Measurement Accuracy Research Articles

Vision Systems for a UR5 Cobot on a Quality Control Robotic Station

This paper addresses the development of a vision system for the UR5 cobot and the corresponding operating algorithm of the robotic quality control station. The hardware–software architecture of the developed robotic station consisting of a UR5 cobot equipped with a web camera and a stationary industrial camera with a lighting system is presented. Image processing and analysis algorithms are described, the method of control and communication between the station components is discussed, and operating scenarios are presented as a single robotic station and as a part of the robotic line. Based on the results which were obtained, the level of measurement noise, accuracy, and repeatability of the developed vision system were estimated. A novel complete vision system architecture with hardware–software modules for the UR5 cobot quality control station is shown and discussed. The software part based on Python 3.12 language, OpenCV 4.7.0.68 libraries, and the PolyScope 1.8 environment incorporates modules for system calibration, image acquisition, preprocessing and image analysis (for objects’ location and geometric measurements) and for robotic cell communication and control. The hardware part of the UR5 cobot vision system is based on a PC with two independent and distinct cameras: one permanently affixed and the other mounted to the cobot’s flange. This innovative setup, combined with software architecture, broadens the scope of existing robotic quality control applications.

Ensuring Clinical Excellence: The Mindray SAL9000 Biochemical Immunoassay System.

This study aimed to evaluate the performance and clinical laboratory adaptability of the Mindray SAL9000 biochemical immunoassay automation system, ensuring compliance with ISO 15189 standards and relevant national requirements. We conducted comprehensive performance verification tests on 21 biochemical analytes and 15 immunoassays, including precision, accuracy, linear bias, measurement range assessments, interference testing, reference range validation, inter-instrument comparison, and carryover verification. The Mindray SAL9000 demonstrated high performance across various parameters, with all analytes showing good linearity and minimal bias. While specific interfering substances affected some analytes, the system showed excellent resistance to common interferences such as hemolysis, ascorbic acid, and jaundice. The inter-instrument comparison with the BS2000M and Roche 702 indicated a good correlation, with most parameters showing biases of less than 10%, although exceptions were noted for ALT and AST. In conclusion, the Mindray SAL9000 meets clinical requirements through its high precision, excellent accuracy, and broad measurement range, making it a reliable and adaptable choice for clinical outpatient and emergency laboratories.

Is body composition important in the context of renal function in pediatric neurogenic bladder?

Neurogenic bladder due to myelomeningocele (MMC) is a significant risk factor for chronic kidney disease in children. Cystatin C (CysC) is a more accurate GFR marker than creatinine as it is unaffected by muscle mass but may be influenced by fat mass and BMI. This study evaluates: (1) GFR measurement accuracy using CysC and creatinine in MMC-related neurogenic bladder, (2) the relationship between body composition via bioelectrical impedance analysis (BIA) and renal parameters, and (3) the use of BIA for non-invasive GFR and body composition assessment. Forty children (median age 9.96years) underwent serum creatinine, CysC testing, and BIA measurements. We assessed age, sex, spinal lesion level, anthropometric measurements, BMI, and activity using Hoffer's scale. GFR was calculated using five creatinine-based formulas, three CysC-based, and three combining CysC and creatinine, including BIA GFR as an alternative approach. Creatinine-based GFR estimates were significantly higher than CysC-based GFR. Although only 30% of MMC patients met the traditional BMI criteria for overweight/obesity, 62.5% were obese based on BIA-measured body fat percentage. Significant differences were found in CysC and CysC-based GFR equations within BMI and fat mass groups. Positive correlations were observed between CysC and body weight, BMI percentiles, body fat mass and fat-to-muscle ratio. Muscle mass positively correlated with creatinine. BIA-determined fat mass percentage is a more sensitive obesity indicator than BMI in MMC patients. CysC levels and CysC-based GFR equations are influenced by body fat mass, requiring consideration of adiposity to avoid misestimating renal impairment.

An Optimal SVD Filtering Method for Measurement Accuracy Improvement against Harmonic Disturbance in Grid-Connected Inverters

An Optimal SVD Filtering Method for Measurement Accuracy Improvement against Harmonic Disturbance in Grid-Connected Inverters

Experimental Study of Hot-Sphere Anemometer Response in Stratospheric Environment.

