Instantaneous Frequency Identification Using Adaptive Linear Chirplet Transform and Matching Pursuit

Time-frequency Perspectives: the “chirplet” Transform

We have developed a new expansion’ we call the “chirplet transform”. It has been successfully applied to a wide variety of signal processing applications including radar[l] and image processing. There has been a recent debate as to the relative merits of an affine-in-time (wavelet) transform and the classical Short Time Fourier Transform (STFT), for the analysis of non-stationary phenomena. Chi...

General Linear Chirplet Transform and Radar Target Classification

In this paper, we design an attractivealgorithm aiming to classify moving targets includinghuman, animal, vehicle and drone, at groundsurveillance radar systems. The non-stationary reflectedsignal of the targets is represented with a novelmathematical framework based on behavior of thesignal components in reality. We further propose usingthe generalized linear chirp transform for the analysisst...

Adaptive "chirplet" transform: an adaptive generalization of the wavelet transform

Manoeuvring target detection in over-the-horizon radar using adaptive clutter rejection and adaptive chirplet transform

In over-the-horizon radar (OTHR) systems, the signal-to-clutter ratio (SCR) used for moving target detection is very low. For slowly moving targets such as ships, the SCR is typically from 250 dB to 260 dB and their Doppler frequencies are close to that of the clutter. For manoeuvring targets, such as aircraft and missiles, the Doppler frequencies are time-varying when a long integration time i...

Instantaneous frequency estimation using discrete evolutionary transform for jammer excision

In this paper, we propose a method –based on the discrete evolutionary transform (DET)– to estimate the instantaneous frequency of a signal embedded in noise or noise-like signals. The DET provides a representation for non-stationary signals and a time-frequency kernel that permit us to obtain the time-dependent spectrum of the signal. We will show the instantaneous phase and the corresponding ...