We define a discrete version of the angular Fourier transform and present properties that show it to be rotation in time-frequency space, this new is generalization DFT. Efficient algorithms for its computation can then based on FFT eigenstructure

A vibration estimation method for synthetic aperture radar (SAR) is presented based on a novel application of the discrete fractional Fourier transform (DFRFT). Small vibrations ground targets introduce phase modulation in SAR returned signals. With standard preprocessing signals, followed by DFRFT, time-varying accelerations, frequencies, and displacements associated with vibrating objects can be extracted successively estimating quasi-instantaneous chirp rate phase-modulated signal each...

Previously investigated multicomponent AM-FM demodulation techniques either assume that the individual component signals are spectrally isolated from each other or components can be by linear time-invariant filtering and, consequently, break down in case where overlap when one of is stronger than other. In this paper, we present a nonlinear algorithm for separation and discrete-time signals. Our approach divides problem into two independent tasks: algebraic based on periodicity assumptions...

Existing versions of the discrete fractional Fourier transform (DFRFT) are based on (DFT). These approaches need a full basis DFT eigenvectors that serve as Hermite-Gauss functions. In this letter, we define DFRFT centered version (CDFRFT) using derived from Gru/spl uml/nbaum tridiagonal commutor excellent approximations to We develop fast and efficient way compute multiangle CDFRFT for set angles FFT algorithm. then show associated chirp-frequency representation is useful analysis tool...

Automatic modulation recognition is a topic of interest in many fields including signal surveillance, multi-user detection and radio frequency spectrum monitoring. In this paper, we present an algorithm for different types continuous phase signals that uses combination features extracted through cyclic spectral analysis ICA-SVM hybrid system. Simulation results demonstrate the ability to correctly identify over wide range SNR scenarios. The effects pulse shaping partial response waveforms...

Target vibrations introduce nonstationary phase modulation, which is termed the micro-Doppler effect, into returned synthetic aperture radar (SAR) signals. This causes artifacts, or ghost targets, appear near vibrating targets in reconstructed SAR images. Recently, a vibration estimation method based on discrete fractional Fourier transform (DFrFT) has been developed. capable of estimating instantaneous accelerations and frequencies. In this paper, deghosting for images proposed. For...

Existing approaches to furnishing a basis of eigenvectors for the discrete Fourier transform (DFT) are based upon defining tridiagonal operators that commute with DFT. In this paper, motivated by ideas from quantum mechanics in finite dimensions, we define symmetric matrix commutes centered DFT, thereby We show these limit converge Gauss-Hermite (G-H) functions and eigenvalue spectrum commutor provides very good approximation continuous G-H differential operator.

The continuous-time angular Fourier transformation (AFT) represents a rotation in continuous time-frequency space and also serves as an orthonormal signal representation for chirp signals. We present discrete version of the AFT (DRFT) that some properties transform support its interpretation rotation. is generalization DFT. eigenvalue structure DFT then exploited to develop efficient algorithm computation this transform.

Synthetic-aperture radar (SAR) can be used to remotely estimate ground target vibrations by exploiting the Doppler in returned signals. Recent studies suggest that time-frequency signal-processing tools retrieve vibration signature from SAR A estimation method based on fractional Fourier transform (FRFT) was reported earlier and it tested simulated data. In this paper, a first-time demonstration of FRFT-based is using real data collected Lynx (K <sub...

In synthetic-aperture-radar (SAR) imaging, large volumes of data are normally processed and transported over airborne or space-based platforms. The development fast robust algorithms for processing analysis this type is therefore great importance. It has been demonstrated recently that a Markov-random-field (MRF) model, based on the statistical properties coherent provides an ideal framework to describe spatial correlation within SAR imagery in presence speckle noise, which present all...

The spectrogram is a useful tool for the time-frequency analysis of non stationary signals. This tool, however, based upon multicomponent sinusoidal model over signal frame and not suitable when, example, frequency content chirping. Recently, centered version discrete fractional Fourier transform was shown to possess capability concentrate linear chirp in few coefficients. We present modified which incorporates its multiangle instead decomposes into multiple simulation results that study...

An algorithm for the separation and energy-based demodulation of two-component mixtures AM-FM signals is presented. The proposed based on generating differential or difference equation mixture signal nonlinear energy operators.