Accurate wind speed measurement in low-pressure conditions is crucial for the thermal performance validation and attitude control of stratospheric aircraft. As air density decreases, traditional wind speed measurement systems based on principles such as dynamic pressure, heat transfer, ultrasound, and particle velocimetry face significant challenges when applied in low-pressure environments, often failing to achieve the required measurement accuracy. This paper presents the development of a wind speed simulation system based on a rotation method designed to operate in low-pressure conditions, utilizing a space environment simulation chamber in conjunction with a high-precision turntable. The system was employed to conduct response tests on a constant heat flow thermal sphere anemometer within a stratospheric pressure range of 1 kPa to 30 kPa. The experimental results revealed that at extremely low Reynolds numbers, the probe signal exhibited increasing nonlinearity, significantly affecting the response curve at pressures below 15 kPa. While the sensitivity of the hot-sphere probe remained relatively stable at wind speeds above 5 m/s, it decreased nonlinearly as the pressure dropped when wind speeds fell below 5 m/s. Furthermore, this paper analyzes the impact of various interpolation methods on wind speed conversion errors, providing valuable data to support the future development and validation of stratospheric aircraft.

Using Advanced InSAR Techniques and Machine Learning in Google Earth Engine (GEE) to Monitor Regional Black Soil Erosion—A Case Study of Yanshou County, Heilongjiang Province, Northeastern China

The black soil region experiences complex erosion due to natural processes and intense human activities, leading to soil degradation and adverse ecological and agricultural impacts. However, the complexities involved in quantifying regional erosion poses remarkable challenges in accurately assessing the current status of regional soil erosion for effective soil conservation. To solve this issue, we proposed a new method for monitoring soil erosion using Interferometric synthetic aperture radar (InSAR) technology and machine learning algorithms within the Google Earth Engine platform. The new method not only enables regional-scale monitoring, but also ensures high accuracy in measurement (millimeter-level). The erosion susceptibility of the study area (Yanshou County, Heilongjiang Province, Northeastern China) was also classified using random forest algorithms to refine the monitored and predicted soil erosion. The results indicate that the five-year (2016–2021) deformation in Yanshou County was −11.08 mm, with a significant mean cumulative deformation of −8.08 mm yr−1 occurring in 2017. The driving factor analysis shows that the region was subject to the compound effect of water and freeze–thaw erosion, closely related to crop phenological stages. The susceptibility analysis indicates that 73.3% of the region was susceptible to erosion, with a higher probability in river areas, at high altitudes, and on steep slopes. However, good vegetation cover can reduce the risk of soil erosion to some extent. This study offers a new perspective on monitoring regional soil erosion in the black soil region of China. The proposed method holds potential for future expansion to monitor soil erosion in a larger areas, thereby guiding the strategies development for protection of the agriculturally important black soil.

Long-Term Reproducibility of BMD-Measurements with Clinical QCT Using Simultaneous and Asynchronous Calibration Methods and Different Measurement and Reconstruction Protocols.

Osteoporosis is underdiagnosed and undertreated. To improve timely fracture risk assessment optimized densitometry methods are required such as opportunistic spinal quantitative computed tomography (QCT). However, it is unclear how to best calibrate these scans and correct for potential scanner drift of QCT when used for monitoring bone mineral density (BMD) changes. We compared gold standard simultaneous calibration with asynchronous calibration methods, assessing mid-term (12weeks) and long-term (1.5years) reproducibility of BMD measurements. Cortical and trabecular compartments of the European Spine Phantom were studied with ten different protocols including low dose and high resolution (HR)-modes. Based on weekly phantom data, we compared simultaneous calibration to asynchronous single (termed global) or monthly calibration. The accuracy was better for trabecular measurements than for cortical measurements for all calibration methods. Reproducibility was excellent for all methods and slightly better for asynchronous than for simultaneous calibration both for trabecular and cortical bone. For HR protocols, reproducibility was better than for low dose measurements. In trabecular compartments averaged HR-BMD remained stable for global (- 0.1%/year, ns) but not for simultaneous calibration (- 1.5%/year, p < 0.001). No significant drifts could be detected for averaged low dose BMD (- 0.9 to + 0.8%/year) for either calibration method. Our data suggest that with regard to precision and accuracy measurements with asynchronous calibration are suitable for vertebral BMD assessment (no contrast agents) in clinical practice. Regular (e.g., monthly) stability tests using a calibration phantom could assure long term stability of at least 1year.

