Three-dimensional ISAR imaging: a review

Three-dimensional (3D) inverse synthetic aperture radar (ISAR) imaging has been proven feasible by combining traditional ISAR imaging and interferometry. Such technique, namely inteferometric ISAR (In-ISAR), allows for the main target scattering centres to be mapped into a 3D spatial domain as point clouds. Specifically, the use of an In-ISAR system can overcome the main geometrical interpretation issues imposed by the monostatic acquisition geometry as the problem of cross-range scaling and unknown image projection plane (IPP). However, some issues remain such as scatterer scintillation, shadowing effects, poor SNR etc., which limit the effectiveness of 3D imaging. A solution to such unsolved issues can be found in the use of multiple 3D views, which can be obtained exploiting either multi-temporal or multi-perspective configurations or a combination of both. This study aims to review the main concepts to produce multi-view 3D ISAR images by using In-ISAR systems also presenting real data collected with a multi-static In-ISAR system

ISAR image matching and three-dimensional scattering imaging based on extracted dominant scatterers

This paper studies inverse synthetic aperture radar (ISAR) image matching and three-dimensional (3D) scattering imaging based on extracted dominant scatterers. In the condition of a long baseline between two radars, it is easy for obvious rotation, scale, distortion, and shift to occur between two-dimensional (2D) radar images. These problems lead to the difficulty of radar-image matching, which cannot be resolved by motion compensation and cross-correlation. What is more, due to the anisotropy, existing image-matching algorithms, such as scale invariant feature transform (SIFT), do not adapt to ISAR images very well. In addition, the angle between the target rotation axis and the radar line of sight (LOS) cannot be neglected. If so, the calibration result will be smaller than the real projection size. Furthermore, this angle cannot be estimated by monostatic radar. Therefore, instead of matching image by image, this paper proposes a novel ISAR imaging matching and 3D imaging based on extracted scatterers to deal with these issues. First, taking advantage of ISAR image sparsity, radar images are converted into scattering point sets. Then, a coarse scatterer matching based on the random sampling consistency algorithm (RANSAC) is performed. The scatterer height and accurate affine transformation parameters are estimated iteratively. Based on matched scatterers, information such as the angle and 3D image can be obtained. Finally, experiments based on the electromagnetic simulation software CADFEKO have been conducted to demonstrate the effectiveness of the proposed algorithm

Moving Target Detection in Foliage Using Along Track Monopulse Synthetic Aperture Radar Imaging

Abstract-This paper presents a method for detecting moving targets embedded in foliage from the monostatic and bistatic Synthetic Aperture Radar (SAR) data obtained via two airborne radars. The two radars, which are mounted on the same aircraft, have different coordinates in the along track (cross-range) domain. However, unlike the interferometric SAR systems used for topographic mapping, the two radars possess a common range and altitude (i.e., slant range). The resultant monopulse SAR images are used to construct difference and interferometric images for moving target detection. It is shown that the signatures of the stationary targets are weakened in these images. Methods for estimating a moving target's motion parameters are discussed. Results for an ultrawideband UHF SAR system are presented

Advanced Ground-Based Real and Synthetic Aperture Radar

Ground-based/terrestrial radar interferometry (GBRI) is a scientific topic of increasing interest in recent years. The GBRI is used in several field as remote sensing technique for monitoring natural environment (landslides, glacier, and mines) or infrastructures (bridges, towers). These sensors provide the displacement of targets by measuring the phase difference between sending and receiving radar signal. If the acquisition rate is enough the GBRI can provide the natural frequency, e.g. by calculating the Fourier transform of displacement. The research activity, presented in this work, concerns design and development of some advanced GBRI systems. These systems are related to the following issue: detection of displacement vector, Multiple Input Multiple Output (MIMO) and radars with 3D capability

Multiple input multiple output radar three dimensional imaging technique

Ph.DDOCTOR OF PHILOSOPH

Decentralized approach for translational motion estimation with multistatic inverse synthetic aperture radar systems

This paper addresses the estimation of the target translational motion by using a multistatic Inverse Synthetic Aperture Radar (ISAR) system composed of an active radar sensor and multiple receiving-only devices. Particularly, a two-step decentralized technique is derived: the first step estimates specific signal parameters (i.e., Doppler frequency and Doppler rate) at the single-sensor level, while the second step exploits these estimated parameters to derive the target velocity and acceleration components. Specifically, the second step is organized in two stages: the former is for velocity estimation, while the latter is devoted to velocity estimation refinement if a constant velocity model motion can be regarded as acceptable, or to acceleration estimation if a constant velocity assumption does not apply. A proper decision criterion to select between the two motion models is also provided. A closed-form theoretical performance analysis is provided for the overall technique, which is then used to assess the achievable performance under different distributions of the radar sensors. Additionally, a comparison with a state-of-the-art centralized approach has been carried out considering computational burden and robustness. Finally, results obtained against experimental multisensory data are shown confirming the effectiveness of the proposed technique and supporting its practical application

Joint shape and motion estimation from echo-based sensor data

2018 Fall.Includes bibliographical references.Given a set of time-series data collected from echo-based ranging sensors, we study the problem of jointly estimating the shape and motion of the target under observation when the sensor positions are also unknown. Using an approach first described by Stuff et al., we model the target as a point configuration in Euclidean space and estimate geometric invariants of the configuration. The geometric invariants allow us to estimate the target shape, from which we can estimate the motion of the target relative to the sensor position. This work will unify the various geometric- invariant based shape and motion estimation literature under a common framework, and extend that framework to include results for passive, bistatic sensor systems