Real-time Self-calibration Research Articles

Real-time Self-calibration Method of Vehicle Camera Attitude Based on ANN

The research of the monocular vision ranging method has great research value in the field of intelligent vehicles. Camera calibration is an important step in a monocular vision ranging model. The accuracy of camera calibration directly determines the accuracy of ranging. Because the camera attitude may change during vehicle driving, it will have a certain impact on the accuracy of the ranging algorithm. Therefore, based on a monocular ranging model and focal length calibration method based on geometric transformation, a real-time camera attitude self-calibration method based on the width measurement model and ANN model is proposed in this paper. Firstly, the method takes the wheel width of the known vehicle type as a fixed value, takes the contact points between the two wheels of the front vehicle and the ground as the feature points, and brings them into the width measurement model to form constraints. However, the single formula formed by a single pair of feature points cannot solve the camera inclination of multiple dimensions at the same time, and it is difficult to solve the analytical solution of the complex formula. In this paper, the ANN model is proposed to fit and solve the formula, and a large number of data sets are obtained through experimental point distribution to train and test the model. The results show that the ranging accuracy of using this method to calibrate the camera tilt angle is unchanged compared to the previous measurement accuracy using sensors, meeting the ranging requirements

Improvement of optoacoustic angiographic images using one-dimensional deconvolution with adaptive real-time self-calibration

This work introduces a method of one-dimensional deconvolution with Tikhonov regularization for enhancing three-dimensional optoacoustic images in vivo. The method employs adaptive self-calibration to eliminate frequency-dependent distortions associated with ultrasound propagation and detection. By adapting to the inhomogeneous frequency characteristics of the examined medium, the method eliminates the need for additional calibration experiments. The processing time for three-dimensional optoacoustic data of size 200x200x100 voxels is less than 5 ms, facilitating the real-time enhancement of angiographic images and improving the effective spatial resolution by more than 50%.

Real-Time Self-Calibration Method for SO2 Ultraviolet Cameras

Real-Time Self-Calibration Method for SO2 Ultraviolet Cameras

Enzyme-modulated photothermal immunoassay of chloramphenicol residues in milk and egg using a self-calibrated thermal imager

Highly sensitive and accurate detection of chloramphenicol is of paramount importance for food safety. Herein, an enzyme-modulated photothermal immunosensor that uses a self-calibrated thermal imaging system (SCTIS) as signal read-out was developed for detecting chloramphenicol. In this immunosensor, alkaline phosphatase was used as a modulator of the photothermal conversion. It could hydrolyze the substrate into ascorbic acid, thereby reducing oxidized 3,3′,5,5′-tetramethylbenzidine, which exhibited a near-infrared laser-driven photothermal effect. For precise temperature measurement, the SCTIS was designed by using the temperature compensation of a ceramic chip to enable real-time self-calibration of the temperature. This SCTIS-based immunosensor could detect chloramphenicol with a LOD of 9 pg/mL in 2 h, and relative standard derivations from 3.95% to 13.58%. The average recoveries in milk and egg samples ranged from 76% to 114%. This versatile sensing strategy can detect various targets by altering recognition elements, thus has wide applicability in food safety testing and monitoring.

Real-time self-calibration PGC-Arctan demodulation algorithm in fiber-optic interferometric sensors.

Fiber-optic interferometric sensors (FOISs) are widely used in seismometers, hydrophones, and gyroscopes. The arctangent approach of phase-generated carrier (PGC-Arctan) demodulation algorithm is one of the key demodulation techniques in FOISs. The conventional PGC-Arctan demodulation algorithm requires the specific value of the phase modulation depth C to work properly. However, C will variate with laser wavelength, temperature, and humidity in the actual working environment, which leads to harmonic distortion and even demodulation failure. In this paper, a novel PGC demodulation algorithm called self-calibration PGC-Arctan (PGC-Arctan-SC) demodulation algorithm is presented. The proposed algorithm can jointly estimate the accurate C value by the elliptical parameters and C-related components while suppressing nonlinear distortion by ellipse fitting algorithm (EFA). Then C can be calibrated to the specific predefined optimal value by the closed-loop proportion integration differentiation (PID) module. The simulation results are consistent with theoretical analysis, and the all-digital PGC-Arctan-SC demodulation system is implemented on the embedded SoC. The experimental results show that C can be estimated and calibrated accurately in real time. The signal-to-noise and distortion ratio (SINAD) of the PGC-Arctan-SC demodulation output achieves 61.57 dB.

A Method toward Real-Time CFD Modeling for Natural Ventilation

Natural ventilation is often used as a passive technology to reduce building energy consumption. To leverage the rule-based natural ventilation control to more advanced control at multiple spatial scales, mathematical modeling is needed to calculate the real-time ventilation rate, indoor air temperatures, and velocities at high spatial resolution. This study aims to develop a real-time mathematical modeling framework based on computational fluid dynamics (CFD). The real-time concept is implemented by using real-time sensor data, e.g., wall surface temperatures as boundary conditions, while data assimilation is employed to implement real-time self-calibration. The proof of concept is demonstrated by a case study using synthetic data. The results show that the modeling framework can adequately predict real-time ventilation rates and indoor air temperatures. The data assimilation method can nudge the simulated air velocities toward the observed values to continuously calibrate the model. The real-time CFD modeling framework will be further tested by the real-time sensor data once building construction is fully completed.

