Auto-calibration Algorithm Research Articles

Auto-Calibration을 이용한 Unstructured Environment에서의 실내 위치추정 기법

This paper proposes a way of expanding the use area of localization technique by using a beacon. In other words, we have developed the auto-calibration algorithm that recognizes the location of this beacon by attaching the beacon on an arbitrary position and by using the information of existing beacon under this situation. By doing so, the moving robot can overcome the limitation that the localization of moving robot is only possible within the area that has installed the existing beacon since the beacon cannot be installed on the accurate location when passing through a danger zone or an unknown zone. Accordingly, the moving robot can slowly move to the unknown zone according to this auto-calibration algorithm and can recognize its own location at a later time in a safe zone. The localization technique is essentially needed in using a moving robot and it is necessary to guarantee certain degree of reliability. Generally, moving robots are designed in a way to work well under the situation that the surroundings is well arranged and the localization techniques of using camera, laser and beacon are well developed. However due to the characteristics of sensor, there may be the cases that the place is dark, interfering radio waves, and/or difficult to install a beacon. The effectiveness of the method proposed in this paper has been proved through an experiment in this paper.

자동 보정 기능을 가진 직교 위상 수신기의 특성 해석

본 논문에서는 직교 위상 수신기에서 발생하는 동상 성분 채널과 직교 성분 채널간의 이득과 위상 불평형의 추정문제를 다룬다. 즉, 자동 보정 기능을 가지는 직교 위상 수신기에서의 백색 Gaussian 잡음을 고려한 통계적인 특성 분석을 통하여 제안된 알고리즘에 의한 추정값이 점근적으로 비편향 최소 분산 추정(asymptotically minimum-variance unbiased estimate) 특성을 가짐을 보여준다. 이를 위하여 먼저 자동 보정 알고리즘에서 사용하는 샘플링 값들에 대한 통계적인 특성을 구하고, 이 샘플 값들의 함수의 형태로 구해지는 이득과 위상 불평형 추정값들의 통계적인 특성을 분석하기 위해 추정값들의 확률분포함수를 구한다. 이를 기반으로 평균 함수 및 분산 함수를 계산하여 추정값들이 비편향 최소 분산 추정 특성을 나타냄을 확인한다. This paper deals with an estimation problem of the gain and phase imbalances between the in-phase and quadrature components in the quadrature receivers which are widely used in wireless communications. It is shown that the estimates derived from the suggested auto-calibration algorithm is asymptotically minimum-variance unbiased as a function of the sampling time. In order to show this characteristic, the probability density functions of the estimates for the gain and phase imbalances are derived first. Then the mean and variance functions are investigated analytically or numerically based on the density functions.

A 16-bit 65-MS/s Pipeline ADC With 80-dBFS SNR Using Analog Auto-Calibration in SiGe SOI Complementary BiCMOS

A 16-bit 65-MS/s switched-capacitors pipeline analog-to-digital converter built in 0.45-mum 25-GHz f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> complementary silicon-on-insulator BiCMOS delivers 80.1-dBFS signal-to-noise ratio, 98-dBc spurious-free dynamic range (SFDR) with 3-Vpp input range at 2-MHz input frequency. The 5 times 5.3 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> die consumes 1.7 W from a dual plusmn2.7-V supply. A noniterative analog auto-calibration algorithm simultaneously compensates for both random mismatch in the capacitors of the first quantizer stages, and integral nonlinearity curvatures contributed by sample-and-hold (S/H) and voltage reference buffers, yielding SFDR optimizations up to 12 dB. The test chip performance validates the transient noise simulations run for the analog front-end and the clock jitter, corroborating the efficacy of the circuit techniques adopted to design S/H, clock and references.

Magnetometer Autocalibration Leveraging Measurement Locus Constraints

An autocalibration algorithm for calibration of magnetometer triads used to determine heading in small aerial vehicles is developed and its performance is analyzed. The algorithm estimates the 12 calibration parameters, which are elements of an affine transformation mapping measured, and thus, erroneous magnetometer measurements into corrected field measurements. The mapping corrects magnetometer output errors due to hard-iron biases, scale factor deviations, and nonorthogonality effects caused by soft irons or physical arrangement of the sensor axes. The correction mapping is determined by leveraging the fact that the locus of Earth's magnetic field vector as measured by a triad of magnetometers is an ellipsoid. The coefficients defining the ellipsoid are computed using a total least-squares estimator. It is shown that, generally, in such autocalibration algorithms, soft-iron errors and sensing axes nonorthogonality can result in an error mode that is unobservable. These conditions are identified and the algorithm incorporates a method for detecting them. In these instances, even though autocalibration can provide an estimate of only 9 of the 12 calibration parameters, it is shown that how external measurements from a triad of accelerometers and a global positioning system receiver can provide the information needed to estimate the unobservable error mode.

