Calculating radar range profile by time domain processing with physical optics

Abstract

This thesis provides an in-depth exploration of the concept of Radar Cross Section (RCS) analysis. RCS is a critical metric in radar technology, used to measure the detectability of a target by quantifying the electromagnetic energy scattered by the target and reflected back to the radar system. This study examines the theoretical foundations, computational methods, and practical applications of RCS, offering an approach that aims to bridge the gap between theoretical knowledge and real-world implementations. The thesis contributes significantly to areas such as radar system design, radar signal processing, and stealth technology evaluation. The study begins with the theoretical foundations of the RCS concept. RCS is influenced by numerous factors, including the size, shape, material properties, and orientation of the object, as well as the radar operating frequency. The scattering mechanisms that affect RCS are categorized into specular reflection, diffuse scattering, edge diffraction, and multiple scattering. Each mechanism impacts RCS differently depending on the geometry and electromagnetic properties of the target. Additionally, the behavior of RCS is described across three main regions: the Rayleigh region (where the object's size is much smaller than the radar wavelength), the Resonance region (where the object's size is comparable to the radar wavelength), and the Optical region (where the object's size is much larger than the radar wavelength). These classifications provide a fundamental framework for understanding how the interaction between geometry and radar frequency affects the visibility of a target. The second part of the thesis focuses on computational methods used for RCS analysis. These methods are divided into two main categories: high-frequency and low-frequency techniques. High-frequency techniques include Physical Optics (PO), Geometric Optics (GO), the Geometric Theory of Diffraction (GTD), and the Shooting and Bouncing Rays (SBR) method. These techniques are based on optical approximations and are computationally efficient for modeling large targets. However, they are limited in accurately modeling diffraction and multiple scattering effects. On the other hand, low-frequency techniques, such as the Method of Moments (MoM) and the Finite Element Method (FEM), provide accurate full-wave solutions for small targets or resonant cases but come with high computational costs for large targets. The choice of method depends on factors such as the target's size, radar frequency, and the desired level of accuracy. To improve the accuracy of RCS computations, this thesis introduces two algorithms: a mesh refinement algorithm and a shadowing algorithm. The mesh refinement algorithm ensures that triangular surfaces in 3D models meet specific size constraints based on the radar wavelength, enhancing the accuracy of RCS predictions for targets with complex geometries. In regions with high curvature or intricate details, surfaces are iteratively subdivided to provide a more detailed representation. The shadowing algorithm accurately identifies and models the shadowed regions of the target, which do not contribute to radar returns. By combining these two algorithms, the thesis provides a more accurate and reliable framework for RCS computations, particularly for targets with complex geometries. One of the key contributions of this thesis is the transition from traditional frequency-domain analysis to time-domain simulations, offering a different perspective for analyzing target-radar interactions. Most conventional methods assume continuous wave (CW) radar operations, which do not accurately reflect the pulse-based structure of modern radar systems. To address this limitation, this study integrates physical optics principles with time-domain simulations. This approach enables more realistic modeling of radar pulse behavior. By storing the reflectivity contributions of illuminated mesh elements in detail, the interaction between radar pulses and the target can be analyzed dynamically and spatially. This transition significantly enhances the ability to simulate real-time radar operations, accounting for target movement and temporal variations in radar returns. The thesis further strengthens this framework through advanced signal processing techniques. Matched filtering maximizes the signal-to-noise ratio (SNR), facilitating the detection of weak targets and improving range resolution. Range normalization compensates for signal attenuation over distance, ensuring consistent detection sensitivity across different ranges. Coherent integration accumulates signal energy across multiple radar pulses, enabling the detection of weaker targets. These techniques allow for the generation of high-resolution range profiles (HRRPs), which provide detailed information about the physical dimensions and reflective properties of targets by isolating the strongest reflections within a predefined range window. The practical applicability of the proposed methodologies has been tested through simulations of different targets. First, a PEC missile target was analyzed at operating frequencies of 2 GHz and 4 GHz. The RCS results were validated against those obtained from the commercial FEKO software, demonstrating a high level of accuracy. The missile's structural features, scattering behavior, and high-resolution range profile were examined from multiple perspectives, and the proposed approach achieved a target dimension estimation with an accuracy of 0.24 meters. Additionally, the F-22 aircraft was also analyzed as part of the validation process. RCS results were compared with FEKO simulations, showing excellent agreement and verifying the accuracy of the proposed techniques. The HRRP analysis accurately estimated the dimensions and range of the F-22, demonstrating the applicability of the framework to complex geometries. Signal processing steps, such as matched filtering, range normalization, and coherent integration, were consistently applied across all targets, ensuring reliable differentiation between target reflections and noise. Lastly, the Chengdu J-20 aircraft, with its larger dimensions and complex geometry, was analyzed at 4 GHz. The RCS results obtained for this aircraft were consistent with FEKO simulations, further validating the robustness of the proposed methodologies. This case study highlights the framework's ability to handle large-scale targets and intricate geometries, as well as its effectiveness in extracting detailed range profiles of the aircraft. The thesis concludes by emphasizing the contributions of these methodologies to RCS analysis and radar signal processing. The integration of mesh refinement and shadowing algorithms with time-domain simulations addresses significant challenges in modeling complex geometries and real-time radar interactions. The proposed techniques have a wide range of applications, including radar system design, stealth technology evaluation, and electromagnetic wave analysis. By combining theoretical principles with computational innovations, this thesis establishes a strong foundation for future research and practical advancements in radar technology.