reflected TV signals. UHF-band TSAR imaging requires wide-angle data to produce good cross-range resolution. We show that direct Fourier reconstruction (DFR) causes degradation of the reconstructed image due to aspect-dependent scattering. We find that a Smoothed Pseudo Wigner-Ville distribution (SPWVD) applied in the cross-range direction in place of the Fourier transform can generate a sequence of images, which shows the target reflectivity as a function of aspect angle. Compared to DFR results, these images have higher cross-range resolution. A final image can be synthesized from these images and used for target recogni- tion. XPATCH is used to simulate monostatic data from an aircraft. The proposed SPWVD-based imaging method produces a useful image of the aircraft from this data.

We investigate passive radar imaging of aircraft using reflected TV signals. We apply a Smoothed Pseudo WignerVille Distribution (SPWVD)-based SAR imaging algorithm to two different scenarios. In the first simulation, multistatic VHF-band dataset generated by Fast Illinois Solver Code (FISC) is used. In the second simulation, a more realistic simulated passive radar dataset is used. A set of instantaneous images are produced by our algorithm, which have higher resolution and show more detail and features of the aircraft than can be obtained by Direct Fourier Reconstruction (DFR). The set of images provides visually more information about the target and helps to estimate its shape and features. This study suggests that the SPWVD-based imaging might be useful in passive radar imaging and target classification. 1.

c ° Sa majesté la reine, représentée par le ministre de la Défense nationale, 2003 This report presents trade-off studies on Time-Frequency Distribution (TFD) algorithms and a methodology for fusing them to achieve better target characterization. It is shown that TFD algorithmic fusion considerably increases the detectability of signals while suppressing artifacts and noise. The report reviews a sample of representative TFD algorithms. Their performance is studied from a qualitative and quantitative point of view. For simplicity, we considered the mean-squared error as a measure of performance in the quantitative trade-off studies. The TFD algorithmic fusion is performed using a self-adaptive signal. It may be adjusted to work for a wide range of signal-to-noise ratios. The algorithm uses the first two terms of the Volterra series expansion and we treat the outputs of the time-frequency algorithms as the variables of a Volterra series and the coefficients of the series are estimated through training sets with a least-squares algorithm. Simplistic TFD algorithmic fusion methods (e.g., weighted averaging or weighted multiplication) are special cases of the proposed

In this paper, we introduce the concept of 3-D radar signatures in a slow time-range-Doppler, fast timerange-Doppler and frequency-range-Doppler. Then, we describe how to utilize 3-D time or frequency-range-Doppler signatures to extract information for detecting, relocating and re-focusing moving targets. Finally, we use AN/APY-6 X-band radar data for the demonstration of ground moving target detection. 1