This paper studies the range equation modeling of a ground moving target for multichannel medium-Earth-orbit (MEO) synthetic aperture radar (SAR) ground moving target indication (GMTI), an issue which is challenging to tackle due to the non-linear motion of the radar platform and the Earth rotation. In the paper, the coordinates of the multichannel MEO SAR and the target, as well as the target’s range equation with respect to each channel, are developed. Moreover, an expression of concise form is derived for the target’s quadratic-approximated range equation, which will benefit the design of GMTI methods. Furthermore, theoretical analyses are conducted to reveal the dependency between the accuracy of the quadratic-approximated range equation and the parameters of the radar and the target. Numerical simulations are carried out to investigate the influence of the quadratic approximation of the range equation on the GMTI performance and to figure out the quadratic-approximated range equation’s scope of application.

This paper studies the imaging of a ground moving target with airborne circular stripmap synthetic aperture radar (CSSAR). First, the range equation of a target moving with accelerations is developed. Then, a new range model of high accuracy is proposed, since the commonly used second-order Taylor-approximated range model is inaccurate when the azimuth resolution is relatively high or the target moves with accelerations. The proposed range model also makes it easy to derive an accurate analytical expression for the target’s 2-D spectrum. Third, based on the proposed range model, the target’s 2-D spectrum is derived and an efficient imaging method is proposed. The proposed imaging method implements focusing via a phase multiplication in the 2-D frequency domain and utilizes the genetic algorithm to accomplish an efficient search of the parameters of the proposed range model. Finally, numerical experiments are conducted to validate the proposed range model and the proposed imaging method.

Medium-Earth-orbit (MEO) synthetic aperture radar (SAR) has the advantages of short revisit time and wide coverage, and thus is a potential tool for implementing ground moving target indication (GMTI) tasks. In the paper, aiming at MEO SAR’s problems of low signal-to-noise ratio and limited computation resource, an efficient imaging method is proposed for MEO multichannel SAR-GMTI systems with relatively low resolution. The proposed imaging method is designed with the consideration of both static scenes and ground moving targets, and it can simultaneously correct the range cell migrations of static scenes and multiple moving targets of no Doppler ambiguity. It needs only four Fourier transforms and twice phase multiplications, and thus is computationally efficient. Moreover, moving targets’ signal characteristics, including the azimuth and range displacements and along-track interferometric phase, in the SAR image obtained by the proposed imaging method are figured out. Experimental results validate the proposed imaging method and the theoretical analyses.

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(1) Background: There are few studies on people at high risk for clinical pancreatic cancer (PC). We aimed to explore the risk factors of PC and establish a scale for identifying high-risk populations of clinical PC. (2) Methods: We conducted a matched case-control study, retrospectively collecting demographic data and common clinical indicators from all subjects. Logistic regression was used to explore the risk factors of PC. Based on these factors, we created a high-risk population rating scale, which showed a higher diagnostic value. (3) Results: 385 cases and 428 controls were finally enrolled in our study. Multivariate analysis showed that body mass index (BMI) below 18.5 kg/m2 (OR 5.944, 95%CI: 1.759~20.084), smoking (OR 2.745, 95%CI: 1.555~4.844), new-onset diabetes (OR 5.239, 95%CI: 2.091~13.125), low high-density lipoprotein cholesterol (HDL-C) levels (OR 1.790, 95%CI: 1.044~3.069), and carbohydrate antigen 19-9 (CA19-9) levels no less than 35 U/mL (OR 160.328, 95%CI: 83.392~308.243) were associated with an increased risk of PC, whereas high total cholesterol (TC) levels were related to a lower risk of PC (OR 0.392, 95%CI: 0.211~0.730). The high-risk population scale, whose area under the receiver operating curve reached 0.948 (p < 0.001), showed a greater clinical diagnostic value. (4) Conclusions: Smoking history, new-onset diabetes, BMI, TC, HDL-C, and CA19-9 levels were associated with the risk of PC. The high-risk population rating scale might be used for early clinical PC screening.