Sensor Noise Sources Research Articles

Bayesian multilevel random‐effects model for estimating noise in image sensors

Sensor noise sources cause differences in the signal recorded across pixels in a single image and across multiple images. This study presents a Bayesian approach to decomposing and characterising the sensor noise sources involved in imaging with digital cameras. A Bayesian probabilistic model based on the (theoretical) model for noise sources in image sensing is fitted to a set of a time-series of images with different reflectance and wavelengths under controlled lighting conditions. The image sensing model is a complex model, with several interacting components dependent on reflectance and wavelength. The properties of the Bayesian approach of defining conditional dependencies among parameters in a fully probabilistic model, propagating all sources of uncertainty in inference, makes the Bayesian modelling framework more attractive and powerful than classical methods for approaching the image sensing model. A feasible correspondence of noise parameters to their expected theoretical behaviours and well-calibrated posterior predictive distributions with a small root mean square error for model predictions have been achieved in this study, thus showing that the proposed model accurately approximates the image sensing model. The Bayesian approach could be extended to formulate further components aimed at identifying even more specific parameters of the imaging process.

Magnetic noise contribution of the ferromagnetic core of induction magnetometers

Abstract. The performance of induction magnetometers, in terms of resolution, depends both on the induction sensor and the electronic circuit. To investigate accurately the sensor noise sources, an induction sensor, made of a ferrite ferromagnetic core, is combined with a dedicated low voltage and current noise preamplifier, designed in CMOS 0.35 μm technology. A modelling of the contribution of the ferromagnetic core to the noise through the complex permeability formalism is performed. Its comparison with experimental measurements highlight another possible source for the dominating noise near the resonance.

Grey Level and Noise Evaluation of a Foveon X3 Image Sensor: A Statistical and Experimental Approach

Radiometric values on digital imagery are affected by several sources of uncertainty. A practical, comprehensive and flexible procedure to analyze the radiometric values and the uncertainty effects due to the camera sensor system is described in this paper. The procedure is performed on the grey level output signal using image raw units with digital numbers ranging from 0 to 212-1. The procedure is entirely based on statistical and experimental techniques. Design of Experiments (DoE) for Linear Models (LM) are derived to analyze the radiometric values and estimate the uncertainty. The presented linear model integrates all the individual sensor noise sources in one global component and characterizes the radiometric values and the uncertainty effects according to the influential factors such as the scene reflectance, wavelength range and time. The experiments are carried out under laboratory conditions to minimize the rest of uncertainty sources that might affect the radiometric values. It is confirmed the flexibility of the procedure to model and characterize the radiometric values, as well as to determine the behaviour of two phenomena when dealing with image sensors: the noise of a single image and the stability (trend and noise) of a sequence of images.

Sensor fusion and actuator system of a quadrotor helicopter

This article focuses on the sensor and actuator system of an autonomous indoor quadrotor helicopter. The sensor system has two parts: an inertial measurement unit (IMU) and a vision system. The fusion between the two systems is solved by extended Kalman filters. The calibration of the inertial measurement unit is described for various types of errors. The variance analysis is performed for the noise sources of sensors. The actuators of the helicopter are the four rotors. The identification and low level control of the brushless DC motor based rotor system is also presented. The embedded control system integrates a lot of processors and communication lines. The verification of the system´s parts were performed under real-time conditions. The main results of the paper are the new calibration algorithm for the different sensors and the real-time realization of the complex sensory system that may be part of a formation control system of UAVs.

A Technique for Evaluation of CCD Video-Camera Noise

This paper presents a technique to identify and measure the prominent sources of sensor noise in commercially available charge-coupled device (CCD) video cameras by analysis of the output images. Noise fundamentally limits the distinguishable content in an image and can significantly reduce the robustness of an image processing application. Although sources of image sensor noise are well documented, there has been little work on the development of techniques to identify and quantify the types of noise present in CCD video-camera images. A comprehensive noise model for CCD cameras was used to evaluate the technique on a commercially available CCD video camera.

