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There has been an increasing interest in addressing the issue of high-resolution inverse synthetic aperture radar (ISAR) imaging from sparse sampling data. Traditional compressed sensing (CS) and matrix completion (MC) methods are based on sparse and low-rank constraints, respectively, which do not make full use of the structure of ISAR data. In this article, a sparse ISAR imaging algorithm using a structured low-rank approach is proposed for enhanced imaging performance. Based on the observation that the structured Hankel matrix has better low-rank property, the proposed algorithm can outperform the group of conventional MC methods in terms of accuracy to data quality and quantity. Rather than using the traditional singular value decomposition (SVD) solution of nuclear norm minimization, the proposed algorithm restates the nuclear norm via an equivalent reformulation that the structured Hankel matrix can be decomposed into two disjointed parts to avoid the dimensional expansion of the Hankel matrix. Meanwhile, the alternative direction method of multipliers (ADMMs) is applied to effectively reduce the computational complexity. Finally, the effectiveness of the proposed algorithm is further validated using the experiments on simulated and measured data.

High speed, high maneuverability, and weak space-moving targets (SMTs) are major threats for space-borne radar (SBR) systems. First, the severe range migration (RM) and Doppler extension are induced by complex relative motion between the radar platform and non-cooperative moving targets, making moving target detection (MTD), and parameter estimation particularly difficult. Apart from this challenge, Doppler ambiguity and Doppler aliasing arise from the limited pulse repetition frequency (PRF) of a SBR system to ensure an adequate coverage rate, which may make the existing MTD algorithms deteriorate dramatically. To address these issues, we focus on the detection of high speed and high maneuverability targets based on the modified keystone transform matched filtering (MKTMF), whose Doppler frequency exceeds PRF as well as spans multiple PRFs. The proposed method is suitable for the weak MTD under a low signal-to-noise ratio (SNR) case since the nonlinear operation is not involved. Finally, some numerical results and real data results are provided to validate the superiority of the proposed method.

Eucommia ulmoides, a precious Chinese herbal medicine, lack of studies on the detection of its pesticide residues. A simple sample preparation based on the solid-phase extraction (SPE) procedure was established for the analysis of 16 kinds of pesticides in Eucommia ulmoides by gas chromatography mass spectrometry (GC-MS) with selective ion monitoring mode. Here, the type and volume of extraction solvent and eluent, the kinds of sorbents in SPE Cleanert column, were optimized. Under the optimal conditions, a good linear relationship was obtained in the range of 0.005 to 5.0 mg/L with correlation coefficient (r) higher than 0.9990, and the average recoveries (AR) of 16 pesticides ranged from 79.6 to 109.2% at the spiking levels of 0.01, 0.1, and 0.5 mg/kg. The relative standard deviations (RSD) were 0.78 to 9.56% (n = 6). The results show that the established method can not only fully meet the analytical requirements of various pesticides in Eucommia ulmoides, but also have the potential to be applied in the detection of pesticide residues in others Chinese herbal medicine.