A robust compressive sensing based technique for reconstruction of sparse radar scenes

Cataloged from PDF version of article.Pulse-Doppler radar has been successfully applied to surveillance and tracking of both moving and stationary targets. For efficient processing of radar returns, delay–Doppler plane is discretized and FFT techniques are employed to compute matched filter output on this discrete grid. However, for targets whose delay–Doppler values do not coincide with the computation grid, the detection performance degrades considerably. Especially for detecting strong and closely spaced targets this causes miss detections and false alarms. This phenomena is known as the off-grid problem. Although compressive sensing based techniques provide sparse and high resolution results at sub-Nyquist sampling rates, straightforward application of these techniques is significantly more sensitive to the off-grid problem. Here a novel parameter perturbation based sparse reconstruction technique is proposed for robust delay– Doppler radar processing even under the off-grid case. Although the perturbation idea is general and can be implemented in association with other greedy techniques, presently it is used within an orthogonal matching pursuit (OMP) framework. In the proposed technique, the selected dictionary parameters are perturbed towards directions to decrease the orthogonal residual norm. The obtained results show that accurate and sparse reconstructions can be obtained for off-grid multi target cases. A new performance metric based on Kullback–Leibler Divergence (KLD) is proposed to better characterize the error between actual and reconstructed parameter spaces. Increased performance with lower reconstruction errors are obtained for all the tested performance criteria for the proposed technique compared to conventional OMP and 1 minimization techniques. © 2013 Elsevier Inc. All rights reserve

Sparse ground-penetrating radar imaging method for off-the-grid target problem

Cataloged from PDF version of article.Spatial sparsity of the target space in subsurface or through-the-wall imaging applications has been successfully used within the compressive-sensing framework to decrease the data acquisition load in practical systems, while also generating high-resolution images. The developed techniques in this area mainly discretize the continuous target space into grid points and generate a dictionary of model data that is used in image-reconstructing optimization problems. However, for targets that do not coincide with the computation grid, imaging performance degrades considerably. This phenomenon is known as the off-grid problem. This paper presents a novel sparse ground-penetrating radar imaging method that is robust for off-grid targets. The proposed technique is an iterative orthogonal matching pursuit-based method that uses gradient-based steepest ascent-type iterations to locate the off-grid target. Simulations show that robust results with much smaller reconstruction errors are obtained for multiple off-grid targets compared to standard sparse reconstruction techniques. (c) 2013 SPIE and IS&

Perturbed Orthogonal Matching Pursuit

Cataloged from PDF version of article.Compressive Sensing theory details how a sparsely represented signal in a known basis can be reconstructed with an underdetermined linear measurement model. However, in reality there is a mismatch between the assumed and the actual bases due to factors such as discretization of the parameter space defining basis components, sampling jitter in A/D conversion, and model errors. Due to this mismatch, a signal may not be sparse in the assumed basis, which causes significant performance degradation in sparse reconstruction algorithms. To eliminate the mismatch problem, this paper presents a novel perturbed orthogonal matching pursuit (POMP) algorithm that performs controlled perturbation of selected support vectors to decrease the orthogonal residual at each iteration. Based on detailed mathematical analysis, conditions for successful reconstruction are derived. Simulations show that robust results with much smaller reconstruction errors in the case of perturbed bases can be obtained as compared to standard sparse reconstruction techniques

Sparse delay-Doppler image reconstruction under off-grid problem

Pulse-Doppler radar has been successfully applied to surveillance and tracking of both moving and stationary targets. For efficient processing of radar returns, delay-Doppler plane is discretized and FFT techniques are employed to compute matched filter output on this discrete grid. However, for targets whose delay-Doppler values do not coincide with the computation grid, the detection performance degrades considerably. Especially for detecting strong and closely spaced targets this causes miss detections and false alarms. Although compressive sensing based techniques provide sparse and high resolution results at sub-Nyquist sampling rates, straightforward application of these techniques is significantly more sensitive to the off-grid problem. Here a novel and OMP based sparse reconstruction technique with parameter perturbation, named as PPOMP, is proposed for robust delay-Doppler radar processing even under the off-grid case. In the proposed technique, the selected dictionary parameters are perturbed towards directions to decrease the orthogonal residual norm. A new performance metric based on Kull-back-Leibler Divergence (KLD) is proposed to better characterize the error between actual and reconstructed parameter spaces. © 2014 IEEE

A recursive way for sparse reconstruction of parametric spaces

A novel recursive framework for sparse reconstruction of continuous parameter spaces is proposed by adaptive partitioning and discretization of the parameter space together with expectation maximization type iterations. Any sparse solver or reconstruction technique can be used within the proposed recursive framework. Experimental results show that proposed technique improves the parameter estimation performance of classical sparse solvers while achieving Cramér-Rao lower bound on the tested frequency estimation problem. © 2014 IEEE

Stimulated emission and time-resolved photoluminescence in rf-sputtered ZnO thin films

Stimulated emission (SE) was measured from ZnOthin filmsgrown on c-plane sapphire by rf sputtering. Free exciton transitions were clearly observed at 10 K in the photoluminescence(PL), transmission, and reflection spectra of the sample annealed at 950 °C. SE resulting from both exciton-exciton scattering and electron hole plasma formation was observed in the annealed samples at moderate excitation energy densities. The SE threshold energy density decreased with increasing annealing temperature up to ∼950 °C. The observation of low threshold exciton-exciton scattering-induced SE showed that excitonic laser action could be obtained in rf-sputtered ZnOthin films. At excitation densities below the SE threshold, time-resolvedPL revealed very fast recombination times of ∼74 ps at room temperature, and no significant change at 85 K. The decay time for the SE-induced PL was below the system resolution of \u3c45 ps

