This correspondence investigates the uncertainty principles under linear canonical transform (LCT). First, a lower bound on product of signal representations in two LCT domains for complex signals is derived, which can be achieved by chirp with Gaussian envelope. Then, tighter real proposed Sharma and Joshi also proven to hold arbitrary parameters based properties moments LCT. The principle fractional Fourier special case results.

To reduce the amount of measurements, compressed sensing (CS) has been introduced to synthetic aperture radar (SAR). In this letter, a novel CS-SAR imaging algorithm is proposed, which consists 2-D undersampling, range reconstruction, range-azimuth decoupling, and azimuth reconstruction. proposed algorithm, profile reconstructed in fractional Fourier domain, decoupling case undersampling realized by using reference function multiplication chirp-z transform. Comparisons with existing...

Energy efficiency is regards as an important problem in energy-limited wireless medical sensor networks owing to the energy shortage. On other hand, full-duplex considered promising technology for future consumer that provides higher transmission rate. In this paper, we discussed a secure energy-efficient beamformer design was impaired by channel state information (CSI) two-way multi-input multi-output (MIMO) smart healthcare, enabling simultaneous data and power communication. We consider...

As an important signature associated with human movement, micro-Doppler (m-D) can provide the basis for activity classification. In particular, m-D signal of limbs a highly distinctive feature reduced which be used to detect people who are carrying weapon or injured. Fully exploiting elaborate features that correspond motion improve classification accuracy such activities. Therefore, it is significant separate limb-swing from torso and process them separately. this paper, novel separation...

We report the design and analysis of a non-blocking microring resonator-based optical switched router, which can be used as switch node to construct large photonic routing network on chips. The proposed router has sixteen microrings, fourteen crossings four 90° waveguide bends, could tuned through thermo-optic (TO) or electro-optic (EO) effect. Compared with previously described 5 × switching our comprises fewer resonators (MRRs), results in more compact design, higher speed, lower loss...

In this paper we propose a new CFAR detector based on ordered data variability. The proposed detector, designated as ODV-CFAR, uses the variability index statistics to select dynamically whole reference cells, smaller ranked cells or larger estimate unknown background level. performance of is evaluated and compared with those ACCA-ODV trimmed-mean (TM) detectors in various environments. results show that ODV-CFAR acts like CA-CFAR homogeneous performs robustly non-homogeneous environments

Greedy pursuit algorithms are widely used for sparse signal recovery from a compressed measurement system due to their low computational complexity. Combining different greedy can improve the performance. In this paper an improved orthogonal matching (OMP) is proposed, in which randomly enhanced adaptive subspace (REASP) refine estimated support set of OMP at each iteration and hence boost performance OMP. The simulation results verify effectiveness proposed algorithm show that it has good...

Compressed sensing has important applications in many areas and there are approaches for sparse signals recovery. Sparse Bayesian learning is a popular recovery method. Recently an inverse-free (IFSBL) been proposed, which low computational complexity without matrix inverse. In practice, the non-zero elements of signal tend to have certain structural characteristics block algorithms required. The main work this paper extend IFSBL algorithm case propose algorithm, utilizes cluster-structured...

Compressed sensing (CS) has attracted considerable attention in signal processing because of its advantage recovering sparse signals with lower sampling rates than the Nyquist rates. Greedy pursuit algorithms such as orthogonal matching (OMP) are well-known recovery CS. In this study, authors study a modified OMP proposed by Schnass et al., which uses special dictionary to identify support while maintaining same computational complexity. The performance guarantee is analysed framework mutual...

Abstract Passive radar (PR) systems need to detect the presence of a target response, which is many orders magnitude weaker than clutter (direct signal and multipath). Indeed, cancellation key stage within PR processing scheme. One most effective techniques in this field using CLEAN approach. In paper, batch-based technique based on GMP FFT has been proposed, can speed up computational have better gain. Furthermore, segmenting operation be applied obtained over long time. It helpful enhance...

Compressed sensing can exactly reconstruct sparse or compressible signals. In practice, many signals have block structures. To recover signals, a backtracking-based matching pursuit algorithm is proposed, which chooses possible correct atoms by using processing and deletes unreliable backtracking mechanism. The proposed doesn't require the prior knowledge about structure of signal. Experiments demonstrate that outperforms some other greedy recovery methods.

The Gaussian mixture model (GMM) is prone to large-scale misdetection in the static case where background and foreground have similar colours. This study presents an improved GMM method solve this problem. First, principal component analysis used transform high-dimensional space into low-dimensional one with three colour channels, which aims reduce runtime. Then, images are processed by obtain areas. At same time, mean difference of pixel features red, green blue hue, saturation value (HSV)...

A contradiction between wide swath and high spatial resolution exists in synthetic aperture radar (SAR) imaging processing. Displaced phase centers multiple azimuth beams (DPC-MAB) system can make a tradeoff them, but it arises non-uniform sampling the direction. In this paper, novel reconstruction method associated with fractional Fourier transform is proposed, which has better performance compared traditional one. Moreover, reconstruct under sampled signal successfully while fails....

Unsupervised band selection (BS) methods have attracted much attention in hyperspectral imagery (HSI), which can select informative bands to solve the problems of information redundancy and high computational complexity. In this paper, we propose a KL-weighted graph sparse self-representation (SSR) method for unsupervised BS, dissimilarity measured via KL divergence is integrated into superpixel-based SSR model by weighting representation coefficient matrix. An alternating optimization...

Passive radar (PR) systems use the existing transmitters of opportunity in environment to perform tasks such as detection, tracking, and imaging. The classical cross‐correlation based methods obtain range‐Doppler map have problems high sidelobe limited resolution due influence signal bandwidth. In this paper, we propose a novel processing method on compressed sensing (CS), which performs sparse reconstruction range Doppler dimensions achieve reduces without excessive computational burden....

Compressive sensing (CS) is a novel signal sampling theory and it can recover sparse or compressive signals with lower rates than their Nyquist rates. Greedy pursuit algorithms are important recovery in CS. In this paper, we study the performance of subspace (SP) greedy algorithm propose modified SP termed as regularized multipath (RMSP), which divides test set into several subsets each iteration by means regularization, gets candidates support subsequent processing, then selects one...