Detection Of Frequency Modulated Signals Research Articles

The influence of magnetic film anisotropy on the frequency-modulated signal detection

We studied the possibility of using a magnetostriction converter for detecting a microwave signal with frequency modulation. The magnetization vector and elastic displacement oscillations in a normally magnetized ferrite film with crystallographic anisotropy are considered. We analyzed the effect of crystallographic cell orientation on the nature of the magnetization dynamics and elastic displacement oscillations, the establishment of various oscillation modes, and the detection process.

Edge filter enhanced self-mixing interferometry.

Self-mixing interferometry (SMI) represents a simple, robust, and self-aligned technique for metrology applications. Still, its applicability on diffuse targets is limited to distances up to few meters. We present an enhanced approach based on the detection of the frequency-modulated (FM) self-mixing signal. The FM signal detection is achieved using an acetylene edge filter that maps laser frequency variations into intensity variations as the laser wavelength is tuned to the edge of the steep absorption profile. An experimental comparison between the enhanced and the conventional SMI approach is presented. The new approach yields to about two orders of magnitude larger signal-to-noise ratio and extends the applicability of SMI into new fields allowing longer detection ranges and lower backscattering signals.

Rate change detection of frequency modulated signals: developmental trends

The aim of this study was to examine developmental trends in rate change detection of auditory rhythmic signals (repetitive sinusoidally frequency modulated tones). Two groups of children (9-10 years old and 11-12 years old) and one group of young adults performed a rate change detection (RCD) task using three types of stimuli. The rate of stimulus modulation was either constant (CR), raised by 1 Hz in the middle of the stimulus (RR1) or raised by 2 Hz in the middle of the stimulus (RR2). Performance on the RCD task significantly improved with age. Also, the different stimuli showed different developmental trajectories. When the RR2 stimulus was used, results showed adult-like performance by the age of 10 years but when the RR1 stimulus was used performance continued to improve beyond 12 years of age. Rate change detection of repetitive sinusoidally frequency modulated tones show protracted development beyond the age of 12 years. Given evidence for abnormal processing of auditory rhythmic signals in neurodevelopmental conditions, such as dyslexia, the present methodology might help delineate the nature of these conditions.

Nonparametric detection of frequency modulated signals using fractional Fourier transform

A detection scheme for unknown nonlinear frequency modulated signals in white Gaussian noise is developed using the fractional Fourier transform and two-dimensional order-statistic filter. The simulation experiment and comparison with other methods available are shown, and the effectiveness of the proposed method is reported.

Nonparametric Detection of FM Signals Using Time-Frequency Ridge Energy

In many practical applications, signals to be detected are unknown nonlinear frequency modulated (FM) and are corrupted by strong noise. The phase histories of signals are assumed to be unknown smooth functions of time and these functions are poorly modeled or unmodeled by a small number of parameters. Thus, the conventional parametric-based detection methods are invalid in these cases. This paper proposes a nonparametric detection method using the ridge energy of observations. The detection process consists of three steps, TF ridge detection, ridge energy extraction, and decision. First, the directionally smoothed-pseudo-Wigner-Ville distribution (DSPWVD) is introduced to highlight the instantaneous frequency (IF) points along a special direction on the IF curve of a signal from noise. Further, an angular maximal distribution (AMAD) is constructed from a set of DSPWVDs to highlight the entire IF curve. As a result, the TF ridge of an observation can be estimated well from its AMAD by the maxima position detector. Second, the ridge energy, the total energy along the TF ridge on the pseudo-Wigner-Ville distribution (PWVD), is extracted. A noisy signal has larger ridge energy than a pure noise does, with a large probability, because pure noise energy is randomly distributed throughout the TF plane while the signal energy in a noisy signal is concentrated along the estimated TF ridge. Third, the ridge energy of an observation is used as the test statistic to decide whether or not a signal of interest is present in the observation, where the decision threshold is determined by a large number of Monte Carlo simulations using pure noise. Finally, the simulation experiments to two test signals are made to verify the effectiveness of the proposed method.