Ground Moving Target Imaging via SDAP-ISAR Processing: Review and New Trends

Gelli, S.; Bacci, Alessio

doi:10.3390/s21072391

Cited by 8 publications

(5 citation statements)

References 49 publications

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“…Section VI surveys important recent applications of ISAR imaging. Ground moving target imaging from space-and airborne platforms is one use-case receiving a great deal of interest [13]. Another emerging research topic is imaging non-rigid targets with rotating parts (such as drones and helicopters).…”

Section: B Paper Scope and Structurementioning

confidence: 99%

“…ISAR can be used to image targets moving on Earth's surface using a space-or airborne SAR sensor. This concept was first demonstrated in Raney's paper [46], and it has attracted a great deal of interest more recently [13]. For this application, there is an additional challenge besides motion compensation: The strong ground clutter returns may mask the moving target reflections.…”

Section: A Ground Moving Target Imagingmentioning

confidence: 99%

See 1 more Smart Citation

Inverse Synthetic Aperture Radar Imaging: A Historical Perspective and State-of-the-Art Survey

Vehmas¹,

Neuberger

2021

IEEE Access

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Radar can obtain high spatial resolution at large operating distances and its operation is largely independent from weather and lighting conditions. This makes it an important instrument in an ever-increasing number of applications requiring robust and reliable sensing of the environment. Due to the advancements in semiconductor technology and digital computation power, radar can obtain increasingly better position estimation accuracy, detection sensitivity, and target resolution. High-resolution imaging is an example of a rapidly advancing field of radar technology. Inverse synthetic aperture radar (ISAR) is an imaging technique that uses the motion of a target to obtain a high-resolution radar image of it. This paper presents a comprehensive review of past work and the state-of-the-art in ISAR imaging systems, algorithms, and applications. Starting from the early historical developments of simple monostatic range-Doppler imaging, we present the developments up to the current advanced spatially distributed imaging modalities and reconstruction algorithms. The list of references includes the most influential ISAR publications in the open literature up to early 2021.

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Section: B Paper Scope and Structurementioning

confidence: 99%

Section: A Ground Moving Target Imagingmentioning

confidence: 99%

Inverse Synthetic Aperture Radar Imaging: A Historical Perspective and State-of-the-Art Survey

Vehmas¹,

Neuberger

2021

IEEE Access

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“…There has been a well-known method for estimating the clutter covariance matrix, namely, the sample covariance matrix (SCM) using the maximum likelihood estimation [15], but this method performs well only when enough number of signals is independent and identically distributed [28]. In order to reduce the number of required observation data for achieving efficient detection performance within nonhomogeneous clutter, various knowledge-based methods using a priori information were proposed [10,23,24,32,34]. In [2,6], the Bayesian methods were leveraged to estimate the covariance matrix.…”

Section: Introductionmentioning

confidence: 99%

Towards a median signal detector through the total Bregman divergence and its robust analysis

Ono¹,

Peng²

2022

Preprint

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A novel family of geometric signal detectors are proposed through medians of the total Bregman divergence (TBD), which are shown advantageous over the conventional methods and their mean counterparts. By interpreting the observation data as Hermitian positive-definite (HPD) matrices, their mean or median play an essential role in signal detection. As is difficult to be solved analytically, we propose numerical solutions through Riemannian gradient descent algorithms or fixed-point algorithms.Beside detection performance, robustness of a detector to outliers is also of vital importance, which can often be analyzed via the influence functions. Introducing an orthogonal basis for Hermitian matrices, we are able to compute the corresponding influence functions analytically and exactly by solving a linear system, which is transformed from the governing matrix equation. Numerical simulations show that the TBD medians are more robust than their mean counterparts.

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“…The conventional sample matrix inverse (SMI) approach performs well when the number of training samples is greater than two times the dimensionality of STAP [10]. Unfortunately, this is restricted because the large independent and identical distribution (i.i.d) sample requirement will not usually hold in heterogeneous environments [11]. Worse still, training data are usually contaminated by outliers (i.e., discrete clutter), resulting in remarkable clutter suppression performance degradation.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous Clutter Suppression for Airborne Radar STAP Based on Matrix Manifolds

et al. 2021

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Clutter suppression in heterogeneous environments is a serious challenge for airborne radar. To address this problem, a matrix-manifold-based clutter suppression method is proposed. First, the distributions of training data in heterogeneous environments are analyzed, while the received data are characterized on a Riemannian manifold of Hermitian positive definite matrices. It is indicated that the training data with different distributions with the same power are separated, whereas data with the same distribution are closer together. This implies that the underlying geometry of the data can be better revealed by manifolds than by Euclidean space. Based on these properties, homogeneous training data are selected by establishing a binary hypothesis test such that the negative effects of the use of heterogeneous samples are alleviated. Moreover, as exploiting a geometric metric on manifolds to reveal the underlying information of data, experimental results on both simulated and real data validate that the proposed method has a superior performance with small sample support.

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Ground Moving Target Imaging via SDAP-ISAR Processing: Review and New Trends

Cited by 8 publications

References 49 publications

Inverse Synthetic Aperture Radar Imaging: A Historical Perspective and State-of-the-Art Survey

Inverse Synthetic Aperture Radar Imaging: A Historical Perspective and State-of-the-Art Survey

Towards a median signal detector through the total Bregman divergence and its robust analysis

Heterogeneous Clutter Suppression for Airborne Radar STAP Based on Matrix Manifolds

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