The Teager-Kaiser energy operator and the related separation algorithm (ESA) find numerous applications in various problems to monocomponent AM-FM demodulation. This energy-operator-based approach, however, applies only signals with narrowband frequency content, i.e., information bandwidth deviation about carrier are small relative frequency. For large deviation, modulation indices, this approximation fails, ESA incurs frequency/amplitude demodulation errors. In letter, we develop a...

Existing image demodulation approaches based on the two-dimensional (2D) multicomponent AM-FM model assume narrowband components that can be demodulated using energy operators, Hilbert transforms, or monogenic approaches. However, if FM are wideband, then these incur significant errors. Recent work by authors extended wideband in one dimension to accommodate large conversion factors multirate frequency transformations. In this paper, we extend transformations technique developed for...

Automatic modulation recognition is a topic of interest in many fields including signal surveillance, multi-user detection and radio frequency spectrum monitoring. A major weakness conventional algorithms their reliance on high SNR environments favorable statistics. In this paper an algorithm developed using elements cyclo-spectral analysis, ICA SVM to distinguish between different types. By first estimating the cyclic then analyzing statistical features machine learning techniques,...

Recent reports on the effects of vibrating targets synthetic-aperture radar (SAR) imagery and potential SAR to extract non-stationary signatures have drawn significant interest from remote-sensing community. returned signals are superposition transmitted pulses modulated by both static non-static in amplitude phase. More precisely, vibration a target causes small sinusoid-like frequency modulation along synthetic aperture (slow time), whereby phase deviation is proportional displacement...

As an extension of the conventional Fourier transform and as a time-frequency signal analysis tool, fractional transforms (FRFT) are suitable for dealing with various types non-stationary signals. Computation discrete (DFRFT) its chirp concentration properties both dependent on basis DFT eigenvectors used in computation. Several DFT-eigenvector bases have been proposed computation transform, there is no common framework comparing them. In this paper, we compare several different approaches...

The conventional spectrogram is a commonly employed, time-frequency tool for stationary and sinusoidal signal analysis. However, it unsuitable general non-stationary analysis [1]. In recent work [2], slanted that based on the discrete Fractional Fourier transform was proposed multicomponent chirp analysis, when components are harmonically related. this paper, we extend framework to non-harmonic using both piece-wise linear polynomial fitted methods. Simulation results synthetic chirps,...

Hankel rank reduction (HRR) is a method that, by prearranging the data in matrix and performing via singular value decomposition, suppresses noise of time-history vector comprised superposition finite number sinusoids. In this letter, HRR studied for clutter suppression synthetic aperture radar (SAR)-based vibrometry. Specifically, three different applications are presented. First, resembling SAR slow-time signal model, utilized separating chirp immersed sinusoidal clutter. Second, using...

CPM signals find widespread use in wireless communication systems due to their constant modulus property and spectral efficiency. Frequency discrimination based demodulation approaches require efficient instantaneous frequency tracking. Prior attempts at tracking via adaptive linear prediction have invoked the of fixed step-size LMS algorithm. In this paper, we present an algorithm that combines aspects prediction, transformations on multirate operations for using both forgetting factor RLS...

ICA based blind source separation methods suffer from inherent scaling and permutation ambiguities , which would cause problems in a DS-CDMA multiuser detection MAI mitigation scenario. Recently incorporating prior information about the desired user's code were proposed as an add-on to subspace MMSE detector. In this paper, we propose Q-R decomposition technique initialize algorithm order remove ambiguity well avoid explicit computations. It is shown via simulations that more robust case of...

The basis functions of the continuous fractional Fourier transform (FRFT) are linear chirp signals that suitable for time-frequency analysis with chirping content. Efforts to develop a discrete computable version (DFRFT) have focussed on furnishing an orthogonal set eigenvectors DFT serve as versions Gauss-Hermite functions. Analysis DFRFT obtained from Grunbaum's tridiagonal commuter and kernel associated it reveals presence both amplitude frequency modulation in contrast just seen case....

The non-linear, second-order, Teager-Kaiser energy operator (TKEO) finds applications in numerous areas such as speech processing, image communications, biomedical problems, and abrupt event detection. In quantum mechanics, the Hamiltonian is considered whose eigenvalue scalar energy. this work, we provide a matrix framework for several of its generalizations, interpreting eigenvalues presented matrices square-root TKEO or generalization.