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Moving-target detection in ultrawideband (UWB) synthetic aperture radar (SAR) is associated with long integration time and must accommodate azimuth focusing for reliable detection. This paper presents the theory on detection of moving targets by focusing and experimental results on single-channel SAR data aimed at evaluating the detection performance. The results with respect to both simulated and real data show that the ability to detect moving targets increases significantly when applying the proposed detection technique. The improvement in signal-to-clutter noise ratio, which is a basic requisite for evaluating the performance, reaches approximately 20 dB, using only single-channel SAR data. This gain will be preserved for the case of multichannel SAR data. The reference system for this study is the airborne UWB low-frequency SAR Coherent All RAdio BAnd Sensing II. Index Terms-CoherentAll RAdio BAnd Sensing (CARABAS)-II, detection, fast backprojection, fast factorized backprojection (FFBP), moving target, multichannel, single channel, synthetic aperture radar (SAR), ultrawideband (UWB), UWB chirp scaling (UCS). I. INTRODUCTIONO VER the last decades, synthetic aperture radar (SAR) has attracted considerable interest as the number of applications in geoscience, remote sensing, surveillance, and reconnaissance increases. The ability to effectively collect data in severe conditions, such as rain, clouds, and/or darkness, is considered to be the main advantage of SAR systems as compared to other imaging sensors. Ultrawideband (UWB) SAR is understood as SAR systems utilizing either a large absolute bandwidth or a large fractional bandwidth signal and a wide antenna beamwidth. Examples of experimental UWB SAR systems are Coherent All RAdio BAnd Sensing (CARABAS)-II operating in the lower very high frequency (VHF) band from 20 to 90 MHz [1], LORA in the VHF and UHF bands from 200 to 800 MHz [2], P-3 with a bandwidth of 515 MHz in the VHF/UHF bands at 215-900 MHz [3], ground-based BoomSAR with a spectral response extending from 50 to

This paper presents five different statistical methods for ground scene prediction (GSP) in wavelength-resolution synthetic aperture radar (SAR) images. The GSP image can be used as a reference image in a change detection algorithm yielding a high probability of detection and low false alarm rate. The predictions are based on image stacks, which are composed of images from the same scene acquired at different instants with the same flight geometry. The considered methods for obtaining the ground scene prediction include (i) autoregressive models; (ii) trimmed mean; (iii) median; (iv) intensity mean; and (v) mean. It is expected that the predicted image presents the true ground scene without change and preserves the ground backscattering pattern. The study indicates that the the median method provided the most accurate representation of the true ground. To show the applicability of the GSP, a change detection algorithm was considered using the median ground scene as a reference image. As a result, the median method displayed the probability of detection of 97 % and a false alarm rate of 0.11 / km 2 , when considering military vehicles concealed in a forest.

Abstract-A likelihood ratio is proposed for moving target detection in a wide band (WB) SAR system. For this paper, WB is defined as any systems having a large fractional bandwidth, i.e. an ultra wide frequency band combined with a wide antenna beam. The developed method combines time domain fast backprojection SAR processing methods with moving target detection using space-time processing. The proposed method reduces computational load when sets of relative speeds can be tested using the same clutter suppressed sub-aperture beams. The proposed method is tested on narrow band radar data.