Automatic recognition of radar signals based on time-frequency image shape character

Radar signal recognition is one of the key technologies of modern electronic surveillance systems. Time-frequency image provides a new way for recognizing the radar signal. In this paper, a series of image processing methods containing image enhancement, image threshold binarization and mathematical morphology is utilized to extract the shape character of smoothed pseudo wigner-ville time-frequency distribution of radar signal. And then the identification of radar signal is realized by the character. Simulation results of eight kinds of typical radar signal demonstrate that when signal noise ratio (SNR) is greater than -3 dB, the Legendre moments shape character of the time-frequency image is very stable. Moreover, the recognition rate by the character is more than 90 per cent except for the FRANK code signal when SNR > -3 dB. Test also show that the proposed method can effectively recognize radar signal with less character dimension through compared with exitsing algorithms.Defence Science Journal, 2013, 63(3), pp.308-314, DOI:http://dx.doi.org/10.14429/dsj.63.240

Artificial disc and vertebra system: a novel motion preservation device for cervical spinal disease after vertebral corpectomy

OBJECTIVE: To determine the range of motion and stability of the human cadaveric cervical spine after the implantation of a novel artificial disc and vertebra system by comparing an intact group and a fusion group. METHODS: Biomechanical tests were conducted on 18 human cadaveric cervical specimens. The range of motion and the stability index range of motion were measured to study the function and stability of the artificial disc and vertebra system of the intact group compared with the fusion group. RESULTS: In all cases, the artificial disc and vertebra system maintained intervertebral motion and reestablished vertebral height at the operative level. After its implantation, there was no significant difference in the range of motion (ROM) of C3-7 in all directions in the non-fusion group compared with the intact group (p>;0.05), but significant differences were detected in flexion, extension and axial rotation compared with the fusion group (

Analysis of preoperative and postoperative depression and anxiety in patients with osteochondral lesions of the talus

PurposeThis study aims to investigate the psychological status of patients with Hepple V osteochondral lesions of the talus (OLT) and evaluate the effect of autologous osteoperiosteal transplantation (AOPT) on their psychological well-being.MethodsFifty patients with Hepple V OLT who underwent AOPT at the Comprehensive Foot and Ankle Surgery Ward of Xi’an Honghui Hospital from November 2021 to May 2023 were included in this study. The patients were divided into two groups based on the presence or absence of preoperative symptoms of anxiety/depression. Group A comprised patients with preoperative symptoms, while Group B included patients without such symptoms. Preoperative and final follow-up assessments included the Hospital Anxiety and Depression Scale for evaluating anxiety and depression, the visual analogue scale for pain assessment, and the American Orthopaedic Foot and Ankle Society scores for assessing ankle and hindfoot function.ResultsAmong the 50 Hepple V OLT patients who obtained complete follow-up, twenty-four had preoperative symptoms of anxiety/depression, with an incidence rate of up to 48%. Patients in Groups A and B showed significant improvement in all evaluation indexes after AOPT compared to the preoperative period, but the overall prognosis of Group A was poorer than that of Group B.ConclusionAOPT can effectively improve patients’ pain, functional activities, and psychological status, and there is a significant correlation between patients’ preoperative psychological status and prognosis

Study of Neutron Radiation Field at the First Radioactive ion Beam Line in Lanzhou

International audienceThe first Radioactive Ion Beam Line in Lanzhou was a projectile fragment separator located in the HIRFL. The process of production and separation of radioactive ion beams can induce a strong and complex radiation field. The neutron dose equivalent rates were measured in four positions with a 70 MeV/u ^40Ar^18+ beam. The results were compared with that simulated by the FLUKA code. New shielding walls were installed to reduce the neutron background for spectroscopy measurement in the experimental terminal. In addition, the induced radioactivity of accelerator components and corresponding residual dose rates were analyzed for the radiation safety of accelerator workers. The airborne radioactivity as well as occupational exposure due to immersion in and inhalation of activated air were also estimated. This work aims to provide a valuable experience for the radiation study in the future fragment separator HFRS at HIAF

Application of Multistep Inversion Method for Online Monitoring Aerosol Particle Size Distribution and Aerosol Concentration

Aerosol concentration in the flow is usually time varying, and aerosol particle size distribution (PSD) is considered to be unchanged, which increases the difficulty of the measurement of aerosol PSD and concentration online. To solve these problems, a kind of multistep inversion method based on the angular light-scattering (ALS) signals is proposed. First, the aerosol PSD is estimated using shuffled frog-leaping algorithms (SFLAs) from relative ALS signals. Then, with aerosol PSD as priori information, the aerosol concentration is obtained by the Kalman filter (KF) algorithm, widely used in the real-time control system of industrial facilities for its ability of fast predictions. The result reveals that the performance of the improved SFLA is better than that of the original SFLA in solving the aerosol PSD. Moreover, in studying the aerosol concentration, more accurate results can be obtained with larger standard deviation of process noise or smaller standard deviation of measurement noise, while decreasing sampling time interval can improve the accuracy of retrieval results and reduce time delay to a certain degree. So, to improve retrieval accuracy, the noise should be controlled, and appropriate sampling time interval should be selected. All the numerical simulations confirm that the methodology provides effective and reliable results in real-time estimating

Few-Shot Building Footprint Shape Classification with Relation Network

Buildings are important entity objects of cities, and the classification of building shapes plays an indispensable role in the cognition and planning of the urban structure. In recent years, some deep learning methods have been proposed for recognizing the shapes of building footprints in modern electronic maps. Furthermore, their performance depends on enough labeled samples for each class of building footprints. However, it is impractical to label enough samples for each type of building footprint shapes. Therefore, the deep learning methods using few labeled samples are more preferable to recognize and classify the building footprint shapes. In this paper, we propose a relation network based method for the recognization of building footprint shapes with few labeled samples. Relation network, composed of embedding module and relation module, is a metric based few-shot method which aims to learn a generalized metric function and predict the types of the new samples according to their relation with the prototypes of these few labeled samples. To better extract the shape features of the building footprints in the form of vector polygons, we have taken the TriangleConv embedding module to act as the embedding module of the relation network. We validate the effectiveness of our method based on a building footprint dataset with 10 typical shapes and compare it with three classical few-shot learning methods in accuracy. The results show that our method performs better for the classification of building footprint shapes with few labeled samples. For example, the accuracy reached 89.40% for the 2-way 5-shot classification task where there are only two classes of samples in the task and five labeled samples for each class

Angle-Only Cooperative Orbit Determination Considering Attitude Uncertainty

In this paper, a novel concept for cooperative orbit determination (OD) using inter-spacecraft angle-only measurements is proposed. Different from the conventional cooperative OD that only estimates orbit states, the attitude of the observer spacecraft is considered by incorporating the attitude into the estimated vector. The observability of a two-spacecraft system is analyzed based on the observability matrix. Observability analysis reveals that inter-spacecraft angle-only measurements are inadequate to estimate both the attitude and the orbit states in two-body dynamics. The observability of the two-spacecraft system can be improved by considering high-order gravitational perturbation or executing an attitude maneuver on the observer spacecraft. This is the first time that we present the observability analysis and orbit estimation results for a two-spacecraft system considering attitude uncertainty for the observer. Finally, simulation results demonstrate the effectiveness of the proposed method. The results in this paper can be potentially useful for autonomous managements of a spacecraft constellation and formation