This paper proposes a synthetic aperture radar (SAR) automatic target recognition approach based on global scattering center model. The model is established offline using range profiles at multiple viewing angles, so the original data amount much less than that required for establishing SAR image templates. Scattering features different poses can be conveniently predicted by this Moreover, modified to predict various configurations. For classified, regional in levels are extracted...

Continuous respiratory monitoring is an important tool for clinical monitoring. Associated with the development of biomedical technology, it has become more and important, especially in measuring gas flow CO2 concentration, which can reflect status patient. In this paper, a new type device presented, uses low-power sensors piezoresistive silicon differential pressure sensor to measure pyroelectric concentration simultaneously. For portability device, measurement circuits are integrated...

In the existing compressed sensing (CS) theory, accurate reconstruction of an unknown signal lies in awareness its sparsifying dictionary. For represented by a finite sum complex sinusoids, however, it is impractical to set fixed Fourier dictionary prior due our ignorance signal's component frequencies. To address this, we model as parameterized dictionary, with sampled frequency grid points treated underlying parameters. Consequently, refinable during process, and refinement can be...

In this letter, a 3-D range migration algorithm for multiple-input multiple-output synthetic aperture radar imaging is proposed. The accurate expression of the signal spectrum derived by utilizing spherical wave decomposition. This method compensates curvature wavefront in wavenumber domain and achieves Fourier transform reflectivity map through dimension-reducing accumulation operation. Its fast transform-based scheme provides high efficiency. addition, does not take plane approximation can...

The inverse synthetic aperture radar (ISAR) imaging technique of a moving target with sparse sampling data has attracted wide attention due to its ability reduce the collection burden. However, traditional low-rank or 2D compressive sensing (CS)-based ISAR methods can handle random separable only. When specific condition cannot be satisfied, CS-based provide satisfactory results any more. To remedy this problem, in paper, we proposed joint and sparsity priors' constrained model for various...

The scattering center model represents the characteristics of radar targets at high frequencies by a set point scatterers. Such is useful in analysis, data compression and target recognition. We propose methodology to extract from wideband measurements sparsely distributed aspect angles. It exploits regular variation ID projective location slow coefficient stable centers adjacent aspects, greatly cuts down original amount compared other methods. extracted contains effective large angular...

An electronically large planar antenna with wideband illumination retrieves 3-D microwave image high resolution. Cross multi-input-multi-output (MIMO) topology is commonly used to produce the effective array at a reasonable cost and complexity. However, imaging algorithm for monostatic will cause distortion dispersion in near range applications. In this paper, an efficient precise by cross MIMO proposed. The integrals over transmitting receiving arrays are carried out wavenumber domain...

The standard compressed sensing (CS) theory reconstructs a signal by recovering sparse representation of the over pre-specified dictionary. For CS complex sinusoids, this dictionary is usually set to be DFT matrix corresponding uniform frequency grid. However, such setting can make conventional reconstruction methods degrade considerably, since component frequencies practical signals do not necessarily align with specified To deal problem, we apply linear approximation true unknown and...

Inverse synthetic aperture radar (ISAR) can form two‐dimensional (2D) electromagnetic images of a target, but it cannot provide the third dimensional information about target. Conventional 3D turntable ISAR imaging requires data collection over densely azimuth‐elevation samples, which needs large amount storage. In this study, an effective algorithm for model based on compressive sensing is proposed, exploits sparsity in image domain to achieve reconstruction by using limited number...

In this letter, we propose a fast reconstruction algorithm for 3-D turntable microwave imaging from sparse measurements. A conventional Fourier-transform-based method collects data over densely azimuth-elevation samples and needs large amount of storage long collection time. To reduce the cost acquisition, proposed exploits sparsity in image domain to achieve by utilizing For aim, signal model is first represented as tensor array, then, novel called 3-D-SL0 applied recover scattering...

A methodology to reconstruct the 3-D scattering center model from data with wide azimuthal aperture at a single elevation, such as those collected in turntable or circular synthetic radar configurations, is proposed this paper. The divided into overlapped subapertures, and 2-D centers are extracted each subaperture. These local rotated mapped ground plane target coordinate system, where they associated according their location amplitude consistency. Three-dimensional position of scatterer...

This paper presents a sequential algorithm for near-field multiple-input multiple-output synthetic aperture radar (MIMO-SAR) imaging. method can be decomposed into reconstruction MIMO array with the range migration technology and synthesis backprojection technology. Different to (RMA), does not adopt Fourier transform along scanning direction; therefore, it used MIMO-SAR systems arbitrary paths perform imaging during scanning. In addition, due its scheme, proposed is conducive parallel...

In near-range sparse multiple-input multiple-output (MIMO) array imaging, since grating lobes spread wide and overlap with each other, the zeros of transmitting receiving cannot cancel other out. As a result, there are residual in imaging results. This article proposes lobe suppression method based on zero migration multiapodization. The is equivalent to broadening array. Therefore, completely suppressed without increasing redundancy To realize migration, novel named generalized matched...

Multimedia has changed traditional white-blackboard lecture forever and reformed continually the forms presentation of materials. In this paper, we propose an online marking system. The realization system will help improve working efficiency papers, reduce potential cheating facilitate teacher storage analysis students' examination papers. is realized based on B/S structure (Browser/Server structure) which increase flexibility as long accesses to Internet. proposed system, some functions in...

Three-dimensional (3-D) radar imaging can provide additional information along elevation dimension about the target with respect to conventional 2-D imaging, but usually requires a huge amount of data collected over 3-D frequency-azimuth-elevation space, which motivates us perform by using sparsely sampled data. Traditional compressive sensing (CS) based methods sparse convert into long vector, and then complete recovery steps. This 1-D vectorized model, however, faces challenges high...

In this article, a grating and sidelobe suppression method for near-range multiple-input multiple-output (MIMO) array imaging is proposed, which achieves by reducing the sidelobes of transmitting receiving array. The first utilizes generalized matched filtering (GMF) to obtain results are separable along Then, an image domain phase compensation term derived eliminate spatially variant characteristic wavenumber spectrum, weighting scheme with adaptive range proposed reduce array,...

In this letter, a novel frequency-domain imaging method is proposed for single-input-multiple-output array, which avoids the interpolation. This transforms measurements into wavenumber domain compensation. The spectrum data at each frequency are proved to be Fourier transform of phase-modulated reflectivity function; therefore, subimage specific can produced by inverse fast and phase demodulation. final image obtained coherent accumulation all subimages. does not take plane wave...

The problem of reconstruction for a sparse multidimensional signal from multilinear system with separable dictionaries by limited amount measurements is addressed. For this aim, continuous Gaussian function used to approximate the l 0 norm tensor signal, and steepest ascent algorithm exploited optimise cost function. Compared conventional techniques, which usually convert into one-dimensional (1D) vector, proposed method can deal directly, thus it works fast saves memory usage. Finally,...

A continuous compressed sensing method for 2D radar imaging is adopted. Atomic norm minimisation used sparse signal recovery and the property of dual optimal solution utilised to generate a super‐resolution image. feasible first‐order algorithm based on alternating direction multipliers presented problem solving where primal can be obtained simultaneously. fast implementation also developed by exploiting low rank structure subproblem. Experimental results real data validate effectiveness...