Autocalibration Algorithm for Robust Capon Beamforming

The robust Capon beamformer (RCB) is more robust than the standard Capon beamformer when there is uncertainty, as in the case of a sensor location error or an array model mismatch. However, the RCB suffers from mutual coupling between the array sensors, which is difficult to neglect in practice. In this work, an autocalibration algorithm is described that improves the RCB by recursively calibrating the uncertainty due to mutual coupling. The proposed method is better able to estimate the angle-of-arrival and power of the signal of interest than the RCB, as shown by numerical simulation and practical analysis of experimental data obtained in an anechoic chamber

Auto-calibration by linear iteration using the DAC equation

This paper presents an iterative algorithm for auto-calibration. The proposed algorithm switches between linearly estimating the dual of the absolute conic and the intrinsic parameters, while also incorporating the rank-3 constraint on the intrinsic parameters. The proposed algorithm locates in-between of a non-linear optimization and initial linear computation, and provides robust and sufficiently accurate initial values for a bundle adjustment. The performance of the algorithm is shown for both simulated and real data, especially in the important case of natural (zero skew and unit aspect ratio) cameras.

Camera auto-calibration using a sequence of 2D images with small rotations

In this study, we describe an auto-calibration algorithm with fixed but unknown camera parameters. We have modified Triggs' algorithm to incorporate known aspect ratio and skew values to make it applicable for small rotation around a single axis. The algorithm despite being a quadratic one is easy to solve. We have applied the algorithm to some artificial objects with known size and dimensions for evaluation purposes. In addition, the accuracy of the algorithm has been verified using synthetic data. The described method is particularly suitable for three dimensional human head modeling.

Robust DOA estimation and array calibration in the presence of mutual coupling for uniform linear array

The presence of unknown mutual coupling between array elements is known to significantly degrade the performance of most high-resolution direction of arrival (DOA) estimation algorithms. In this paper, a robust subspace-based DOA estimation and array auto-calibration algorithm is proposed for uniformly linear array (ULA), when the array mutual coupling is present. Based on a banded symmetric Toeplitz matrix model for the mutual coupling of ULA, the algorithm provides an accurate and high-resolution DOA estimate without any knowledge of the array mutual couplings. Moreover, a favorable estimate of mutual coupling matrix can also be achieved simultaneously for array auto-calibration. The algorithm is realized just via one-dimensional search or polynomial rooting, with no multidimensional nonlinear search or convergence burden involved. The problem of parameter ambiguity, statistically consistence and efficiency of the new estimator are also analyzed. Monte-Carlo simulation results are also provided to demonstrate the effectiveness and behavior of the proposed algorithm.

A new data processing and calibration method for an eye-tracking device pronunciation system

In this paper, a new data processing and calibration method for a pronunciation system of an eye-tracking device is described. The eye-tracking device was created using both head mounted display (HMD) technology and remote operation capabilities. A pattern recognition computer program was used to distinguish the pupil position and calculate its coordinates. This system can be adapted to provide a digital speech function. A new method for processing the image of the eye in the PC-based system was also developed. With one video CCD camera and frame grabber analyzing a series of human pupil images while the subject is gazing at the screen, an auto-calibration algorithm is used to obtain the direction of the eye gaze in real time. The computers provide the speech sound according to the location where the eye gazes exceed 0.5 s . The availability of multipurpose in this eye-tracking system with very simple equipment will be reconfirmed for future advanced research.

Improved time-base for waveform parameter estimation

An improved gated oscillator time-base and associated auto-calibration algorithm for use in a high-accuracy sampling waveform acquisition system are described. The time-base architecture consists of a stable 100 MHz gated oscillator, 24-bit counter chain, and a clock period interpolator. The nominal, uncorrected linearity of the time-base is approximately /spl plusmn/30 ps. By using an iterative, sine-fit based algorithm, the linearity has been improved to <5 ps. Details of the performance and major sources of error of the time-base and correction algorithm in an equivalent time sampling system are also discussed.

Intelligent and Low Cost Continuous Relative Density Measurement in Batch Fermenters

In this article we present two methods for the real time automatic measurement of the relative density. The first one relies on the heat generated during the fermentation which requires no additional sensors in the tanks. It is based on the thermal model of the tank and the only additional requirements are the measurement of the temperature of the surrounding air. The other method is based on two low-cost pressure sensors with an algorithm for autocalibration and compensation of temperature perturbation. The autocalibration is done during fermenter feeding and with only one manual measurement of the relative density.

An autocalibrating model for simulating and measuring net canopy photosynthesis using a standard greenhouse climate computer

A model for measuring net canopy photosynthesis in commercial greenhouses is described. The problem of calculating CO 2 fluxes at high ventilation rates with sufficient accuracy with commercially available equipment is discussed, and a solution is suggested, using two cooperating submodels and an autocalibration algorithm. The first is a CO 2-balance model which calculates the canopy photosynthesis as the residual accounting for the other CO 2 fluxes. The model stresses the importance of CO 2 infiltration at low ventilation rates and maintains an experience database of measured photosynthesis rates and related climatic variables. Model 2 is a black-box photosynthesis calculation that simulates the crop's photosynthetic response using temperature, irradiance, and CO 2 concentration as variables Model 2 takes over at higher ventilation rates, when model one cannot function with sufficient accuracy. The autocalibration algorithm uses the experience database from model 1 to tune model 2's performance to actual crop characteristics by performing regression routines once every day. The model was implemented using a previously described standard model interface on a standard climate computer system and allowed hourly monitoring of photosynthesis rates in standard greenhouses.