Range-spread target detection in spherically invariant random vector clutter is addressed, and different detectors with constant false alarm rate (CFAR) property are devised by exploiting order statistics theory. Firstly, a known normalized covariance matrix, the generalized likelihood ratio test based on (OS-GLRT) utilizes some largest observations from range cells occupied most likely scatterers. OS-GLRT robust when estimated number of scatterers somewhat larger than actual, but degraded...

A novel radar target recognition method based on the deep one-dimensional residual-inception network is proposed for a high-resolution range profile (HRRP). The traditional methods shallow models can hardly extract complete information of targets HRRP from different angles. models, such as sparse autoencoder, have been adopted to solve this problem. However, these with huge amount parameters require more training samples guarantee generalization performance. To above-mentioned problem, model...

This article details the approach to large-scale production of cyclobutane 2 by continuous-flow [2 + 2] photocycloaddition maleic anhydride and ethylene, including (1) focused reaction optimization development a robust isolation protocol, (2) equipment design process safety, (3) results commissioning tests runs delivering target compound at throughputs exceeding 5 kg/day.

Minimum input power and maximum efficiency occur at a characteristic optimum slip value which can be calculated for any induction motor using methods described. Efficiency is shown to independent of output when variable voltage controller reduces the approximately as square root load torque maintain required during part operation. Saturation effects do not significantly change these results.

In order to improve the accuracy and robustness of radar target recognition under low SNR conditions, a novel high range resolution profile (HRRP) method based on feature pyramid fusion lightweight CNN is proposed in this paper. The combines multi-scale space theory with deep convolutional neural network. Because local connection characteristic kernel, extracted by mainly focus information target. To make full use both global HRRP, representation HRRP different Gaussian kernels introduced...

Adaptive detection of range-spread targets is considered in the presence subspace interference plus Gaussian clutter with unknown covariance matrix. The target signal and are supposed to lie two linearly independent subspaces deterministic but coordinates. Relying on two-step criteria, adaptive detectors based Gradient tests proposed, homogeneous partially interference, respectively. Both proposed exhibit theoretically constant false alarm rate property against matrix as well power level....

To address multi‐sensor real‐time track‐to‐track association problem of aircraft platforms in a complex environment, where sensor biases are time‐varied, targets distributed closely and different sensors report targets, an anti‐bias algorithm based on distance detection is proposed according to the statistical characteristics Gaussian random vectors. First, vector between homologous tracks derived its feature analysed; second, rough minimum average refined χ 2 distribution illustrated...

Adaptive detection of a sparsely distributed target is addressed without secondary data, in non-Gaussian clutter modelled as spherically invariant random vector. By utilising different estimators covariance matrix, an adaptive scheme proposed for target, based on the generalised likelihood ratio test and order statistics. Moreover, detector with recursive estimator holds approximate constant false alarm rate property respect to matrix structure statistics texture. The performance assessment...

In the clutter-dominated disturbance modeled as spherically invariant random vectors with same covariance matrix and possibly correlated texture components, we propose an estimator of matrix, which exploits all secondary data fully introduces a constraint trace. Moreover, its adaptive target detection application is investigated. For match between estimated clutter group size actual one, normalized matched filter (ANMF) new any number iterations theoretically ensures constant false alarm...

The work presented here addresses adaptive range-spread target detection in spherically invariant random vector (SIRV) clutter based on two-step generalized likelihood ratio test (GLRT) design procedure. Firstly, with known normalized covariance matrix (NCCM), a robust detector constant false alarm rate (CFAR) property is proposed, which cascades the GLRT for scatterer each range cell and two binary integrators. Subsequently, optimum parameters cascaded are obtained. Furthermore, by...

Adaptive detection of a range-spread target is addressed for possibly singular estimated covariance matrix, in non-Gaussian clutter modelled as spherically invariant random vector. Firstly, modified generalised likelihood ratio test with recursive estimator (MGLRT-RE) derived. To improve the adaptability and to reduce computational complexity MGLRT-RE, simplified MGLRT (SMGLRT) proposed proved be constant false alarm rate (CFAR) statistics texture theoretically. Based on secondary data,...

A high resolution range profile (HRRP) is a summation vector of the sub-echoes target scattering points acquired by wide-band radar. Generally, HRRPs obtained in non-cooperative complex electromagnetic environment are contaminated strong noise. Effective pre-processing HRRP data can greatly improve accuracy recognition. In this paper, denoising and reconstruction method for proposed based on Modified Sparse Auto-Encoder, which representative non-linear model. To better reconstruct HRRP,...

Abstract This study considers the problem of detecting range‐spread targets embedded in subspace interference plus Gaussian clutter with an unknown covariance matrix. The target and signals are modeled terms deterministic belonging to two known subspaces, respectively. Based on Gradient test criterion, adaptive detectors devised for rejecting homogeneous partially environments, Both proposed theoretically exhibit a desirable property constant false alarm rate respect matrix as well power...

This study deals with the problem of adaptively detecting range‐spread targets in Gaussian environment, by assuming a persymmetric structure covariance matrix. A detector based on two‐step generalised likelihood ratio test design scheme is devised to reduce secondary data requirement, which ensures constant false alarm rate property. Moreover, general closed‐form expressions probabilities and detection for proposed are derived, both cases deterministic fluctuating scatter models....

Server consolidation with virtualization is a popular method to address the issue of large amount power consumption inter-connected computers in data centers. The more are consolidated, energy saved. However, highly consolidating, wherein many servers consolidated into one physical computer, results performance decline. Especially, I/O severely decreased as reported. In this work, we focus on Docker, container-based virtualizing system, and OverlayFS. OverlayFS widely recognized for...

A modified variability index (MVI) CFAR detector is presented. The MVI a combination of the cell averaging (CA), greatest-of (GO), and trimmed mean (MTM). analytic expression its threshold multiplier factor TMTM also derived. Under SwerllingII assumption, evaluated compared with CA, OS, VI OSVI (order statistic VI) through Monte-Carlo simulation in various environments. In homogeneous background clutter edge environment, keeps good performance VI. multiple targets background, performs...