A calibration method of USBL installation error based on attitude determination

The Ultra-short baseline (USBL) positioning system has important application in the positioning of underwater vehicles. The installation error angle of the USBL positioning system has an important influence on the positioning accuracy of USBL system. The traditional calibration methods have limited estimation accuracy for installation error angles and have high route requirements. To solve the above problems, a calibration method of installation error angle based on attitude determination is proposed in this paper. When strapdown inertial navigation system (SINS) and USBL are fixed together in the application process, the installation error angle of USBL is fixed and unchanged. Then the calibration of installation error angle can be accomplished with the idea of attitude determination. The vector observation model based on the installation error angle matrix is established first. Observation vectors are obtained by the relative position of transponders in the USBL coordinate frame. The reference vector is calculated by position of transponder, position and attitude of SINS and lever arm between SINS and USBL. By constructing the observation vectors and the reference vectors, the proposed method can calibrate the installation error angle of SINS and USBL in real time. The advantages of the proposed method are that it has no specific requirements for the calibration route and can calibrate the installation error angle in real time with high accuracy. In order to verify the performance of the proposed algorithm, simulation experiment and field experiment are carried out in this paper. The results of simulation experiment and field experiment show that the proposed method can give the estimated installation error angle of USBL in real time, and the estimated result is the best among several methods. The proposed method can not only achieve the calibration of the installation error angle in circular trajectory, but also in straight trajectory

Streptococcus suis Sequence Type 7 Outbreak, Sichuan, China

An outbreak of Streptococcus suis serotype 2 emerged in the summer of 2005 in Sichuan Province, and sporadic infections occurred in 4 additional provinces of China. In total, 99 S. suis strains were isolated and analyzed in this study: 88 isolates from human patients and 11 from diseased pigs. We defined 98 of 99 isolates as pulse type I by using pulsed-field gel electrophoresis analysis of SmaI-digested chromosomal DNA. Furthermore, multilocus sequence typing classified 97 of 98 members of the pulse type I in the same sequence type (ST), ST-7. Isolates of ST-7 were more toxic to peripheral blood mononuclear cells than ST-1 strains. S. suis ST-7, the causative agent, was a single-locus variant of ST-1 with increased virulence. These findings strongly suggest that ST-7 is an emerging, highly virulent S. suis clone that caused the largest S. suis outbreak ever described

Global climate forcing of aerosols embodied in international trade

International trade separates regions consuming goods and services from regions where goods and related aerosol pollution are produced. Yet the role of trade in aerosol climate forcing attributed to different regions has never been quantified. Here, we contrast the direct radiative forcing of aerosols related to regions’ consumption of goods and services against the forcing due to emissions produced in each region. Aerosols assessed include black carbon, primary organic aerosol, and secondary inorganic aerosols, including sulfate, nitrate and ammonium. We find that global aerosol radiative forcing due to emissions produced in East Asia is much stronger than the forcing related to goods and services ultimately consumed in that region because of its large net export of emissions-intensive goods. The opposite is true for net importers such as Western Europe and North America: global radiative forcing related to consumption is much greater than the forcing due to emissions produced in these regions. Overall, trade is associated with a shift of radiative forcing from net importing to net exporting regions. Compared to greenhouse gases such as carbon dioxide, the short atmospheric lifetimes of aerosols cause large localized differences between consumption- and production-related radiative forcing. International efforts to reduce emissions in the exporting countries will help alleviate trade-related climate and health impacts of aerosols while lowering global emissions

