Cameron Decomposition Research Articles

Backscattering Analysis at ATR on Rough Surfaces by Ground-Based Polarimetric Radar Using Coherent Decomposition

This article deals with the analysis of backscattering at automatic target recognition (ATR) by ground-based radar located on rough terrain surfaces, using the properties of wave polarization. The purpose of the study is to examine and compare linear and circular polarized reflected waves, which can be described by decomposition theorems. Coherent decompositions (Pauli, Krogager, Cameron decomposition) are considered in the case of a rough terrain, for which the advantage of the Pauli decomposition has been shown. The article demonstrates an approach to the extraction of polarization signal backscattering data for two types of vehicles with different profiles. It is shown that the measurement results can be calibrated by a corner reflector that takes into account the properties of the ground surface, and further used for ATR based on supervised learning algorithms. The accuracy of object classification was 68.1% and 54.2% for the signal generated by linearly and elliptically polarized waves, respectively. Based on these results, we recommend using a linearly polarized wave as an object recognition mechanism. At the same time, any reflected depolarized wave significantly reshapes the structure due to the rotation of the object profile and the influence of a rough surface (vegetation fluctuations). This explains the low recognition accuracy in general.

Null-Pol Response Pattern in Polarimetric Rotation Domain: Characterization and Application

Man-made targets with various orientations usually exhibit scattering diversity which makes polarimetric radar target recognition difficult. The recently developed polarimetric rotation domain techniques provide solutions to understand and utilize target scattering diversity. Meanwhile, the Null-Pol theory is the important component of target optimal polarization in radar polarimetry. This work first extends the Null-Pol theory into the polarimetric rotation domain and discloses the different scattering responses from canonical man-made structures. In this vein, the Null-Pol response pattern interpretation tool is established and a set of Null-Pol features are extracted and characterized. Then, a man-made structure identification approach is proposed based on selected features derived from the Null-Pol response pattern. Comparison studies are carried out with simulated datasets of canonical structures considering polarimetric measurement errors, simulated, and measured data of unmanned aerial vehicles (UAVs). Compared with the Cameron decomposition, the proposed method achieves more accurate and stable performance.

Man-Made Target Structure Recognition With Polarimetric Correlation Pattern and Roll-Invariant Feature Coding

Man-made target recognition is of great significance for many applications within microwave remote sensing. The scattering diversity of various man-made target structures makes radar target identification a difficult task. This work aims at mitigating this issue by mining and utilization of man-made target scattering diversity in polarimetric rotation domain with the interpretation tool of polarimetric correlation pattern. The optimal polarimetric roll-invariant feature set is collected from polarimetric correlation pattern. Then, a polarimetric roll-invariant feature coding scheme is developed for man-made target structure recognition. Moreover, polarimetric radar measurement errors in terms of channel coupling and imbalance are also considered. Experimental studies with electromagnetic computation datasets including canonical structures and an unmanned aerial vehicle (UAV) target and real spaceborne polarimetric synthetic aperture radar (PolSAR) data of a ship target are carried out. Compared with the Cameron decomposition, the proposed method exhibits better recognition performance and stronger robustness, especially for oriented man-made structures.

On the Extension of Cameron Decomposition Helicity Asymmetry Parameter From Single-Look to Multi-Look PolSAR Imagery

The helicity asymmetry parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\tau $ </tex-math></inline-formula> in the Cameron decomposition indicates the degree to wh ich a scatterer deviates from being an ideal symmetric scatterer. However, the solving procedure of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\tau $ </tex-math></inline-formula> can only be expressed in terms of single-look Sinclair scattering matrix. In this article, we extend the helicity <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\tau $ </tex-math></inline-formula> to a generalized helicity parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\tau _{g} $ </tex-math></inline-formula> , which is appropriate for both the single- and multi-look polarimetric synthetic aperture radar (PolSAR) data. For single-look data, the generalized helicity <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\tau _{g} $ </tex-math></inline-formula> is equivalent to the previous helicity <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\tau $ </tex-math></inline-formula> . In addition, we investigate the relationships among the classical helix/helicity definitions, including the Cameron helicity, the Krogager helix component, and the Yamaguchi helix component. To achieve this, we represent the Cameron and Krogager decompositions in terms of the unified coherent polarimetric decompositions (CTD) model in the format of coherency matrix and revise the expression of Krogager decomposition contributions in function of Huynen parameters. Results show that essentially the Cameron helicity and Krogager helix are two kinds of representation of reflection asymmetry under the same decomposition model, and the Yamaguchi helix contribution is always larger than the Krogager helix contribution. Single-look PolSAR data from L-band ESAR are used for demonstration in this article. Several multi-look datasets are generated by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1\,\,\times \,\,3$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3\,\,\times \,\,3$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3\,\,\times \,\,5$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5\,\,\times \,\,5$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5\,\,\times \,\,7$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$7\,\,\times \,\,7$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$7\,\,\times \,\,9$ </tex-math></inline-formula> , and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$9 \times 9$ </tex-math></inline-formula> boxcar average. Two techniques are taken to mitigate reflection symmetry assumption based on helix component and helicity angle, respectively. It will be shown that the technique with the generalized helicity <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\tau _{g} $ </tex-math></inline-formula> performs best in terms of efficiency and stability.

Calculating the model of a nondiagonal rotation invariant angle for a complicated scatterer.

