N-Point RCS Models for Closely Spaced Object Resolution

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Current radar systems face challenges in accurately distinguishing between multiple closely spaced objects due to their radar cross-section (RCS) signatures, especially when using lower frequency microwave radars, leading to potential misidentification in critical applications like air traffic control, and existing methods for generating multiple object scenarios are impractical and costly.

Innovation Solution

A method and system utilizing N-point signature prediction models with a computer-based processing chain that combines individual RCS data from a database, employing ray tracing and blockage checking to account for object interactions, allowing for improved target resolution and probability of intercept without requiring high-frequency microwave technology.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If higher frequency microwave radar is used to improve resolution and distinguish multiple closely spaced objects, then measurement precision is improved, but device complexity and cost increase exponentially

Engineering Contradiction:

Improveradar resolutionVSAvoidradar system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent creates a virtual model (copy) of the radar system and environment, including virtual representations of multiple objects and their interactions. This virtual model allows for simulation and analysis of radar signatures without requiring actual high-frequency hardware, thereby achieving the analytical benefits of high-frequency radar while avoiding the exponential cost and complexity increase

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent replaces the physical mechanical/electrical system of high-frequency microwave radar with a computational model-based system. Instead of using expensive high-frequency hardware to achieve resolution, the system uses computer simulations, ray tracing algorithms, and virtual scenario generation to analyze and distinguish multiple objects, substituting computational processing for physical hardware complexity

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If a massive database of multiple object scenarios is created to distinguish between objects, then measurement precision is improved, but loss of time and computational resources increase

Engineering Contradiction:

Improveobject identification accuracyVSAvoiddatabase generation time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent pre-generates and stores radar signature data for individual objects in a database before actual detection scenarios occur. These pre-computed individual object signatures are then combined using ray tracing and blockage checking algorithms to create multi-object scenario signatures on-demand, avoiding the need to generate and store every possible multi-object combination in advance

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent merges individual object radar signature data from the database with ray tracing simulations of object interactions (blockage, coupling, multiple scattering) to generate composite multi-object scenario signatures. This combining approach allows the system to create accurate multi-object RCS predictions by integrating pre-computed individual object data with simulated interaction effects, reducing the need for exhaustive pre-generation of all possible scenarios

Inventive Principle:

Principle #5Merging (Combining)

3Device complexity

If lower frequency microwave radar is used to reduce cost, then device complexity is reduced, but measurement precision deteriorates causing multiple objects to be detected as a single object

Engineering Contradiction:

Improveradar system complexityVSAvoidtarget resolution

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent introduces an intermediary computational layer between the radar signal and the target identification process. This intermediary system uses ray tracing algorithms and blockage checking to simulate and analyze the radar signatures of multiple objects, accounting for complex interactions like multiple scattering and coupling effects. This computational intermediary enables accurate distinction of multiple closely spaced objects even when using lower frequency radar hardware

Inventive Principle:

Principle #24Intermediary (Mediator)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Enhances the accuracy of radar systems in detecting multiple objects by effectively modeling and predicting their combined RCS signatures, improving the probability of intercept and reducing costs associated with high-frequency radar technology.

Implementation Method 1

employ a ray tracing scheme to determine ray blockage and ray coupling as a result of object interaction

Methodology Applied

Scientific EffectRay tracing: Reflection

Data Source

PatentUS7652620B2RCS signature generation for closely spaced multiple objects using N-point models

Publication Date: 2010.01.26 RAYTHEON CO

AI summary

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.