Method for real-time self-calibrating GLONASS code inter-frequency bias and improvements on single point positioning

Utilization of frequency-division multiple access (FDMA) leads to GLONASS pseudorange and carrier phase observations suffering from variable levels inter-frequency bias (IFB). The bias related with carrier phase can be absorbed by ambiguities. However, the unequal code inter-frequency bias (cIFB) will degrade the accuracy of pseudorange observations, which will affect positioning accuracy and convergence of precise point positioning (PPP) when including GLONASS satellites. Based on observations made on un-differenced (UD) ionospheric-free combinations, GLONASS cIFB parameters are estimated as a constant to achieve GLONASS cIFB real-time self-calibration on a single station. A total of 23 stations, with different manufacturing backgrounds, are used to analyze the characteristics of GLONASS cIFB and its relationship with variable receiver hardware. The results show that there is an obvious common trend in cIFBs estimated using broadcast ephemeris for all of the different manufacturers, and there are unequal GLONASS inter-satellite cIFB that match brand manufacture. In addition, a particularly good consistency is found between self-calibrated receiver-dependent GLONASS cIFB and the IFB products of the German Research Centre for Geosciences (GFZ). Via a comparative experiment, it is also found that the algorithm of cIFB real-time self-calibration not only corrects receiver-dependent cIFB, but can moreover eliminate satellite-dependent cIFB, providing more stable results and further improving global navigation satellite system (GNSS) point positioning accuracy. The root mean square (RMS) improvements of single GLONASS standard point positioning (SPP) reach up to 54.18 and 53.80% in horizontal and vertical direction, respectively. The study’s GLONASS cIFB self-estimation can realize good self-consistency between cIFB and stations, working to further promote convergence efficiency relative to GPS + GLONASS PPP. An average improvement percentage of 19.03% is observed, realizing a near-consistent accuracy with GPS + GLONASS fusion PPP.

A METHOD FOR SELF-CALIBRATION IN SATELLITE WITH HIGH PRECISION OF SPACE LINEAR ARRAY CAMERA

At present, the on-orbit calibration of the geometric parameters of a space surveying camera is usually processed by data from a ground calibration field after capturing the images. The entire process is very complicated and lengthy and cannot monitor and calibrate the geometric parameters in real time. On the basis of a large number of on-orbit calibrations, we found that owing to the influence of many factors, e.g., weather, it is often difficult to capture images of the ground calibration field. Thus, regular calibration using field data cannot be ensured. This article proposes a real time self-calibration method for a space linear array camera on a satellite using the optical auto collimation principle. A collimating light source and small matrix array CCD devices are installed inside the load system of the satellite; these use the same light path as the linear array camera. We can extract the location changes of the cross marks in the matrix array CCD to determine the real-time variations in the focal length and angle parameters of the linear array camera. The on-orbit status of the camera is rapidly obtained using this method. On one hand, the camera’s change regulation can be mastered accurately and the camera’s attitude can be adjusted in a timely manner to ensure optimal photography; in contrast, self-calibration of the camera aboard the satellite can be realized quickly, which improves the efficiency and reliability of photogrammetric processing.

A METHOD FOR SELF-CALIBRATION IN SATELLITE WITH HIGH PRECISION OF SPACE LINEAR ARRAY CAMERA

Abstract. At present, the on-orbit calibration of the geometric parameters of a space surveying camera is usually processed by data from a ground calibration field after capturing the images. The entire process is very complicated and lengthy and cannot monitor and calibrate the geometric parameters in real time. On the basis of a large number of on-orbit calibrations, we found that owing to the influence of many factors, e.g., weather, it is often difficult to capture images of the ground calibration field. Thus, regular calibration using field data cannot be ensured. This article proposes a real time self-calibration method for a space linear array camera on a satellite using the optical auto collimation principle. A collimating light source and small matrix array CCD devices are installed inside the load system of the satellite; these use the same light path as the linear array camera. We can extract the location changes of the cross marks in the matrix array CCD to determine the real-time variations in the focal length and angle parameters of the linear array camera. The on-orbit status of the camera is rapidly obtained using this method. On one hand, the camera’s change regulation can be mastered accurately and the camera’s attitude can be adjusted in a timely manner to ensure optimal photography; in contrast, self-calibration of the camera aboard the satellite can be realized quickly, which improves the efficiency and reliability of photogrammetric processing.

Diffuse reflectance spectroscopy with a self-calibrating fiber optic probe

Calibration of the diffuse reflectance spectrum for instrument response and time-dependent fluctuation as well as interdevice variations is complicated, time consuming, and potentially inaccurate. We describe a novel fiber optic probe with a real-time self-calibration capability that can be used for tissue optical spectroscopy. The probe was tested in a number of liquid phantoms over a relevant range of tissue optical properties. Absorption and scattering coefficients are extracted with an average absolute error and standard deviation of 6.9%+/-7.2% and 3.5%+/-1.5%, respectively.