Algorithm for extracting the normal cross-section parameters of multiple ball screw shaft ball tracks based on an optical micrometer measurement system

Abstract The accurate and efficient measurement of the normal cross-section parameters of multiple ball screw shaft spiral ball tracks are pivotal for ensuring quality control in ball track machining. Given the intricate nature of the ball screw shaft spiral ball track, balancing the accuracy and efficiency of the normal cross-section parameters measurement is a significant challenge. In this study, we present a method to calculate two core parameters, arc radius and contact angle. The method consists of four parts: the automatic axial cross-section separation method, the arc symmetric extraction method, the spiral transformation method, and the parameter algorithm based on the weighted least squares method. The experimental and simulation results validated the effectiveness of our method. Compared with the traditional axial measurement and transformation (AMT) method, our algorithm reduced the errors in arc radius and contact angle by up to 13.9 µm and 4.77°, respectively, and improved the accuracy by up to 78.34% and 85.04%. Compared with the traditional AMT methods and directly normal measurement method, the measurement time of our algorithm was reduced by up to 1565 s and 3475 s, respectively, and the efficiency was improved by up to 71.01% and 84.51%, respectively.

Strategies to enhance civic awareness for state defence in Indonesia: Measurement and benchmarking of the State Defence Index (SDI)

Countries employ various strategies to strengthen their soft power through education, public campaigns, mandatory service, and community involvement, essential for building a well-informed, prepared, and resilient citizenry. In Indonesia, the Civic Awareness for State Defence (CASD) program is designed to instil state defence awareness among citizens. This study introduces the Indonesia State Defence Index (SDI), a novel metric grounded in theoretical constructs such as national identity, nationalism, patriotism, and national pride. Differentiating from previous indices, our SDI employs advanced methodologies including Principal Component Analysis (PCA) and Structural Equation Modeling (SEM) to enhance measurement accuracy. Unlike earlier approaches that used traditional aggregation methods, our use of PCA ensures the reduction of dimensions for each state defence indicator, thereby guaranteeing that only the intended dimensions are measured. Utilising data from the State Defence Survey conducted by the Indonesian Ministry of Defence from 1 March to 26 June 2024, we aim to measure and benchmark SDI values across Indonesian regions, thereby elucidating the civic awareness profile in the context of state defence. The refined SDI provides critical insights for policymakers, highlighting regions that require focused interventions to bolster state defence preparedness.

Wildlife density estimation by distance sampling: A novel technique with movement compensation.

Estimates of population density are fundamental to wildlife conservation and management. Distance sampling from line transects is a widely used sample count method and is most often analysed using Distance software. However, this method has limited capabilities with mobile populations (e.g., birds), which tend to encounter an observer more often than immobile ones. This paper presents a novel distance sampling method based on a different set of models and assumptions, named WildlifeDensity after its associated software. It is based on mechanistic modelling of visual detections of individuals or groups according to radial distance from the observer or perpendicular distance from the transect line. It also compensates for population-observer relative movement to avoid the detection overestimates associated with highly mobile populations. The models are introduced in detail and then tested in three ways: 1) WildlifeDensity is applied to several 'benchmark' populations of known density and no-to-low mobility, 2) the movement compensation model is tested on two highly mobile songbird populations, and 3) a fairly difficult case is analysed: a low-density, highly mobile bird population in a forest habitat. The results show that 1) using either radial or perpendicular distance data from surveys of immobile populations, WildlifeDensity provides similar estimates (and errors) to Distance, with radial WildlifeDensity analysis appearing to be slightly better for surveys of low-mobility populations (kangaroos), 2) the movement compensation model effectively removes the correlation between observer speed and detection numbers, and 3) WildlifeDensity provides acceptable estimates where conventional Distance analysis overestimates density due to high movement. In summary, WildlifeDensity extends the capabilities of distance sampling by 1) compensating for movement, 2) not requiring complete detectability on the transect line and 3) supporting the use of radial distances, which simplifies fieldwork and increases measurement accuracy.

Improving quality control procedures for the measurement of total daily energy expenditure using the two-point doubly labeled water method.