In the research on scattering polarimetry, a scattering mechanism is described by an internal degree of freedom called rotation invariant parameter α. Traditionally, α is calculated by the diagonal scattering matrix of the single scatterer. However, when the research object is a scatterer with complicated surface and microstructure, the traditional calculation of parameter α is biased, since the corresponding scattering matrix is a nondiagonal matrix. To address this problem, this paper proposes a scientific model based on Cameron decomposition to raise the accuracy of parameter α in the complicated scatterer. The rotation invariant parameter with higher accuracy is renamed as a nondiagonal rotation invariant angle. In the verified experiments, the experimental values of each nondiagonal rotation invariant angle are compared with the referenced values calculated by optical constant and incident angle. The results demonstrate that fewer residuals are achieved than by the traditional method. Based on the presented calculating model, the scattering mechanism difference interval between two different materials is proposed as a judging area to distinguish the differences between scattering mechanisms in application.

Impact of Polarization Distortions on Geometrical Structure Retrieval of Moving Man-Made Targets in ISAR Images

In this paper, the impact of several polarization distortions on geometrical structure retrieval of man-made targets in inverse synthetic aperture radar (ISAR) images is assessed. For polarimetric ISAR, the polarization distortions are usually composed of crosstalk and channel imbalance. For non-stationary targets, a residual phase error exists between two columns of the scattering matrix in the alternate transmission and simultaneous reception (ATSR) mode, especially when the radar frequency is high. These two kinds of distortions have varying influences on different targets, as well as different decomposition methods. Some theoretical derivations and numerical analyses are given to reveal the impact of these distortions on Cameron decomposition. To evaluate the impact of these distortions on geometrical structure retrieval, we use the numerical results and real data of an unmanned aerial vehicle (UAV) called Frontier to perform error analysis of both the decomposition and the retrieved size of the designated structures of the UAV. Some numerical evaluations were conducted from the perspective of system design, and these results can be useful for the practical radar system.

A unified three-component scattering model for polarimetric coherent target decomposition

In this article, first, the properties of the symmetric scattering space are examined based on the representation of the maximum symmetric scattering component proposed by Touzi. The symmetric scattering unit disc in the complex plane is mapped to a more intuitive unit sphere representation, and a new simpler classification method for symmetric scatterers is proposed based on a simplified symmetric scatterer scattering matrix metric distance. Then, a unified three-component scattering model for polarimetric coherent target decomposition (CTD) is proposed. Pauli decomposition, sphere, dihedral, helix (SDH) decomposition and Cameron decomposition can be expressed as a simplified form of the unified model with some certain restrictions, respectively. In addition, SDH decomposition and Cameron decomposition are proved to be equivalent by verification of restrictions’ consistency. Finally, by the combination of SDH decomposition and symmetric scatterer classification, a scattering matrix classification scheme is proposed to classify the scatterers into 12 scattering types.

Derivation of a Signed Cameron Decomposition Asymmetry Parameter and Relationship of Cameron to Huynen Decomposition Parameters

An alternate definition of the asymmetry parameter τ, appearing in the Cameron decomposition is presented. The new definition is signed as τs, but in absolute value, it is equivalent to the previous definition. The Cameron decomposition signed asymmetry parameter τs is given in terms of the Huynen decomposition parameters, including but not limited to the Huynen helicity (asymmetry) parameter. It is demonstrated that the Huynen decomposition asymmetry parameter is a poor indicator of scatterer symmetry. The relationship between the Cameron and Huynen decomposition parameters is examined for special cases.

Automatic Target Recognition by Means of Polarimetric ISAR Images and Neural Networks

Inverse synthetic aperture radar (ISAR) images are often used for classifying and recognizing targets. Moreover, the use of fully polarimetric ISAR (Pol-ISAR) images enhances classification capabilities. In this paper, the authors propose a novel automatic target recognition (ATR) technique based on the use of fully Pol-ISAR images and neural networks (NNs). In order to reduce the amount of data processed by the classifier, the brightest scattering centers are first extracted by means of the Pol-CLEAN technique, and then, their scattering matrices are decomposed using Cameron's decomposition. A classifier based on the use of multilayer perceptron NN that makes use of the features extracted from the Pol-ISAR images is then implemented. A proof-of-concept test is performed on real data acquired during a controlled experiment in an anechoic chamber.

Conservative Polarimetric Scatterers and Their Role in Incorrect Extensions of the Cameron Decomposition

The properties of symmetric polarimetric scatterer scattering matrices are examined. It is shown that the unambiguous rotation angle for conservative symmetric polarimetric scatterers is the interval (-pi/4,+pi/4] as compared with (-pi/2,+pi/2] for nonconservative symmetric scatterers. Errors relating to the Cameron decomposition, which are recently introduced into the literature, are discussed. It is demonstrated that these errors arise from a faulty symmetric scatterer scattering matrix distance measure. This, in turn, leads to an improper mapping of the symmetric scatterer unit disk to a hemisphere. The correct mapping of the symmetric scatterer unit disk to the symmetric scatterer unit sphere is described

Detection of crashed aircraft in polarimetric imagery

This manuscript presents studies examining the use of C-band polarimetric Synthetic Aperture Radar (SAR) systems for the detection of crashed aircraft. The ultimate aim is to assist Search and Rescue in Canada in the location of such targets. Detection methodologies based on the Polarimetric Whitening Filter, Cameron Decomposition, and measures of even bounce contributions to the backscatter have been examined. Tests were performed using imagery of serviceable and crashed aircraft and crashed aircraft parts. Although individual methods make it possible to detect the crashed aircraft, best results for target detection with decreased numbers of false alarms occur when these methods are used in combination.