR system.

• Bistatic SAR can be classified into sub-classes: Space-Surface Bistatic SAR (SS-BSAR) and Bistatic Forward-looking SAR (BFSAR).

Interferometry SAR (InSAR)

• Interferometry SAR employs the phase data because information can be extracted from it. 

• Interferometry SAR can be classified into sub-classes: Interferometry SAR (inSAR) and Differential interferometry (D-InSAR).

Polarimetry SAR (PolSAR)

• SAR polarimetry is a technique used for deriving qualitative and quantitative physical information based on the measurement and exploration of the polarimetric properties.

• Polarimetry SAR can be classified into sub-classes: Polarimetry SAR (PolSAR) and Polarimetry Interferometry (PolInSar).

Ultra-wideband SAR (UWB SAR)

• Ultra-wideband (UWB) SAR refers to any radio transmission system that uses a very large bandwidth instead of conventional radar systems which provides radio energy with a fairly narrow range of frequencies. 

• UWB allows rapid changes in modulation instead of a narrow-band channel. 

• UWB SAR provides better resolution and more spectral information of target reflectivity.

Location

Radar sensors are typically mounted on a moving platform, such as an aircraft or spacecraft. 

Radars can be classified according to their location as follows (Richards et al., Melvin et al.) :

• • Surface-based radar: Ground-based and sea-based including vehicle-borne and ship-based radar.

  • Airborne radar.

  • Space-based radar.

In addition, the space is divided into different areas (See Figure 1  from Li et al.) :

• • Air.

  • Near space.

  • Geosynchronous Orbit (GEO)

  • Middle Earth Orbit (MEO)

  • Low Earth Orbit (LEO)

 Figure 1

References

A. Moreira, P. Prats-Iraola, M. Younis, G. Krieger, I. Hajnsek, K. Papathanassiou, “A tutorial on synthetic aperture radar", IEEE Geoscience and Remote Sensing Magazine, Volume 1, No. 1, pages 6–43, 2013.

G. Gao, “Statistical modeling of SAR images: A survey", MDPI Sensors, Volume 10, No. 1, pages 775–795, 2010.

D. Yue, F. Xu, A. Frery, Y. Jin, “Synthetic aperture radar image statistical modeling: Part one-single-pixel statistical models", IEEE Geoscience and Remote Sensing Magazine, Volume 9, No. 1, pages 82–114, 2020.

M. Richards, J. Scheer, W. Holm, "Principles of Modern Radar", Volume I: Basic Principles; SciTechPublishing: Edison, NJ, USA, 2013.

W. Melvin, J. Scheer, "Principles of Modern Radar", Volume III, Radar Applications; SciTech Publishing: Edison, NJ, USA, 2013.

Y. Li, X. Li, H. Wang, B. Deng, Y. Qin, “Performance Evaluation of Target Detection with a Near-Space Vehicle-Borne Radar in Blackout Condition”, MDPI Sensors, 2016.