Weighted Least Squared Approach to Fault Detection and Isolation for GPS Integrity Monitoring

Reliability of a global navigation satellite system is one of great importance for global navigation purposes. Therefore, an integrity monitoring system is an inseparable part of aviation navigation system. Failures or faults due to malfunctions in the systems should be detected to keep the integrity of the system intact. In order to solve the problem that least squares method detects and isolates a satellite fault for GPS integrity monitoring, in this paper, a weighted least squares algorithm is proposed for satellite fault detection and isolation. The algorithm adopts the diagonal elements of the covariance matrix of GPS measurement equation as the weighted factor. Firstly, the weighted least squares approach for satellite fault detection establishes the test statistic by the sum of the squares of the pseudo-range residuals of each satellite for GPS. Then, the detection threshold is obtained by the false alarm rate of the fault detection, probability density function and visiable satellite number.The effectiveness of the proposed approach is illustrated in a problem of GPS (Global Positioning System) autonomous integrity monitoring system. Through the real raw measured GPS data，based on least squares RAIM method and the weighted least squares RAIM approach, the performance of the two algorithms is compared. The results show that the proposed RAIM approach is superior to the least squares RAIM algorithm in the sensitivity of fault detection and fault isolation performance for GPS integrity monitoring

Electric quadrupole second harmonic generation revealing dual magnetic orders in a magnetic Weyl semimetal

Broken symmetries and electronic topology are nicely manifested together in the second order nonlinear optical responses from topologically nontrivial materials. While second order nonlinear optical effects from the electric dipole (ED) contribution have been extensively explored in polar Weyl semimetals (WSMs) with broken spatial inversion (SI) symmetry, they are rarely studied in centrosymmetric magnetic WSMs with broken time reversal (TR) symmetry due to complete suppression of the ED contribution. Here, we report experimental demonstration of optical second harmonic generation (SHG) in a magnetic WSM Co$_{3}$Sn$_{2}$S$_{2}$ from the electric quadrupole (EQ) contribution. By tracking the temperature dependence of the rotation anisotropy (RA) of SHG, we capture two magnetic phase transitions, with both the SHG intensity increasing and its RA pattern rotating at $T_{C,1}$=175K and $T_{C,2}$=120K subsequently. The fitted critical exponents for the SHG intensity and RA orientation near $T_{C,1}$ and $T_{C,2}$ suggest that the magnetic phase at $T_{C,1}$ is a 3D Ising-type out-of-plane ferromagnetism while the other at $T_{C,2}$ is a 3D XY-type all-in-all-out in-plane antiferromagnetism. Our results show the success of detection and exploration of EQ SHG in a centrosymmetric magnetic WSM, and hence open the pathway towards the future investigation of its tie to the band topology.Comment: 19 pages, 4 figure

Dynamic radiomics for predicting the efficacy of antiangiogenic therapy in colorectal liver metastases

Background and objectiveFor patients with advanced colorectal liver metastases (CRLMs) receiving first-line anti-angiogenic therapy, an accurate, rapid and noninvasive indicator is urgently needed to predict its efficacy. In previous studies, dynamic radiomics predicted more accurately than conventional radiomics. Therefore, it is necessary to establish a dynamic radiomics efficacy prediction model for antiangiogenic therapy to provide more accurate guidance for clinical diagnosis and treatment decisions.MethodsIn this study, we use dynamic radiomics feature extraction method that extracts static features using tomographic images of different sequences of the same patient and then quantifies them into new dynamic features for the prediction of treatmentefficacy. In this retrospective study, we collected 76 patients who were diagnosed with unresectable CRLM between June 2016 and June 2021 in the First Hospital of China Medical University. All patients received standard treatment regimen of bevacizumab combined with chemotherapy in the first-line treatment, and contrast-enhanced abdominal CT (CECT) scans were performed before treatment. Patients with multiple primary lesions as well as missing clinical or imaging information were excluded. Area Under Curve (AUC) and accuracy were used to evaluate model performance. Regions of interest (ROIs) were independently delineated by two radiologists to extract radiomics features. Three machine learning algorithms were used to construct two scores based on the best response and progression-free survival (PFS).ResultsFor the task that predict the best response patients will achieve after treatment, by using ROC curve analysis, it can be seen that the relative change rate (RCR) feature performed best among all features and best in linear discriminantanalysis (AUC: 0.945 and accuracy: 0.855). In terms of predicting PFS, the Kaplan–Meier plots suggested that the score constructed using the RCR features could significantly distinguish patients with good response from those with poor response (Two-sided P<0.0001 for survival analysis).ConclusionsThis study demonstrates that the application of dynamic radiomics features can better predict the efficacy of CRLM patients receiving antiangiogenic therapy compared with conventional radiomics features. It allows patients to have a more accurate assessment of the effect of medical treatment before receiving treatment, and this assessment method is noninvasive, rapid, and less expensive. Dynamic radiomics model provides stronger guidance for the selection of treatment options and precision medicine