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A variety of problems arising in imaging, radar, and localization amount to recover a signal that is sparse in a continuous indexed dictionary. Line spectral estimation theory considers a particular instance of this problem, namely that of estimating the frequency and magnitude components of a sum of complex sinusoids from uniformly spaced samples. In this work we consider the significantly more general...
It is attractive for wideband Radar system that sampling rate can be reduced by compressed sensing method. The GTD model can simulate wideband scattering with high accuracy. A compressed sensing method for parameter estimation of GTD model is proposed, and is applied in tomographic SAR imaging. By this method, complex scatter intensity can be estimated accurately.
We propose a framework for coherent MIMO radar imaging that allows to combine range imaging using iterative block sparse recovery with conventional, grid-less azimuth imaging. In each iteration of a block-sparse range recovery algorithm, we incorporate a projection step using an arbitrary azimuth imaging algorithm. The proposed imaging framework is hence not limited to azimuth imaging on a grid. This...
Phase-shift-based Time-of-Flight (ToF) imaging systems estimate the distances from the camera to the scene points from the phase shift undergone by a modulated light signal, projected onto the scene, instead of actually performing time measurements. The phase shift is typically computed from several values of the cross-correlation between the light signal received by each pixel and a reference signal...
It is a pleasure to introduce this special section of the IEEE Transactions on Aerospace and Electronic Systems (T-AES), linked to the 1st International Workshop on Compressive Sensing applied to Radar/SAR (CoSeRa), which was held in Bonn, Germany, in May 2012. During this workshop more than 40 scientists and researchers from all over the world presented their ongoing work in this area. The program,...
Degeneration of inverse synthetic aperture radar (ISAR) image quality may be caused by rotational motion induced quadratic phase error (QPE). Traditional algorithms can't correct the QPE well with smaller number of pulses. In this paper, the Parametric Compressed Sensing Least Square (PCS-LS) is proposed to compensate the QPE on each range bin and to reconstruct the image robustly. Mig-25 data is...
We study the compressive radar imaging problem from the perspective of statistical estimation. The goal of this paper is to characterize the estimation error. Conventional radar estimation and detection techniques are characterized by concrete performance guarantees which relate directly to practical systems. The state evolution approach applied to compressive sensing is particularly useful for such...
Differential SAR tomography extends the synthetic aperture principle into the elevation and time directions for 4-D imaging. With modern meter-resolution space-borne SAR systems like TerraSAR-X (TS-X), systematic tomographic imaging of urban infrastructure and its deformations becomes feasible. We demonstrate the potential of TS-X data for this purpose and introduce several novel concepts. Since building...
The authors recently proposed a parameter estimation technique for multiple-input/multiple-output (MIMO) radar systems that employ compressive sensing (CS), and which applies to the case of slowly moving targets. This technique is based on the use of a step-frequency technique, and it allows angle, Doppler and range information to be estimated in a decoupled fashion. This decoupling significantly...
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