RFI suppression for SAR systems based on LMS adaptive filtering

Radio Frequency Interference (RFI) suppression has been an essential technique in Synthetic Aperture Radar (SAR) imaging. SAR is a technique for creating high resolution images of the earth’s surface. Over the area of the surface being observed, these images represent the backscattered microwave energy, which depends on the properties of the surface, such as its slope, roughness, textural in homogeneities and dielectric constant. The radar backscattering cross section also depends strongly on the existence of vegetation. These dependencies allow SAR imagery to be used in conjunction with models of the scattering mechanism to measure various characteristics of the earth’s surface, such as topography. An important characteristic of SAR is its day/night capability, which it possesses because it supplies its own illumination and receives the backscatter from it, as opposed to passive sensors which receive either the earth’s radiation or the reflected illumination from the sun. Furthermore, a SAR sensor has all-weather capability, because microwaves propagate through clouds and rain with only limited attenuation. These features, together with its fine two-dimensional resolution capability, have made SAR a valuable remote sensing tool for both military and civilian users. The VHF/UHF bands has been found to have significant advantages for air and ground survelliance application. However, from the point of view of SAR implementations, the VHF/UHF portion of the spectrum is already in heavy use by other services, such as television, mobile communications, radio and cellular phones. Even in remote locations the interference power often exceeds receiver noise by many dB, becoming the limiting factor on system sensitivity and severely degrading the image quality. Therefore it is important to investigate possible means of suppressing the interference in the received signal. MetaSensing B.V. asked the candidate to investigate this issue on P band data acquired by them with an airborne SAR system during an acquisition campaign in September 2013. In order to alleviate the problem of Radio Frequency Interference (RFI), it is proposed in this thesis to use an Adaptive Line Enhancer(ALE) controlled by the Normalised Least Mean Squares (NLMS) algorithm to eliminate RFI. Experimental results demonstrate that the filter improves the image result. Results from application of this algorithm to real radar data aicted with interference are presented