Electromagnetic and Acoustic Emission Fine Spectra

A new measuring method for the detection of fine spectra of electromagnetic and acoustic emission (EME and AE) signals from small cracks is described. It requires wide band ultra-low noise amplifiers, analogue filters, the optimization of signal to noise ratio of sensors and the application of noise elimination methods. Analyses of noise sources in sensors and preamplifiers are given. They are thermal noise, polarization noise and low frequency 1/f noise. Measuring set-up background noise suppression involving also the electromagnetic shielding allows us to detect signals in the range of 1 to 100 nV. This measuring set-up was used to observe crack initiation in granite samples. AE and EME signals show different behaviour in the first interval of about 20 μs just after crack initiation. For the first stage of crack initiation the frequency spectrum of EME signal is given by the eigen vibrations of crack walls, by the internal friction and the sample electrical conductivity. We observed that the crack opening and crack wall vibration create the high frequency signal in the frequency band up to 10 MHz. These signals were observed in the first time interval of about 20 μs. After that the frequency spectrum is given by the sample eigen vibration or the sample boundary conditions, and we have observed the spectra in the frequency range 100 kHz to 2 MHz.

Applications of Kalman filtering to real-time trace gas concentration measurements.

A Kalman filtering technique is applied to the simultaneous detection of NH3 and CO2 with a diode-laser-based sensor operating at 1.53 micrometers. This technique is developed for improving the sensitivity and precision of trace gas concentration levels based on direct overtone laser absorption spectroscopy in the presence of various sensor noise sources. Filter performance is demonstrated to be adaptive to real-time noise and data statistics. Additionally, filter operation is successfully performed with dynamic ranges differing by three orders of magnitude. Details of Kalman filter theory applied to the acquired spectroscopic data are discussed. The effectiveness of this technique is evaluated by performing NH3 and CO2 concentration measurements and utilizing it to monitor varying ammonia and carbon dioxide levels in a bioreactor for water reprocessing, located at the NASA-Johnson Space Center. Results indicate a sensitivity enhancement of six times, in terms of improved minimum detectable absorption by the gas sensor.

Frequency domain design methodology for uncertain cascaded multiple-loop systems with plant modification

Since the internal signal level increases after using a plant modification loop, Horowitz and Wang (1979, 1988) proposed a quantitative synthesis feedback design method using the bandwidth propagation effect to take care of the internal signal level. The bandwidth increase phenomenon makes it hard work to maintain internal signal level reasonably. Moreover, the noise components are most important in the high-frequency range. It is desirable to decrease loop transmission functions as fast as possible in the high-frequency range to achieve minimum sensor noise sources. In the paper, a frequency domain design methodology for uncertain cascaded multiple-loop systems with plant modification is developed. The plant uncertainties are transferred to the values of equivalent external disturbances at the plant output. Thus, the design problem will become an equivalent external disturbance rejection problem. At the same time the bandwidth propagation effect can be eliminated and loop transmission functions decrease as quickly as possible.

The Resolution Threshold of MUSIC with Unkown Spatially Colored Noise

In this correspondence, we present a resolution analysis for the MUSIC algorithm in a spatially colored noise environment. By applying Wilkinson's first-order perturbation theory to the colored- noise term, we have shown that the MUSIC spectrum estimates at spa- tial frequencies of plane wave arrivals are proportional to the square of array signal-to-interference ratio (ASIR), and that the resolution threshold ASIR for a uniform array is proportional to the inverse square of normalized spatial frequency separation between two ar- rivals. Derivations and simulations are given for the case of two equi- power plane wave arrivals. The presence of unknown spatially colored noise in spatial fre- quency estimation of plane wave arrivals can cause significant per- formance degradation for the MUSIC algorithm. For signal arrivals in a spatially white-noise environment, a complete eigenspace sep- aration between signal subspace and noise subspace can be ob- tained, and MUSIC spectrum exhibits infinite peaks at signal fre- quencies. In a spatially colored noise (SCN) environment, an eigenspace separation with such properties can be made only if the correlation structure of the SCN is known a priori (I). For an un- known SCN, any partitioned subspace designated as the signal sub- space will include components from part of the SCN, and the or- thogonal relation between signal direction vectors and the noisc subspace will be destroyed. As a result,' spectral peaks in the MU- SIC estimator are finite and resolutions are limited. In this paper, spatially colored noise (SCN) is radiation sources whose spatial correlation matrix has a nonidentity structure. Spa- tially colored noise typically arises from sources continuously dis- tributed in spatial frequency. Examples are cosmic noise and at- mospheric noise. It also arises from additive sensor noise sources when they are nonwhite with unknown correlations or, when they are uncorrelated but of unequal powers. Mathematically, SCN may be represented by a matrix component Q in a spatial correlation matrix R (1)