Excitonic fine structure and recombination dynamics in single-crystalline ZnO

The optical properties of a high quality bulk ZnO, thermally post treated in a forming gas environment are investigated by temperature dependent continuous wave and time-resolved photoluminescence (PL) measurements. Several bound and free exciton transitions along with their first excited states have been observed at low temperatures, with the main neutral-donor-bound exciton peak at 3.3605 eV having a linewidth of 0.7 meV and dominating the PL spectrum at 10 K. This bound exciton transition was visible only below 150 K, whereas the A-free exciton transition at 3.3771 eV persisted up to room temperature. A-free exciton binding energy of 60 meV is obtained from the position of the excited states of the free excitons. Additional intrinsic and extrinsic fine structures such as polariton, two-electron satellites, donor-acceptor pair transitions, and longitudinal optical-phonon replicas have also been observed and investigated in detail. Time-resolved PL measurements at room temperature reveal a biexponential decay behavior with typical decay constants of similar to170 and similar to864 ps for the as-grown sample. Thermal treatment is observed to increase the carrier lifetimes when performed in a forming gas environment

Antimicrobial and antioxidant properties of methanol extract, fractions and compounds from the stem bark of Entada abyssinica Stend ex A. Satabie

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to evaluate the antimicrobial and antioxidant activities of the methanol extract, fractions and isolated compounds from <it>Entada abyssinica </it>stem bark, plant used traditionally against gastrointestinal infections.</p> <p>Methods</p> <p>The methanol extract of <it>E. abyssinica </it>stem bark was pre-dissolved in a mixture of methanol and water, and then partitioned between <it>n</it>-hexane, ethyl acetate and <it>n</it>-butanol. The ethyl acetate portion was fractionated by column chromatography and the structures of isolated compounds elucidated by analysis of spectroscopic data and comparison with literature data. Antimicrobial activity was assayed by broth microdilution techniques on bacteria and yeasts. The antioxidant activity was determined by DPPH radical scavenging method.</p> <p>Results</p> <p>Four known compounds [(5<it>S</it>,6<it>R</it>,8a<it>R</it>)-5-(carboxymethyl)-3,4,4a,5,6,7,8,8a-octahydro-5,6,8a-trimethylnaphthalenecarboxylic acid (<b>1</b>), methyl 3,4,5-trihydroxybenzoate (<b>2</b>), benzene-1,2,3-triol (<b>3</b>) and 2,3-dihydroxypropyltriacontanoate (<b>4</b>)] were isolated. Compared to the methanol extract, fractionation increased the antibacterial activities of the <it>n</it>-hexane and ethyl acetate fractions, while the antifungal activities increased in ethyl acetate, <it>n</it>-butanol and aqueous residue fractions. The isolated compounds were generally more active on bacteria (9.7 to 156.2 μg/ml) than yeasts (78.1 to 312.5 μg/ml). Apart from compound <b>1</b>, the three others displayed DPPH^·scavenging activity (RSa), with RSa₅₀values of 1.45 and 1.60 μg/ml.</p> <p>Conclusion</p> <p>The results obtained from this study support the ethnomedicinal use of <it>E. abyssinica </it>in the treatment of gastrointestinal infections and the isolated compounds could be useful in the standardisation of antimicrobial phytomedicine from this plant.</p

Broadband luminescence in defect-engineered electrochemically produced porous Si/ZnO nanostructures

The fabrication, by an all electrochemical process, of porous Si/ZnO nanostructures with engineered structural defects, leading to strong and broadband deep level emission from ZnO, is presented. Such nanostructures are fabricated by a combination of metal-assisted chemical etching of Si and direct current electrodeposition of ZnO. It makes the whole fabrication process low-cost, compatible with Complementary Metal-Oxide Semiconductor technology, scalable and easily industrialised. The photoluminescence spectra of the porous Si/ZnO nanostructures reveal a correlation between the lineshape, as well as the strength of the emission, with the morphology of the underlying porous Si, that control the induced defects in the ZnO. Appropriate fabrication conditions of the porous Si lead to exceptionally bright Gaussian-type emission that covers almost the entire visible spectrum, indicating that porous Si/ZnO nanostructures could be a cornerstone material towards white-light-emitting devices

Markov Chain Monte Carlo and the Application to Geodetic Time Series Analysis

The time evolution of geophysical phenomena can be characterised by stochastic time series. The stochastic nature of the signal stems from the geophysical phenomena involved and any noise, which may be due to, e.g., un-modelled effects or measurement errors. Until the 1990's, it was usually assumed that white noise could fully characterise this noise. However, this was demonstrated to be not the case and it was proven that this assumption leads to underestimated uncertainties of the geophysical parameters inferred from the geodetic time series. Therefore, in order to fully quantify all the uncertainties as robustly as possible, it is imperative to estimate not only the deterministic but also the stochastic parameters of the time series. In this regard, the Markov Chain Monte Carlo (MCMC) method can provide a sample of the distribution function of all parameters, including those regarding the noise, e.g., spectral index and amplitudes. After presenting the MCMC method and its implementation in our MCMC software we apply it to synthetic and real time series and perform a cross-evaluation using Maximum Likelihood Estimation (MLE) as implemented in the CATS software. Several examples as to how the MCMC method performs as a parameter estimation method for geodetic time series are given in this chapter. These include the applications to GPS position time series, superconducting gravity time series and monthly mean sea level (MSL) records, which all show very different stochastic properties. The impact of the estimated parameter uncertainties on sub-sequentially derived products is briefly demonstrated for the case of plate motion models. Finally, the MCMC results for weekly downsampled versions of the benchmark synthetic GNSS time series as provided in Chapter 2 are presented separately in an appendix