A Coarse-Alignment Method Based on the Optimal-REQUEST Algorithm

In this paper, we proposed a coarse-alignment method for strapdown inertial navigation systems based on attitude determination. The observation vectors, which can be obtained by inertial sensors, usually contain various types of noise, which affects the convergence rate and the accuracy of the coarse alignment. Given this drawback, we studied an attitude-determination method named optimal-REQUEST, which is an optimal method for attitude determination that is based on observation vectors. Compared to the traditional attitude-determination method, the filtering gain of the proposed method is tuned autonomously; thus, the convergence rate of the attitude determination is faster than in the traditional method. Within the proposed method, we developed an iterative method for determining the attitude quaternion. We carried out simulation and turntable tests, which we used to validate the proposed method’s performance. The experiment’s results showed that the convergence rate of the proposed optimal-REQUEST algorithm is faster and that the coarse alignment’s stability is higher. In summary, the proposed method has a high applicability to practical systems

A Novel Hybrid of a Fading Filter and an Extreme Learning Machine for GPS/INS during GPS Outages

In this paper, a novel algorithm based on the combination of a fading filter (FF) and an extreme learning machine (ELM) is presented for Global Positioning System/Inertial Navigation System (GPS/INS) integrated navigation systems. In order to increase the filtering accuracy of the model, a variable fading factor fading filter based on the fading factor is proposed. It adjusts the fading factor by the ratio of the estimated covariance before and after the moment which proves to have excellent performance in our experiment. An extreme learning machine based on a Fourier orthogonal basis function is introduced that considers the deterioration of the accuracy of the navigation system during GPS outages and has a higher positioning accuracy and faster learning speed than the typical neural network learning algorithm. In the end, a simulation and real road test are performed to verify the effectiveness of this algorithm. The results show that the accuracy of the fading filter based on a variable fading factor is clearly improved, and the proposed improved ELM algorithm can provide position corrections during GPS outages more effectively than the other algorithms (ELM and the traditional radial basis function neural network)

A Novel Method to Estimate the Sea State for Recycling Work on the Sea Surface

The recycling of marine exploration equipment after it has surfaced is greatly affected by sea state. In order to estimate the sea state in real time, this paper proposes a method for measuring wave elevation, which modifies the integrated results of GNSS/SINS in the up direction by virtual horizontal lines to extract wave fluctuation information. From these wave information, the significant wave heights (SWH) can be calculated as the only input parameter of P-M spectrum, and a series of wave height data can be further simulated. When the GNSS is interrupted due to severe sea state, the simulated data can be integrated with the SINS to deal with the data distortion problem. The simulation results show that the application of wave spectrum in the GNSS intermittent situation has obvious improvement effect and important significance

Coarse Alignment Technology on Moving base for SINS Based on the Improved Quaternion Filter Algorithm

Initial alignment of the strapdown inertial navigation system (SINS) is intended to determine the initial attitude matrix in a short time with certain accuracy. The alignment accuracy of the quaternion filter algorithm is remarkable, but the convergence rate is slow. To solve this problem, this paper proposes an improved quaternion filter algorithm for faster initial alignment based on the error model of the quaternion filter algorithm. The improved quaternion filter algorithm constructs the K matrix based on the principle of optimal quaternion algorithm, and rebuilds the measurement model by containing acceleration and velocity errors to make the convergence rate faster. A doppler velocity log (DVL) provides the reference velocity for the improved quaternion filter alignment algorithm. In order to demonstrate the performance of the improved quaternion filter algorithm in the field, a turntable experiment and a vehicle test are carried out. The results of the experiments show that the convergence rate of the proposed improved quaternion filter is faster than that of the tradition quaternion filter algorithm. In addition, the improved quaternion filter algorithm also demonstrates advantages in terms of correctness, effectiveness, and practicability

Arctic sea-ice loss is projected to lead to more frequent strong El Niño events.

