No abstract

Multi-sensor integrated positioning technique that combines complementary features of the global positioning system (GPS) and inertial navigation system (INS) for navigation in challenging urban environments has been a hot research area. A variety of algorithms have been proposed over the past two decades for this well-studied field. However, with the increasing demands of seamless positioning, traditional GPS/INS integrated technique faces rigorous challenges, especially in GPS-denied environment, where traditional techniques cannot be applied directly. To improve the precision and robustness of the navigation system, a novel hybrid GPS/INS/Doppler velocity log (DVL) positioning method is proposed, which introduces DVL as the reference information to assist the GPS module to correct the divergence error of INS. A new robust adaptive federated strong tracking Kalman filter (RAFSTKF) algorithm is also presented for data fusion, which has the advantage of robustness with respect to the uncertainty of the system model. Meanwhile, we introduce the least square principle and adaptively adjust information sharing factors to obtain the optimal estimation, which can improve the reliability of the overall system. The theoretical analysis and simulation results demonstrate the effectiveness of the proposed hybrid GPS/INS/DVL positioning method based on RAFSTKF. In addition, the tracking performance of the proposed method outperforms that of traditional federated Kalman filter. INDEX TERMS Localization, target tracking, positioning, hybrid navigation, Kalman filter, weighted least square, federated strong tracking filter. I. INTRODUCION Many existing and perspective technologies of navigation and location systems would benefit notably from the ability to position accurately and reliably in challenging environments [1]-[6]. Recently, inertial navigation systems (INS) provide users with position, velocity, and attitude (PVA) information with high resolution independent of the vehicle platform [7], [8]. However the PVA information provided by INS can only maintain reliable precision for short time limited by the fact that the INS navigation error will accumulate The associate editor coordinating the review of this manuscript and approving it for publication was Shuai Han.

Background Valvular dysfunction is a common complication in patients with bicuspid aortic valves (BAV). The aim of this study was to determine the relationship between BAV morphology patterns and valve dysfunction. Methods We searched the PubMed, The Cochrane Library, Web of Science, and CNKI until May 31, 2020, to identify all studies investigating the morphology of BAV and valvular dysfunction, and data were extracted according to the Preferred Reporting Items for Systematic reviews and Meta‐Analyses (PRISMA). Data were analyzed using Stata 15.1 software. The additional characteristics (gender, mean age) were collected to perform a meta‐regression analysis. Results Thirteen studies on BAV‐RL (n = 2002) versus BAV‐RN (n = 1254) and raphe (n = 4001) versus without raphe (n = 673) were included. The BAV‐RL patients showed a higher incidence of aortic regurgitation than BAV‐RN patients (OR = 1.46; 95% CI: 1.12 to 1.90, p = .005), while the BAV‐RL patients showed a lower incidence of aortic stenosis than BAV‐RN patients (OR = 0.66, 95% CI: 0.58 to 0.76, p = .000); BAV patients with raphe presents a higher incidence of aortic regurgitation than those without raphe (OR = 1.95, 95% CI: 1.12–3.39, p = .017). No differences were found between raphe and without raphe group in the incidence of aortic stenosis (OR = 0.97, 95% CI: 0.53 to 1.76, p = .907). Mean age and gender had no influence on observed differences. Conclusions Our results confirmed a relationship between different BAV phenotypes and aortic valve dysfunction. BAV‐RL and BAV with raphe are more likely to develop aortic regurgitation, while patients with BAV‐RN present a higher possibility to develop aortic stenosis.

No abstract