The bidirectional analytic ray tracing (BART) method is developed to rapidly calculate composite scattering from three-dimensional (3D) electrically large complex targets above a randomly rough surface. Ray tracing is carried out both along the incident (forward) direction and converse direction of scattering (backward) recording different orders of ray illumination on each facet or edge of the target and surface. Once a pair of forward and backward rays meet on a facet/edge, a scattering term is constructed using the diffused scattering/diffraction of this facet/edge and all reflections occurred on the tracing paths. The rough surface is modeled with ldquorough facetsrdquo including coherent scattering and diffused incoherent scattering, which can be directly calculated according to the IEM (integral equation method) of a randomly rough surface. Analytic tracing of polygon ray tubes is developed to precisely calculate the illumination and shadowing of facets, which exempt large patches of the target from any finer meshing. It significantly reduces the complexity relevant to the target electric-size. Higher orders of scattering and, in particular, interactions between the target and rough surface are then taken into account. The accuracy and performance of BART is validated and evaluated by comparing with exact computational electromagnetic methods for electrically small targets. Numerical examples of angularly composite scattering from a three-dimensional electrically large, e.g., a ship-like target over a randomly rough surface are presented and discussed.

Bidirectional Analytic Ray Tracing for Fast Computation of Composite Scattering From Electric-Large Target Over a Randomly Rough Surface

The shooting and bouncing ray (SBR) method is highly effective in the radar cross section (RCS) prediction. For electrically large and complex targets, computing scattered fields is still time-consuming in many applications like range profile and ISAR simulation. In this paper, we propose a GPU-based SBR that is fully implemented on the graphics processing unit (GPU). Based on the stackless kd-tree traversal algorithm, the ray tube tracing can rapidly evaluate the exit position in a single pass on the GPU. We also present a technique for fast electromagnetic computing that allows the geometric optics (GO) and Physical optics (PO) integral to be carried out on the GPU efficiently during the ray tube tracing. Numerical experiments demonstrate that the GPU-based SBR can significantly improve the computational efficiency of the RCS prediction, about 30 times faster, while providing the same accuracy as the CPU-based SBR.

GPU-Based Shooting and Bouncing Ray Method for Fast RCS Prediction

Ray tracing is of great use for computational electromagnetics, such as the well-known shooting and bouncing ray (SBR) method. In this paper, the kd-tree data structure, coupled with the mailbox technique, is proposed to accelerate the ray tracing in the SBR. The kd-tree is highly effective in handling the irregularly distribution of patches of the target, while the repeatedly intersection tests between the ray and the patch when using space division acceleration structures can be eliminated through the mailbox technique. Numerical results show excellent agreement with the measured data and the exact solution, and demonstrate that the kd-tree as well as the mailbox technique can greatly reduce the computation time.

/pdf/kd-tree-based-fast-ray-tracing-for-rcs-prediction-3b96vt9yus.pdf

Kd-tree based fast ray tracing for rcs prediction

This paper presents a forward approach to establish parametric scattering center models for known complex radar targets. In this approach, an automatic technique based on ray tracing and clustering is first developed to extract scattering centers directly from the computer-aided design (CAD) model of the targets. Following this, a set of forward methods is developed to determine the physically relevant parameters of two-dimension (2-D) attributed scatterers, such as type, amplitude, position and length. Finally, this approach is validated through the parametric model establishment of two complex targets and good agreement has been demonstrated between the reconstructed and actual radar characteristics. Different from the familiar inverse extraction approaches, the proposed approach provides a new forward way of constructing radar targets' feature database based on 2-D parametric scattering center model, which will ultimately facilitate the feature matching in the synthetic aperture radar (SAR) automatic target recognition (ATR) system.

A Forward Approach to Establish Parametric Scattering Center Models for Known Complex Radar Targets Applied to SAR ATR

In this paper, a convergence analysis to obtain the optimal calculation parameters in an inhouse 3D ray launching algorithm to model the radio wave propagation channel in complex indoor environments is presented. Results show that these parameters lead to accurate estimations with reduced computational time. In addition, simulation results of an indoor complex scenario in terms of received power and power delay profile are presented, showing significant influence of multipath propagation in an indoor radio channel. The adequate election of simulation parameters given by convergence conditions, can aid in optimizing required computational time.

Convergence Analysis in Deterministic 3D Ray Launching Radio Channel Estimation in Complex Environments

The present paper deals with a new efficient approach in order to assess the simulation of scattered fields from arbitrary metallic objects. The basic idea is to combine a ray tracing algorithm with the principles of physical optics (PO) and the physical theory of diffraction (PTD). The ray tracing algorithm stochastically launches discrete rays and uses a ray density normalization. In order to perform simulations at finite objects the PO/PTD formulation is required. Thus, fast intersection routines can be implemented, while the ray density formulation reduces the PO and PTD integrals to a pure sum of ray contributions. Simulation results obtained with this model are verified by comparison with both exact simulations using a method of moments (MoM) code and measurement results, proving an excellent accuracy and fast computation even at complex objects. With this asymptotic approach, scattering properties of large objects that are too complex for exact methods can be analyzed with rather moderate computation efforts. Typical applications include the simulation of low observability (LO) designs as well as the generation of databases for identifying unknown aircraft by their radar signature.

Ray tracing with PO/PTD for RCS modeling of large complex objects

Automotive radar sensors can measure Doppler and micro-Doppler signatures caused by road users and their moving parts. Radar sensor validation as well as the development of micro-Doppler-based classification approaches require simulation methods able to generate such signatures. In this paper, a deterministic analytic ray-tracing approach is introduced which is able to simulate micro-Doppler signatures. The approach is demonstrated with two driving scenarios: A vehicle with rotating tires driving along a straight line and the same vehicle driving in a circle. Based on these scenarios, it is demonstrated that an artefact-free simulation of micro-Doppler can be achieved using the aforementioned simulation method.

Ray-Tracing-Based Micro-Doppler Simulation for 77 GHz Automotive Scenarios

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Ray tracing with PO/PTD for RCS modeling of large complex objects

Ray-Tracing-Based Micro-Doppler Simulation for 77 GHz Automotive Scenarios