The precision of the doubly labeled water (DLW) method is determined by the precision and accuracy of the isotopic measurements. Quality control (QC) procedures to mitigate sample variability require additional measurements if sample duplicates differ more than a factor of instrument precision. We explored the effect of widening QC ranges on total daily energy expenditure (TDEE) determined using the two-point sampling method. We screened DLW data from 121 individuals for instances where samples were analyzed more than twice using our existing QC criteria (±2.0 per mil [δ] for 2H and ±0.5 δ for 18O). We then applied wider QC ranges for accepting duplicate measures and recalculated TDEE. Widening the 2H QC range to ±10.0 δ in samples collected on the first day (most enriched) and to ±5.0 δ in samples collected on the final day (less enriched) produced almost identical mean TDEE compared to the originally calculated TDEE (2684 ± 508 vs. 2687 ± 512 kcal/day, p= 0.40). There was a strong correlation with the originally calculated TDEE (r2=0.97, p< 0.001). Expanding the 2H QC range to ±10.0 δ for samples collected on the first day and ±5.0 δ for samples collected on the final day provides similar mean TDEE results. These findings may help DLW labs optimize QC criteria and reduce analytical costs.

Cherry-Red Plasma Unraveling the Impact of PV-10 on Chemistry Assays

Abstract Background The accuracy of clinical laboratory measurements can be compromised by laboratory test interferences. PV-10 (Rose Bengal), a chemotherapy medication used in the treatment of metastatic melanoma, was observed to cause a cherry-red discoloration in plasma. This plasma color change, resembling hemolysis, raises serious concerns about potential interference in clinical laboratory tests. Our study focused on understanding the potential interference of PV-10, particularly the impact on the hemolysis index (H index) and various chemistry assays to ensure result accuracy in cancer treatment. Methods To investigate the potential interference of PV-10, pooled normal and high baseline bilirubin plasma samples were spiked with a gradient of PV-10 concentrations (0 to 22 µg/100µL). Samples were analyzed on Roche Cobas 8000 analyzer with H index and all the chemistry assays measured. Results The presence of PV-10 in plasma significantly increased the H index, in a dose-dependent manner. Specifically, the H index increased from 14 (control plasma) to 2643 at the highest PV-10 concentration (22 µg/100µL) in pooled plasma. Among all chemistry assays, most of them were not affected by PV-10. However, certain assays like IRON have dose dependent increase with PV-10 concentration. CHO2A (Total Cholesterol), TP (Total Protein), and TRIG (Triglycerides) have shown a consistent increase trend. In contrast, the DBILI values decreased with increasing PV-10 concentrations, from 6.7 mg/dL to 0.2 mg/dL. TBIL levels also demonstrated a gradual decline from 9.6 mg/dL to 8.4 mg/dL as PV-10 concentration increased in pooled high baseline bilirubin plasma. Conclusion This study provides insights into the potential interference of PV-10 in clinical chemistry assays. The elevated H index by PV-10 is not attributed to hemolysis. It is imperative for both laboratory professionals and care providers to recognize the implications of PV-10-induced plasma discoloration and its potential interference in laboratory tests.

Reduction in Optical Feedback Noise of Atomic Force Microscopy by High-Frequency Current Modulation

Introduction: With the advancement of technology, nanotechnology has emerged as a prominent research field. The Atomic Force Microscope (AFM) serves as a vital tool in nanoscience and technology, playing an indispensable role across various domains. Method: However, in the AFM photoelectric sensing system, the optical feedback noise from the beam deflection method can lead to inaccuracies in signal identification and analysis, impacting the accuracy and reliability of AFM measurements. To mitigate this interference, this study proposes a highfrequency current superposition system aimed at reducing optical feedback noise. By superimposing high-frequency currents, the semiconductor laser transitions from a single-mode to a multi-mode operational state, thereby altering its mode of operation and consequently reducing optical feedback noise during sensing. Initially, mathematical modeling and simulation analysis were conducted on the high-frequency current superposition noise reduction system to examine the impact of high-frequency current on the intensity noise of the semiconductor laser. Subsequently, the design of the high-frequency current superposition noise reduction system was outlined, encompassing the development of a constant current drive circuit, a voltage-controlled oscillator circuit, and a biasing circuit. Finally, the high-frequency current superposition noise reduction system underwent testing. Results: During the high-frequency current superposition noise reduction test, the system's Signal-to-Noise Ratio (SNR) increased from 15.57 dB to 17.81 dB, and the system's noise peak-to-peak value decreased from 8 mV to 6 mV. Analysis of the superposition frequency and noise reduction effect determined the optimal superposition frequency of the AFM photoelectric sensor system to be 400 MHz. Characterization experiments of the high-frequency superposition noise reduction system compared the clarity of Escherichia coli images before and after noise reduction. Conclusion: The aforementioned experimental results demonstrated that high-frequency current superposition is an effective noise reduction method capable of mitigating optical noise in the AFM photoelectric sensing system.

