Region-enhanced passive radar imaging

The authors adapt and apply a recently-developed region-enhanced synthetic aperture radar (SAR) image reconstruction technique to the problem of passive radar imaging. One goal in passive radar imaging is to form images of aircraft using signals transmitted by commercial radio and television stations that are reflected from the objects of interest. This involves reconstructing an image from sparse samples of its Fourier transform. Owing to the sparse nature of the aperture, a conventional image formation approach based on direct Fourier transformation results in quite dramatic artefacts in the image, as compared with the case of active SAR imaging. The regionenhanced image formation method considered is based on an explicit mathematical model of the observation process; hence, information about the nature of the aperture is explicitly taken into account in image formation. Furthermore, this framework allows the incorporation of prior information or constraints about the scene being imaged, which makes it possible to compensate for the limitations of the sparse apertures involved in passive radar imaging. As a result, conventional imaging artefacts, such as sidelobes, can be alleviated. Experimental results using data based on electromagnetic simulations demonstrate that this is a promising strategy for passive radar imaging, exhibiting significant suppression of artefacts, preservation of imaged object features, and robustness to measurement noise

Multifrequency Aperture-Synthesizing Microwave Radiometer System (MFASMR). Volume 1

Background material and a systems analysis of a multifrequency aperture - synthesizing microwave radiometer system is presented. It was found that the system does not exhibit high performance because much of the available thermal power is not used in the construction of the image and because the image that can be formed has a resolution of only ten lines. An analysis of image reconstruction is given. The system is compared with conventional aperture synthesis systems

Time and spatial filtering for echo reduction in antenna measurements

During the last years, new algorithms, based on time filtering, spatial or modal filtering, have been designed for echo reduction techniques applied to antenna measurements. These algorithms have been used for different applications where the effect of the echoes is important, as far field system, VHF or UHF applications, automotive systems, small antennas, etc. The authors, in previous papers, have analysed the effect of different algorithms: time filtering (fft, non uniform dft or matrix pencial), modal filtering based on Spherical modes (MV-Echo) and spatial filtering based on Integral Equations (Insight) and holographic techniques (fft and dft) to cancel the effect of the reflections. This comparison has been applied to the measurements of a dipole antenna (SD1900) using a StarLab system. It is observed that each of the algorithms is better for different situations, depending on the source of the echo. For instance, time filtering techniques are good for reflections coming from different distances with respect the direct ray, but not so good for close reflections. In addition hey need a large frequency band to work properly. Spatial algorithms can correct the effect of positioners or other structures close to the antenna under test, but they are better for planar near field acquisitions and worse for classical single probe spherical near field where the antenna is rotated and probe is fixed (e.g. roll-over-azimuths systems). Moreover, they require extra information of the AUT geometry. This paper presents first a comparison of each algorithm and then, a combination of time and spatial techniques based on uniform or non-uniform DFT to take advantage of the benefits of each algorithm for different origins of the reflections

Accurate Reconstruction and Suppression for Azimuth Ambiguities in Spaceborne Stripmap SAR Images

In this letter, an accurate mathematical model for azimuth ambiguity in stripmap synthetic aperture radar (SAR) images is first constructed, with an azimuth ambiguity factor (AAF) defined as the residual amplitude and phase terms of ambiguities. Next, a novel framework for reconstructing and suppressing azimuth ambiguity is proposed based on the analysis of the AAF. In this framework, azimuth ambiguities are accurately reconstructed by applying reconstruction filters in the range Doppler and 2-D frequency domain, and then, the reconstructed signal is used for suppressing azimuth ambiguities. Moreover, the proposed framework does not depend on the statistical characteristics of a SAR image and is capable of reducing the space-variant ambiguities. As verified by both simulated data and real TerraSAR-X data, the proposed method is capable of suppressing azimuth ambiguities in SAR images

Combination of time and spatial filtering to improve echo reduction in antenna measurements

Different research groups have been working during the last years in different echo reduction techniques applied to antenna measurements, based on spatial, modal or time filtering. Some applications where these methods are usually employed are: outdoor systems, for HF or VHF frequency systems or for small measurement systems where the anechoic material is only placed in front of the AUT. This paper analyzes the measurements of a dipole antenna (SD1900) using a StarLab system and the application of the different algorithms. It is observed that each of the algorithms is better for different situations, depending for instance on the angular value of the pattern. Finally, a combination of different methods in a smart way improve the results of the post processing with respect each independent method