Graph-optimisation-based self-calibration method for IMU/odometer using preintegration theory

Determination of calibration parameters is essential for the fusion performance of an inertial measurement unit (IMU) and odometer integrated navigation system. Traditional calibration methods are commonly based on the filter frame, which limits the improvement of the calibration accuracy. This paper proposes a graph-optimisation-based self-calibration method for the IMU/odometer using preintegration theory. Different from existing preintegrations, the complete IMU/odometer preintegration model is derived, which takes into consideration the effects of the scale factor of the odometer, and misalignments in the attitude and position between the IMU and odometer. Then the calibration is implemented by the graph-optimisation method. The KITTI dataset and field experimental tests are carried out to evaluate the effectiveness of the proposed method. The results illustrate that the proposed method outperforms the filter-based calibration method. Meanwhile, the performance of the proposed IMU/odometer preintegration model is optimal compared with the traditional preintegration models.

Multicamera Calibration Optimization Method Based on Improved Seagull Algorithm

There are some problems in the process of camera calibration, such as insufficient accuracy and poor accuracy. Based on the seagull algorithm, the adaptive differential evolution algorithm is combined with the seagull algorithm to optimize the multicamera calibration. The seagull algorithm can achieve good results on multiparameter problems and effectively avoid falling into local optima. In this paper, the adaptive differential search algorithm is adopted to improve the local search ability and optimize the local search and global search ability. According to Zhang Zhengyou's method, the calibrated parameter is obtained, in which the parameter is used as the initial value. Then, taking the minimum mean error as the criterion, the improved seagull algorithm (SOA-SaDE) is used to establish the objective function, and the internal parameters and distortion coefficient of the camera are further solved. Verification experiments showed that the fusion algorithm has less reprojection error and higher calibration accuracy gull algorithm.

The influence of color temperature mismatch in star simulator on positioning accuracy and magnitude measurement by star sensor

During the calibrating of star sensor, the calibration accuracy is greatly affected by the mismatch between the color temperature of the light and the to-be-measured star, which further affects the attitude measurement accuracy. This paper studied the near-infrared spectra of stars with different color temperatures, and analyzed the errors on star positioning and magnitude measurement of star sensor due to the color temperature mismatch. The results showed that in the central field of view, the spot centroid deviation caused by spectral mismatch is smaller than that in the edge field of view.And the defocus of the imaging surface also affects the spot centroid deviation. Besides, when calibrating with 6000K color temperature light, the maximum measurement error can reach -1.9126 magnitude.

Automatic Temperature Control System on Smart Poultry Farm Using PID Method

Chicken farmers in Indonesia are facing a problem as a result of the country's harsh weather conditions. Poultry species are very susceptible to temperature and humidity fluctuations. As a result, an intelligent poultry farm is necessary to intelligently adjust the temperature in the chicken coop. A smart poultry farm is a concept in which farmers may automatically manage the temperature in the chicken coop, thereby improving the livestock's quality of life. The purpose of this research is to develop a chicken coop prototype that focuses on temperature control systems on smart poultry farms via the PID control approach. The PID control method is expected to allow the temperature control system to adapt to the temperature within the cage, thereby assisting chicken farmers in their tasks. The sensor utilized is a DHT22 sensor with a calibration accuracy of 96.88 percent. The PID response was found to be satisfactory for the system with Kp = 10, Ki = 0, and KD = 0.1, and the time necessary for the system to reach the specified temperature was 121 seconds with a 1.03 % inaccuracy.

A Bayesian Neural Network-Based Method to Calibrate Microscopic Traffic Simulators

Calibrating the microsimulation model is essential to enhance its ability to capture reality. The paper proposes a Bayesian neural network (BNN)-based method to calibrate parameters of microscopic traffic simulators, which reduces repeated running of simulations in the calibration and thus significantly improves the calibration efficiency. We use BNN with probability distributions on the weights to quickly predict the simulation results according to the inputs of the parameters to be calibrated. Based on the BNN model with the best performance, heuristic algorithms (HAs) are performed to seek the optimal values of the parameters to be calibrated with the minimum difference between the predicted results of BNN and the field-measured values. Three HAs are considered, including genetic algorithm (GA), evolutionary strategy (ES), and bat algorithm (BA). A TransModeler case of highway links in Shanghai, China, indicates the validity of the proposed calibration method in terms of error and efficiency. The results demonstrate that the BNN model is able to accurately predict the simulation and adequately capture the uncertainty of the simulation. We also find that the BNN-BA model produces the best calibration efficiency, while the BNN-ES model offers the best performance in calibration accuracy.