Calibration of TEROS 10 and TEROS 12 electromagnetic soil moisture sensors

AbstractThe TEROS 10 and TEROS 12 are widely used capacitance‐based sensors for measuring volumetric water content (), but few systematic studies of the measurement volume and accuracy of these sensors have been published. The objectives of this study were to (1) calibrate and validate these sensors in mineral soils, (2) determine the sensing volume of each sensor, and (3) evaluate the temperature sensitivity of the sensors. Both sensors were calibrated in the laboratory using columns of packed soil at multiple moisture levels from air‐dry to near saturation. Sensors were validated using additional laboratory and field measurements. The sensing volume was determined by quantifying the response of raw sensor outputs while increasing the level of oven‐dry sand, moist sand (0.100 cm3 cm−3), or water around the sensor in the radial and axial directions. Temperature sensitivity was tested in controlled conditions over a range of temperatures from 2°C to 40°C using encapsulated sensors in packed soil columns at constant . Linear calibration models resulted in mean absolute error ≤0.030 cm3 cm−3 for both sensors during laboratory and field validations. In moist sand, the sensing volume contributing 95% of the maximum sensor response was 439 cm3 for the TEROS 10 and 423 cm3 for the TEROS 12. Both sensors exhibited changes in of ≤0.02 cm3 cm−3 when subjected to a temperature change from 2°C to 40°C. For the soils considered here, both sensors demonstrated accuracy that is likely sufficient for a variety of agricultural and hydrological applications.

Multi-spectral radiation thermometry of space point targets based on spectral image pixel binning

The temperature characteristics of space point targets are essential indicators of their operational status and performance. To address the issue of significant temperature measurement errors in space point targets caused by low temperatures and a low imaging signal-to-noise ratio (SNR), we propose a mathematical model for multi-spectral radiation thermometry, derived from the principles of dual-band radiation thermometry. Furthermore, a multi-spectral image pixel binning method is introduced to enhance the SNR and minimize measurement errors. The experimental results indicate that the proposed multi-spectral radiation thermometry outperforms dual-band radiation thermometry. After merging 2 to 20 pixels, multi-spectral radiation thermometry in the 3.75–4.1 and 4.3–4.62 µm bands demonstrates an enhanced SNR and reduced temperature measurement errors. For a 378.15 K blackbody, the relative errors decrease from 1.52% and 2.19% to 0.26% and 0.74%, respectively, after merging six and eight pixels in the two different bands, compared to unmerged images. This method provides a valuable reference for developing techniques to enhance the SNR and improve temperature measurement accuracy for space point targets.

Phase contrast MRI with minimized background phase errors.

Phase contrast MRI (PC-MRI) is used clinically to measure velocities in the body, but systematic background phase errors caused by magnetic field imperfections corrupt the velocity measurements with offsets that limit clinical utility. This work aims to minimize systematic background phase errors in PC-MRI, thereby maximizing the accuracy of velocity measurements. The MRI scanner's background phase errors from eddy currents and mechanical oscillations were modeled using the gradient impulse response function (GIRF). Gradient waveforms were then numerically optimized using the GIRF to create pulse sequences that minimize the background phase errors. The pulse sequences were tested in a static phantom where the predicted response could be compared directly to the measured background velocity. The optimized acquisitions were then tested in human subjects, where flow rates and background errors were compared to conventional PC-MRI. When using the GIRF-optimized gradient waveforms, the predicted background phase was within 0.6 [95% CI = -3.4, 5.4] mm/s of the measured background phase in a static phantom. Excellent agreement was seen for in vivo blood flow values (flow rate agreement = 0.96), and the background phase was reduced by 78.8 18.7%. This work shows that using a GIRF to model the effects of magnetic field imperfections combined with numerically optimized gradient waveforms enables PC-MRI waveforms to be designed to produce a minimal background phase in the most time-efficient manner. The methodology could be adapted for other MRI sequences where similar magnetic field errors affect measurements.

A Critical Review on Soil Gas Analysis: Modern Technologies and Problems

In this review article, the main techniques for spectroscopic studies of gases in field conditions are considered. The issues related to the study of gas emissions from soils and the determination of their concentrations are analysed. The main types of spectroscopy used in portable devices for soil gas analysis, along with their design features and sampling approaches, are provided. Various studies aimed at optimising the operation of devices for analysing gases emitted from the soil, taking into account agronomic, agrochemical, and ecological specifics, are also presented. The effect of using different types of lasers and reflecting elements on the accuracy of optical measurements and the sensitivity to various substances in the gases is analysed.

