Range Points Migration Method Research Articles

K-Space Decomposition-Based 3-D Imaging With Range Points Migration for Millimeter-Wave Radar

In this article, we present a novel method that incorporates the range points migration (RPM) method, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> -space decomposition-based accurate, and noise-robust range extraction filter for microwave or millimeter-wave (MMW) short-range radar using a considerably lower fractional bandwidth signal. The advantage for higher angular resolution in higher frequency systems, such as MMW radar, has been implemented to the incoherent-based RPM method, using the simple 1-D or 2-D Fourier transform-based processing to maintain the imaging accuracy in RPM processing for both the range and the angular directions. As an additional advantage of our method, it also offers data clustering in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> -space, which can enhance the imaging accuracy of the RPM method. The numerical and experimental tests demonstrated that the proposed method offers numerous advantages over the Capon-based super-resolution algorithm or coherent-based imaging approaches.

Range-Point Migration-Based Image Expansion Method Exploiting Fully Polarimetric Data for UWB Short-Range Radar

Ultrawideband radar with high-range resolution is a promising technology for use in short-range 3-D imaging applications, in which optical cameras are not applicable. One of the most efficient 3-D imaging methods is the range-point migration (RPM) method, which has a definite advantage for the synthetic aperture radar approach in terms of computational burden, high accuracy, and high spatial resolution. However, if an insufficient aperture size or angle is provided, these kinds of methods cannot reconstruct the whole target structure due to the absence of reflection signals from large part of target surface. To expand the 3-D image obtained by RPM, this paper proposes an image expansion method by incorporating the RPM feature and fully polarimetric data-based machine learning approach. Following ellipsoid-based scattering analysis and learning with a neural network, this method expresses the target image as an aggregation of parts of ellipsoids, which significantly expands the original image by the RPM method without sacrificing the reconstruction accuracy. The results of numerical simulation based on 3-D finite-difference time-domain analysis verify the effectiveness of our proposed method, in terms of image-expansion criteria.

Three-Dimensional Imaging Method Incorporating Range Points Migration and Doppler Velocity Estimation for UWB Millimeter-Wave Radar

High-resolution, short-range sensors that can be applied in optically challenging environments (e.g., in the presence of clouds, fog, and/or dark smog) are in high demand. Ultrawideband (UWB) millimeter-wave radars are one of the most promising devices for the above-mentioned applications. For target recognition using sensors, it is necessary to convert observational data into full 3-D images with both time efficiency and high accuracy. For such conversion algorithm, we have already proposed the range points migration (RPM) method. However, in the existence of multiple separated objects, this method suffers from inaccuracy and high computational cost due to dealing with many observed RPs. To address this issue, this letter introduces Doppler-based RPs clustering into the RPM method. The results from numerical simulations, assuming 140-GHz band millimeter radars, show that the addition of Doppler velocity into the RPM method results in more accurate 3-D images with reducing computational costs.

Accurate ultrasound imaging based on range point migration method for the depiction of fetal surface.

The purpose of this study is to evaluate the performance of a modified range point migration (RPM) method using a semi-broad transmit beam for fetal surface imaging. The conventional RPM method depicts accurate images of target surfaces by estimating the reflection point on a target surface from the path length of plural transmit-and-receive element combinations. However, the conventional RPM method depicts false images when echoes from different targets are received simultaneously. For the elimination of false images in the employment of the RPM method, we propose a modified RPM method with a semi-broad transmit beam to decrease the number of targets in each measurement region. The modified RPM method depicted two acrylic cylinders of 2 cm in diameter with a root-mean-square error (RMSE) of 0.062 mm, where the RMSE of the migration method was 0.145 mm. The modified RPM method also succeeded in depicting a 7-month fetal phantom with a RMSE of 0.058 mm relative to a 3D image acquired using optical measurement. This study shows the potential of the modified RPM method in achieving accurate surface imaging of multiple targets using a semi-broad beam, indicating that the method is suitable for fetal surface imaging.

Efficient Three-Dimensional Imaging Method Based on Enhanced Range Point Migration for UWB Radars

Ultrawideband pulse radar has a definite advantage over optical ranging techniques in harsh optical environments, such as a dark smog or strong backlight. In security or rescue situations with blurry visibility, it is particularly promising for identifying human bodies. One of the most promising approaches for this type of application is the recently proposed range point migration (RPM) method, which is beneficial for nonparametric imaging and is robust in noisy or heavy interference situations. However, the original RPM requires a discretization of the direction-of-arrival variables in its search operation. The resulting coarse discretization seriously degrades the imaging accuracy, particularly for 3-D problems and far-field observations. Consequently, in this approach, there is a major tradeoff between the amount of computation and accuracy. To overcome this difficulty, this letter proposes a more efficient RPM method, where the extraction of the point of intersection of spheres is adopted. A distinct advantage of this method is that the accuracy is basically invariant to the observation range when avoiding the aforementioned discretization. Numerical simulations including noisy cases prove that our proposed RPM significantly reduces the computation complexity while retaining imaging accuracy.

Accurate 3-Dimensional Imaging Method Based on Extended RPM for Rotating Target Model

Three-dimensional (3-D) reconstruction techniques employed by airborne radars are essential for object recognition in scenarios where optically vision is blurry, and are required for the monitoring of disasters and coast-guard patrols. There have been reports on 3-D reconstruction methods that exploit the layover appearing in inverse synthetic aperture radar (ISAR) imagery, which are suitable for the recognition of artificial targets such as buildings, aircraft or ships. However, existing methods assume only a point target or the aggregate of point targets, and most require the tracking of the multiple points over sequential ISAR images. In the case of a solid object with a continuous boundary, such as a wire or polyhedral structure, the positioning accuracy of such methods is severely degraded owing to scattering centers continuously shifting on the target surface with changes in the rotation angle. To overcome this difficulty, this paper extends the original Range Points Migration (RPM) method to the ISAR observation model, where a double mono-static model with two transmitting and receiving antennas is introduced to suppress cross-range ambiguity. The results of numerical simulation and experimental validation demonstrate that the extended RPM method has a distinct advantage for accurate 3-D imaging, even for non-point targets.

Accurate and Omnidirectional UWB Radar Imaging Algorithm With RPM Method Extended to Curvilinear Scanning Model

Ultrawideband pulse radars are a promising technology for high-quality imaging sensors for rescue robots in the near field because they have the advantage of high range resolution. We have already proposed the accurate and fast imaging algorithm as range point migration (RPM), which employs the direction of arrival (DOA) with the global characteristic of the multiple observed ranges. However, this algorithm assumes the line scanning of an omnidirectional antenna and limits the imaging range. To overcome this limitation, this letter derives an extended RPM method, which accomplishes omnidirectional imaging and accurate target positioning. As a false-image-reduction scheme in this method, this letter introduces a postprocessing algorithm, which constrains the searching range for DOA estimation by using the initial RPM image. The results of numerical simulations, including noisy situations, show that the proposed method accomplishes accurate and omnidirectional imaging on the order of 1/100 wavelength and enhances the imaging range while avoiding false images.