Signal detection algorithms for interferometricsensors with harmonic phase modulation:evaluation of additive noise effects

2021 ◽  
Author(s):  
Leonid Liokumovich ◽  
Konstantin Muravyov ◽  
Aleksandr Sochava ◽  
Philipp Skliarov ◽  
Nikolai Ushakov
Keyword(s):  
Signal Detection ◽  
Additive Noise ◽  
Noise Effects ◽  
Detection Algorithms ◽  
Harmonic Phase

Signal detection algorithms for interferometric sensors with harmonic phase modulation: miscalibration of modulation parameters

2018 ◽  
Vol 57 (25) ◽  
pp. 7127 ◽  
Author(s):  
Leonid Liokumovich ◽  
Konstantin Muravyov ◽  
Philipp Skliarov ◽  
Nikolai Ushakov
Keyword(s):  
Signal Detection ◽  
Phase Modulation ◽  
Detection Algorithms ◽  
Harmonic Phase ◽  
Interferometric Sensors

scholarly journals Signal detection algorithms for interferometric sensors with harmonic phase modulation: distortion analysis and suppression

2017 ◽  
Vol 56 (28) ◽  
pp. 7960 ◽  
Author(s):  
Leonid Liokumovich ◽  
Andrei Medvedev ◽  
Konstantin Muravyov ◽  
Philipp Skliarov ◽  
Nikolai Ushakov
Keyword(s):  
Signal Detection ◽  
Phase Modulation ◽  
Detection Algorithms ◽  
Harmonic Phase ◽  
Interferometric Sensors ◽  
Distortion Analysis

scholarly journals GPS Signal Detection under Multiplicative and Additive Noise

2012 ◽  
Vol 66 (4) ◽  
pp. 479-500 ◽  
Author(s):  
P. Huang ◽  
Y. Pi ◽  
I. Progri
Keyword(s):  
Signal Detection ◽  
Urban Areas ◽  
Multiplicative Noise ◽  
Additive Noise ◽  
Power Level ◽  
Signal Propagation ◽  
Signal Acquisition ◽  
Detection Scheme ◽  
Additive And Multiplicative Noise ◽  
Gps Signal Acquisition

In some Global Positioning System (GPS) signal propagation environments, especially in the ionosphere and urban areas with heavy multipath, GPS signal encounters not only additive noise but also multiplicative noise. In this paper we compare and contrast the conventional GPS signal acquisition method which focuses on handling GPS signal acquisition with additive noise, with the enhanced GPS signal processing under multiplicative noise by proposing an extension of the GPS detection mechanism, to include the GPS detection model that explains detection of the GPS signal under additive and multiplicative noise. For this purpose, a novel GPS signal detection scheme based on high order cyclostationarity is proposed. The principle is introduced, the GPS signal detection structure is described, the ambiguity of initial PseudoRandom Noise (PRN) code phase and Doppler shift of GPS signal is analysed. From the simulation results, the received GPS signal at low power level, which is degraded by additive and multiplicative noise, can be detected under the condition that the received block of GPS data length is at least 1·6 ms and sampling frequency is at least 5 MHz.

Study of BLAST Signal Detection Algorithm in LTE System

2013 ◽  
Vol 756-759 ◽  
pp. 3183-3188
Author(s):  
Tao Lei ◽  
Deng Ping He ◽  
Fang Tang Chen
Keyword(s):  
Signal Detection ◽  
High Speed ◽  
Data Communication ◽  
Detection Algorithm ◽  
Detection Performance ◽  
Detection Algorithms ◽  
High Speed Data ◽  
Simulation Results ◽  
Better Than

BLAST can achieve high speed data communication. Its signal detection directly affects performance of BLAST receiver. This paper introduced several signal detection algorithmsZF algorithm, MMSE algorithm, ZF-SIC algorithm and MMSE-SIC algorithm. The simulation results show that the traditional ZF algorithm has the worst performance, the traditional MMSE algorithm and the ZF-SIC algorithm is similar, but with the increase of the SNR, the performance of ZF-SIC algorithm is better than MMSE algorithm. MMSE-SIC algorithm has the best detection performance in these detection algorithms.

Noise Effects in Perceptual Models

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 44-44
Author(s):  
T D Wickens ◽  
L A Olzak
Keyword(s):  
Visual Perception ◽  
Spatial Frequency ◽  
Signal Detection ◽  
Intrinsic Variability ◽  
Noise Sources ◽  
Third Order ◽  
Noise Effects ◽  
Combination Process ◽  
Delta Sigma ◽  
Visual Phenomena

In studies of visual perception performance is often measured by statistics that are ratios of a perceptual magnitude to its intrinsic variability, most commonly the signal-detection measure d'=delta sigma. Many models for visual phenomena treat the variability sigma as a constant and describe performance exclusively by delta. However, in models for the combination of stimulus attributes, the combination process affects both terms, and an observed d' reflects both delta and sigma. For example, we have shown that masking and configural effects with sinusoidal plaids can be at least partially interpreted as noise effects. We have developed methods to analyse these effects. Through a series of concurrent-response experiments using grating stimuli, some reported at earlier ECVP meetings, we have measured the form and magnitude of the noise sources. Our analysis allows us to model the way that primitive Fourier components (spatial frequency by orientation) are integrated to form second-order or third-order combinations (eg spatial frequency pooled over orientation).

THE EFFECT OF SMOOTHING ON THE DYNAMICAL BEHAVIOR OF NOISY CHAOTIC SIGNALS

1993 ◽  
Vol 03 (06) ◽  
pp. 1591-1600
Author(s):  
M. F. H. TARROJA ◽  
V. A. SICAM
Keyword(s):  
Phase Space ◽  
Signal Detection ◽  
Additive Noise ◽  
Dynamical Behavior ◽  
Data Sets ◽  
Gaussian Filter ◽  
Return Maps ◽  
Chaotic Signals ◽  
First Return Maps ◽  
Distinguishing Features

A smoothing, which has the effect of a Gaussian filter, has been performed on noisy chaotic digitized laser signals. It is shown that this smoothing can unravel distinguishing features of chaos in the phase space plots and first return maps and hence is useful in unambiguously differentiating chaos from noise. The calculation of the correlation dimensions reveal that the dynamics of the signals are not drastically affected by the smoothing. The type of smoothing discussed in this paper is useful in analyzing chaotic data sets corrupted by additive noise from the signal detection process.

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