Arctic sea ice has decreased substantially and is projected to reach a seasonally ice-free state in the coming decades. Little is known about whether dwindling Arctic sea ice is capable of influencing the occurrence of strong El Niño, a prominent mode of climate variability with global impacts. Based on time slice coupled model experiments, here we show that no significant change in the occurrence of strong El Niño is found in response to moderate Arctic sea-ice loss that is consistent with satellite observations to date. However, as the ice loss continues and the Arctic becomes seasonally ice-free, the frequency of strong El Niño events increases by more than one third, as defined by gradient-based indices that remove mean tropical Pacific warming induced by the seasonally ice-free Arctic. By comparing our time slice experiments with greenhouse warming experiments, we conclude that at least 37-48% of the increase of strong El Niño near the end of the 21st century is associated specifically with Arctic sea-ice loss. Further separation of Arctic sea-ice loss and greenhouse gas forcing only experiments implies that the seasonally ice-free Arctic might play a key role in driving significantly more frequent strong El Niño events

Modeling the effects of global cooling and the Tethyan Seaway closure on North African and South Asian climates during the Middle Miocene Climate Transition

Highlights • Closure of the Tethyan Seaway led to precipitation increase in South Asia but decrease in North Africa. • Closure of the Tethyan Seaway led to enhanced moisture transport from North Africa to South Asia. • Global cooling led to precipitation decrease in North Africa and South Asia during the MMCT. Abstract The Middle Miocene was a period of prominent climatic change, marked by the Mid-Miocene Climatic Optimum (MMCO) and the subsequent global cooling due to a decline of the atmospheric CO2 concentrations (pCO2). In addition to this, the closure of the Tethyan Seaway driven by the Arab-Eurasia collision also had an important effect on the paleoclimatic changes during this period. In this study, we use the Community Earth System Model 1.2.2 (CESM 1.2.2) to simulate the effects of global cooling (i.e. pCO2 decline) and the closure of the Tethyan Seaway on the North African and South Asian climates. Our results show that the global cooling led to a precipitation decrease over both North Africa and South Asia, whereas the closure of the Tethyan Seaway resulted in a precipitation decrease over North Africa but an increase over South Asia. The opposite effects over North Africa and South Asia are due to an increased moisture transport from North Africa to South Asia induced by stronger summer atmospheric circulation when the Tethyan Seaway is closed. We further show that the reconstructed records of drying conditions over North Africa during the warming period from the late Early Miocene to the early Middle Miocene from previous studies can be partly explained by the narrowing of the Tethyan Seaway and its climatic continuing deterioration due to the subsequent final closure and global cooling. Both are precursory conditions for the formation of the Sahara desert. The stronger South Asian monsoon during the Middle Miocene transient cooling period found in previous studies can be partially attributed to the final closure of the Tethyan Seaway

Tillage depth regulation system via depth measurement feedback and composite sliding mode control: A field comparison validation study

The existing methodologies employed for the quantification and regulation of tractor’s tillage depth present considerable shortcomings, primarily characterized by their low accuracy and poor disturbance rejection proficiency in complex agricultural terrains. In this study, we present a sophisticated feedback control strategy designed to mitigate these challenges. Our innovative approach hinges on calculating tillage depth from the alignment of the tractor’s hydraulic lifting arm, achieved by employing a mechanical angle sensor. This sensor adeptly gages the angle of the lifting arm, aligning it with the tillage angle of the pull rod and the implement’s angle, resulting in a robust relational model correlating the lifting arm angle with the tillage depth. This pioneering method amalgamates the accuracy inherent in the static model, derived from the tillage angle-based depth measurement, with the dynamic stability afforded by the mechanical ascertainment of the lifting arm angle. In conjunction, we introduce a Hybrid Extended State Observer-Based Backstepping Sliding Mode Controller (HESO-BacksteppingSMC). The HESO is instrumental in estimating unmeasured state variables and lumped disturbances, utilizing the system’s output feedback signal. Our control frame component capitalizes on the fast power-reaching law to yield a continuously smooth control signal, effectively eradicating the conventional chattering phenomenon inherent in controllers and amplifying its functional applicability. Theoretical evaluations affirm the uniformly and ultimately bounded stability of the errors associated with our proposed observer and controller, underscoring their robustness. The superior performance of our proposed tillage depth measurement and control methodology has been corroborated through a series of comprehensive simulation and field plowing trials, attesting to its precision and reliability in complex agricultural settings