Predictive role of peak VO2 for short- and long-term major adverse cardiac events in patients with high cardiovascular risk.

The objective of this study was to assess the accuracy of VO2 measurements in predicting long-term major adverse cardiac events (MACEs) in patients with high cardiovascular risk. Based on a10-year atherosclerotic cardiovascular disease risk score, 333 patients with high cardiovascular risk were included in this retrospective analysis. The study endpoint was MACEs, comprising all-cause mortality, cardiovascular mortality, non-fatal myocardial infarction or stroke, and coronary revascularization. The study cohort was divided into two groups according to the frequency of MACE occurrence. Measurements of VO2 were assessed for the prediction of MACEs. The best predictive accuracy for 1‑year MACEs was determined to be aVO2 max value of ≥ 20.3 mL/kg/min, with 60% specificity and 60% sensitivity (area under the curve [AUC]: 0.61; 95% confidence interval [CI]: 0.51-0.71; p < 0.001), and for 5‑year MACEs it was ≥ 19.9 mL/kg/min, with 69% specificity and 64% sensitivity (AUC: 0.69; 95% CI: 0.62-0.76; p < 0.001). Multivariable Cox regression analysis, after adjusting for univariable factors, showed that VO2 max was independently associated with both short- and long-term MACEs in patients at high cardiovascular risk (hazard ratio [HR]: 0.900, 95% CI: 0.858-0.943, p < 0.001). According to the results of this pilot study, VO2 max can predict both short- and long-term MACEs in patients at high cardiovascular risk.

Suppression of interference fringes in wavelength modulation spectroscopy based on convolutional neural networks

To mitigate interference fringes in wavelength modulated spectroscopy (WMS), we introduce a new filter based on convolutional neural networks (New CNNF). This filter effectively suppresses both high and low-frequency variations of interference fringes, including those with envelopes. In striving for comprehensive interference fringe suppression across the entire frequency spectrum, while accommodating diverse cavity length conditions, we confront the challenge of data sparsity. To address this, we introduce a pioneering methodology: finely segmenting the dataset through concentration column density normalization, thereby achieving notable noise reduction. Through the construction and training of the New CNNF model, it was found to exhibit superior performance compared to traditional filtering algorithms, particularly under low signal-to-noise ratio (SNR) conditions.Following processing with the novel convolutional neural network filters (New CNNF), the sample's signal-to-noise ratio (SNR) improved by 26.70 dB, increasing from the original −10.11 dB. When the etalon lengths were 2 cm and 100 cm, the goodness of fit between the predicted second harmonic signal amplitude by New CNNF and the corresponding label concentration reached 0.9995 and 0.9999, respectively. Experimental results demonstrate that New CNNF effectively suppresses high and low-frequency variations and enveloped interference fringes in the TDLAS-WMS system, thereby enhancing the accuracy and stability of methane concentration measurements. CH4 transitions at λ = 1.654 μm were selected to validate this approach. Our method shows promising application prospects and can be extended to the sensing of other gas molecules.

GNSS/IMU integrated navigation heading angle enhancement algorithm based on dual-antenna TDCP

In the integrated navigation system of Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU), attitude estimation, especially accurate estimation of heading angle, is particularly important for real-time monitoring of vehicle driving status. However, since IMU is divergent in the altitude channel, its error will gradually accumulate if it is not accurately constrained. Therefore, the estimation accuracy of heading angle is insufficient in vehicle-mounted applications where the heading angle changes frequently. In order to solve the problem of poor navigation attitude estimation accuracy in the loose combination of traditional GNSS and IMU, this paper proposes a GNSS/IMU integrated navigation heading angle enhancement algorithm based on dual-antenna epoch carrier phase difference (TDCP). This method solves the vehicle heading angle through dual-antenna TDCP to increase the input dimension of the integrated navigation filter fusion observation value, and uses Hatch filtering and anti-error adaptive filtering to improve the observation domain pseudorange accuracy and GNSS/IMU integrated navigation positioning and attitude determination performance respectively. Experimental results show that compared with the traditional GNSS/IMU integrated navigation method, the proposed algorithm improves the positioning and speed measurement accuracy in the three-dimensional direction by and respectively 22.12%, 41.27%and the vehicle heading angle accuracy is improved 46.29%.