Raytheon Company

Chul J Lee

Brian J Harkins

Axel R Villanueva

Richard A Gilstrap

Sean T Price

Andrew P Simmons

In one aspect, a method to generate radar cross section (RCS) signatures, includes determining a spectrum of an object and using the spectrum of the object to generate RCS signatures of a plurality of objects. In another aspect, an apparatus to generate radar cross section (RCS) signatures includes circuitry to determine a spectrum of an object; and use the spectrum of the object to generate RCS signatures of a plurality of objects. In a further aspect, an article includes a machine-readable medium that stores executable instructions to generate radar cross section signatures (RCS). The executable instructions cause a machine to determine a spectrum of an object and use the spectrum of the object to generate RCS signatures of a plurality of objects.

Generating radar cross-section signatures

In one aspect, a system to generate radar signatures for multiple objects in real-time includes a first module including at least one processor to perform a shooting and bouncing (SBR) technique to solve for physical optics and multi-bounce characteristics of the objects. The at least one processor includes a central processing unit to perform dynamic ray tracing and a graphics processing unit (GPU) to perform far field calculations. The GPU includes a hit point database to store entries associated with rays that intersect an object.

Electromagnetic (EM) solver using a shooting bouncing ray (SBR) technique

In one aspect, a system to generate a radar signature of an object includes electromagnetic processing modules that include a first module including at least one processing unit to perform a shooting and bouncing (SBR) technique to solve for physical optics and multi-bounce characteristics of the object, a second module including a processing unit to perform a physical theory (PTD) technique to solve for material edges of the object and a third module including a processing unit to perform an incremental length diffraction coefficient (ILDC) to solve for material boss/channel. Results from the first, second and third modules are coherently integrated by frequency to generate radar cross section (RCS) values of the object in real-time. Performance of the system is scalable by adding processing units to at least one of the first, second or third modules.

Parallel processing to generate radar signatures for multiple objects

A method and system for analyzing the RCS of an object using N Point signature prediction models is provided. N-point signature prediction models are created for each object in a scenario and stored in lookup tables. Shooting and Bounce trace back techniques are used to determine RCS signatures of multiple objects in modeled scenarios to account for blockage by and coupling phenomena of a scattered field.

RCS signature generation for closely spaced multiple objects using N-point models

Apparatus and method for real-time determination of radar cross sections is disclosed using interleaved gridding. Radar cross section calculations are amenable to an implementation on parallel processors wherein the shooting window is subdivided into smaller areal units that are assigned to the parallel processors in an alternating fashion, such that the calculations performed by a single processor are not localized to a single area of the shooting window. As further disclosed, the shooting and bouncing ray technique for calculating radar cross sections is implemented using the apparatus and method disclosed herein.

Method and apparatus for interleaved gridding in distributed multiple computing for real-time RCS prediction

A method to reduce scattering centers (SC) includes receiving a set of SC data points representing an object. The method also includes reducing SC data points associated with a first region based on magnitudes of intensity of the SC data points associated with the first region, reducing SC data points associated with a second region based on magnitudes of intensity of the SC data points associated with the second region, combining the reduced SC data points associated with the first region and the second region to form a reduced set of SC data points, comparing the reduced set of SC data points with the received set of SC data points to determine if the reduced set of SC data points meets a set of comparison metrics and if the reduced set of SC data points meets the set of comparison metrics, performing another iteration of the reducing.

Reducing scattering center data using magnitude-based reduction

In one example, a method to reduce scattering centers (SC) includes receiving a set of SC data points associated with an object in three-dimensional space, partitioning the SC data points into a plurality of volumes, aggregating the SC data points within each volume based on an aggregate threshold and combining the aggregated SC data points associated with each volume to form a reduced set of SC data points. The method also includes comparing the reduced set of SC data points with the received set of SC data points to determine if the reduced set of SC data points meets a set of comparison metrics and if the reduced set of SC data points meets the set of comparison metrics, increasing the size of the volumes and performing another iteration of reducing the SC data points by volume.

Reducing scattering center data using multi-volume aggregation

In one aspect, a method to generate radar signatures for multiple objects includes performing in parallel a shooting and bouncing (SBR) technique to solve for physical optics and multi-bounce characteristics of a plurality of objects in motion, a physical theory (PTD) technique to solve for material edges of the objects and a incremental length diffraction coefficient (ILDC) to solve for material boss/channel. The method also includes coherently integrating the results from the SBR, PTD and ILDC techniques by frequency and generating the radar cross section (RCS) values of the plurality of objects. Performing the SBR technique includes evaluating rays independently.

Generating radar signatures for multiple objects

In one aspect, a method to generate radar signatures for multiple objects in motion, includes performing a shooting and bouncing (SBR) technique to solve for physical optics and multi-bounce characteristics associated with the objects. Performing the SBR technique includes performing dynamic ray tracing to form an image of an object having surfaces and edges. Performing the dynamic ray tracing includes transforming the object in a common coordinate frame of reference to a centered-body axis frame of reference.

Growing community of inventors

Lexington, MA, United States of America

Chul J Lee