On-Site Calibration Method for Line-Structured Light Sensor-Based Railway Wheel Size Measurement System

Line-structured light has been widely used in the field of railway measurement, owing to its high capability of anti-interference, fast scanning speed and high accuracy. Traditional calibration methods of line-structured light sensors have the disadvantages of long calibration time and complicated calibration process, which is not suitable for railway field application. In this paper, a fast calibration method based on a self-developed calibration device was proposed. Compared with traditional methods, the calibration process is simplified and the calibration time is greatly shortened. This method does not need to extract light strips; thus, the influence of ambient light on the measurement is reduced. In addition, the calibration error resulting from the misalignment was corrected by epipolar constraint, and the calibration accuracy was improved. Calibration experiments in laboratory and field tests were conducted to verify the effectiveness of this method, and the results showed that the proposed method can achieve a better calibration accuracy compared to a traditional calibration method based on Zhang’s method.

Solar Contamination on HIRAS Cold Calibration View and the Corrected Radiance Assessment

The deep-space (DS) view spectra are used as a cold reference to calibrate the Hyperspectral Infrared Atmospheric Sounder (HIRAS) Earth scene (ES) observations. The DS spectra stability in the moving average window is crucial to the calibration accuracy of ES radiances. While in the winter and spring seasons, the HIRAS detector-3 DS view is susceptible to solar stray light intrusion when the satellite flies towards the tail of every descending orbit, and as a result, the measured DS spectra are contaminated by the stray light pseudo spectra, especially in the short-wave infrared (SWIR) band. The solar light intrusion issue was addressed on 13 December 2019 when the DS view angle of the scene selection mirror (SSM) was adjusted from −77.4° to −87°. As for the historic contaminated data, a correction method is applied to detect the anomalous data by checking the continuity of the DS spectra and then replace them with the proximate normal ones. The historic ES observations are recalibrated after the contaminated DS spectra correction. The effect of the correction is assessed by comparing the recalibrated HIRAS radiances with those measured by the Cross-track Infrared Sounder onboard the Suomi National Polar-orbiting Partnership Satellite (SNPP/CrIS) via the extended simultaneous nadir overpasses (SNOx) technique and by checking the consistency among the radiance data from different HIRAS detectors. The results show that the large biases of the radiance brightness temperature (BT) caused by the contamination are ameliorated greatly to the levels observed in the normal conditions.

Accurate Reference Gas Mixtures Containing Tritiated Molecules: Their Production and Raman-Based Analysis

Highly accurate, quantitative analyses of mixtures of hydrogen isotopologues—both the stable species, H2, D2, and HD, and the radioactive species, T2, HT, and DT—are of great importance in fields as diverse as deuterium–tritium fusion, neutrino mass measurements using tritium β-decay, or for photonuclear experiments in which hydrogen–deuterium targets are used. In this publication we describe a production, handling, and analysis facility capable of fabricating well-defined gas samples, which may contain any of the stable and radioactive hydrogen isotopologues, with sub-percent accuracy for the relative species concentrations. The production is based on precise manometric gas mixing of H2, D2, and T2. The heteronuclear isotopologues HD, HT, and DT are generated via controlled, in-line catalytic reaction or by b-induced self-equilibration, respectively. The analysis was carried out using an in-line intensity- and wavelength-calibrated Raman spectroscopy system. This allows for continuous monitoring of the composition of the circulating gas during the self-equilibration or catalytic evolution phases. During all procedures, effects, such as exchange reactions with wall materials, were considered with care. Together with measurement statistics, these and other systematic effects were included in the determination of composition uncertainties of the generated reference gas samples. Measurement and calibration accuracy at the level of 1% was achieved.