Noise in sensors

Significant advances in the field of sensors and the need for improving the resolution in the measurement of physical, chemical and biological quantities, are increasing the importance of the characterization of the noise sources in sensors. The noise in fact limits the ultimate performances that can be obtained from a given device in terms of signal to noise ratio. After a brief review of the fundamental noise sources, particular attention is dedicated to some examples of specific sensors for which noise aspects are presented and discussed. Noise considerations will concern temperature, gas, displacement, weak force and photon sensors.

Quantitative synthesis of multiple-loop feedback systems with large uncertainty†

Abstract This work extends single input-output linear time invariant minimum-phase ‘ quantitative feedback synthesis ’ to two new complex plant structures with internal sensing points. One is the triangular structure. The second consists of parallel branches, each with cascaded sections. Due to uncertainty, the plant parameters are elements of given sets. The system response must satisfy specified time or frequency domain tolerances. The basic problem is how to divide the feedback burden among the available loops so as to minimize the net rms effect at the plant input, of the various sensor noise sources. Frequency-response formulations are presented which provide a clear understanding of the trade-off among the feedback loops. One vital feature is ‘ free uncertainty ’, wherein a loop optimized to cope with uncertainty U1 , may in fact for some frequency ranges, handle uncertainty U≫U1 . A second is ‘ bandwidth propagation ’ wherein the loops take turns in dominating the design over the frequency range. T...

A synthesis theory for a class of multiple-loop systems with plant uncertainty

Abstract There is given a single input-output linear, time-invariant plant with large parameter uncertainty consisting of two parallel branches, one of which has n internal sensing points. The objective is to satisfy specified frequency domain bounds on the system response to commands and disturbances over the parameter range, and to do so with sensibly minimum net effect at the plant input, of the n + 1 sensor noise sources. The basic problem is how to best divide the feedback burden among the n + 1 available feedback loops Li. The procedure developed has high transparency, giving early perspective on the loop bandwidths, permitting approximate loop trade-offs without a detailed design. While the development is more difficult than in the single cascaded plant system, the procedure and final results are very similar : each Lihas only one distinct frequency range say ωi, in which there is trade-off between Liand LI+1and ωi i+1 <ωiwith steadily increasing loop bandwidths going backwards from plant output to...

Synthesis of cascaded multiple-loop feedback systems with large plant parameter ignorance

In a cascaded plant with n sensing points, n independent feedback loops are available to achieve quantitative sensitivity specifications. The optimum design is defined as that which achieves this with minimum net effect, of the n sensor noise sources, at the plant input. A design procedure is presented wherein one works backwards step by step from the system output, designing each loop function L i almost as if the remaining loops ( L i+ j , j>0) are perfect. Even in large plant ignorance problems, only the outer loop L i may be large over some frequency range. In general | L i | max < 1, i ≠ 1 and | L i+1 | max < | L i | max. Each L i has only one distinct frequency range say at ω c, i requiring trade-off between L i and L i+1 . Only in this range is significant design effort required. However, ω c, i+1 > ω c, i so the primary price paid is in the steadily increasing “bandwidth” of each loop. The design procedure is highly transparent with strong universalistic features, permitting the use of universal design curves.