Search Results (6)

In this paper, we present a tailored shooting and bouncing ray (SBR) method for the fast solution of electromagnetic (EM) scattering from a moving target. And, the micro-Doppler features of the moving target are investigated using a time-frequency analysis technique. In our method, a dynamic spatial division technique is employed to accelerate facet information processing and ray-tracing progress of the moving target. At first, the two coordinate systems are established, which are the geodetic coordinate system (GCS) and the local coordinate system (LCS). In GCS, the target is moving with translation and rotation. The dynamic spatial division is established in LCS to store the facet information and remain relatively stationary to the target. In comparison with the traditional SBR method, this technique avoids repetitive spatial division at each moment in the GCS. Then, ray tracing is performed to find the illuminated facets in the LCS. Finally, the scattering field and the phase compensation are computed in the GCS. In numerical simulations, the verification and computation efficiency comparison are provided using our method and other solutions (MLFMM, RL-GO, and traditional SBR). Moreover, the micro-Doppler features are extracted and analyzed using the time-frequency analysis technique, which includes the precession and spin of the missile, and the rotation of the aircraft. Meanwhile, the micro-Doppler spectra of the target is also compared with the theoretical Doppler of equivalent strong scattering points, which are obtained using the instantaneous high-resolution range profile (HRRP). Full article

Inverse synthetic aperture radar (ISAR) imaging can be improved by processing Range-Instantaneous Doppler (RID) images, according to a method proposed in this paper that uses neural networks. ISAR is a significant imaging technique for moving targets. However, scatterers span across several range bins and Doppler bins while imaging a moving target over a large accumulated angle. Defocusing consequently occurs in the results produced by the conventional Range Doppler Algorithm (RDA). Defocusing can be solved with the time-frequency analysis (TFA) method, but the resolution performance is reduced. The proposed method provides the neural network with more details by using a string of RID frames of images as input. As a consequence, it produces better resolution and avoids defocusing. Furthermore, we have developed a positional encoding method that precisely represents pixel positions while taking into account the features of ISAR images. To address the issue of an imbalance in the ratio of pixel count between target and non-target areas in ISAR images, we additionally use the idea of Focal Loss to improve the Mean Squared Error (MSE). We conduct experiments with simulated data of point targets and full-wave simulated data produced by FEKO to assess the efficacy of the proposed approach. The experimental results demonstrate that our approach can improve resolution while preventing defocusing in ISAR images. Full article

Instantaneous frequency measurement devices are useful for conducting extremely fast measurements of the current frequency value of microwave signals, even if their duration is extremely short. This paper presents the principle of determination of temporary values of the microwave signal phase and frequency using interferometer techniques, based on passive microwave components. Additionally, the structures and results of measurements of two novel versions of integrated microwave correlators for microwave frequency discriminators, made on a single printed circuit board, are shown. Three Wilkinson-type, single-stage power dividers, and two rat-race hybrids create the developed correlators. The developed devices were designed to work over a wide frequency range, i.e., of 1.6–3.1 GHz, and can be used to monitor Wi-Fi devices as well as pulse and CW radar systems operating in the S band. They can also be applied in passive radars and active Doppler radars. The view of the printed circuits boards and results of measurements are presented. Recommendations for improving the accuracy of measurement are proposed. Full article

The most commonly used method of fetal monitoring is based on heart activity analysis. Computer-aided fetal monitoring system enables extraction of clinically important information hidden for visual interpretation—the instantaneous fetal heart rate (FHR) variability. Today’s fetal monitors are based on monitoring of mechanical activity of the fetal heart by means of Doppler ultrasound technique. The FHR is determined using autocorrelation methods, and thus it has a form of evenly spaced—every 250 ms—instantaneous measurements, where some of which are incorrect or duplicate. The parameters describing a beat-to-beat FHR variability calculated from such a signal show significant errors. The aim of our research was to develop new analysis methods that will both improve an accuracy of the FHR determination and provide FHR representation as time series of events. The study was carried out on simultaneously recorded (during labor) Doppler ultrasound signal and the reference direct fetal electrocardiogram Two subranges of Doppler bandwidths were separated to describe heart wall movements and valve motions. After reduction of signal complexity by determining the Doppler ultrasound envelope, the signal was analyzed to determine the FHR. The autocorrelation method supported by a trapezoidal prediction function was used. In the final stage, two different methods were developed to provide signal representation as time series of events: the first using correction of duplicate measurements and the second based on segmentation of instantaneous periodicity measurements. Thus, it ensured the mean heart interval measurement error of only 1.35 ms. In a case of beat-to-beat variability assessment the errors ranged from −1.9% to −10.1%. Comparing the obtained values to other published results clearly confirms that the new methods provides a higher accuracy of an interval measurement and a better reliability of the FHR variability estimation. Full article

For inverse synthetic aperture radar (ISAR) imaging of a ship target moving with ocean waves, the image constructed with the standard range-Doppler (RD) technique is blurred and the range-instantaneous-Doppler (RID) technique has to be used to improve the image quality. In this paper, azimuth echoes in a range cell of the ship target are modeled as noisy multicomponent cubic phase signals (CPSs) after the motion compensation and a RID ISAR imaging algorithm is proposed based on the integrated cubic phase bilinear autocorrelation function (ICPBAF). The ICPBAF is bilinear and based on the two-dimensionally coherent energy accumulation. Compared to five other estimation algorithms, the ICPBAF can acquire higher cross term suppression and anti-noise performance with a reasonable computational cost. Through simulations and analyses with the synthetic model and real radar data, we verify the effectiveness of the ICPBAF and corresponding RID ISAR imaging algorithm. Full article

Inverse synthetic aperture radar (ISAR) imaging of a maneuvering target is a challenging task in the field of radar signal processing. The azimuth echo can be characterized as a multi-component polynomial phase signal (PPS) after the translational compensation, and the high quality ISAR images can be obtained by the parameters estimation of it combined with the Range-Instantaneous-Doppler (RID) technique. In this paper, a novel parameters estimation algorithm of the multi-component PPS with order three (cubic phase signal-CPS) based on the modified discrete polynomial-phase transform (MDPT) is proposed, and the corresponding new ISAR imaging algorithm is presented consequently. This algorithm is efficient and accurate to generate a focused ISAR image, and the results of real data demonstrate the effectiveness of it. Full article