Far-Field Rotated Range Profile Model for Radar Simulation
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Solution Overview
Problem
Current radar simulation models, such as the Rotated Range Profile Reduced-Order Model (RRP-ROM), are limited by their dependence on specific sensor designs and placements, requiring frequent database rebuilding and introducing artifacts or increased storage needs when interpolating for different radar sensors, which degrades simulation realism and efficiency.
Innovation Solution
A method using a far-field Rotated Range Profile Reduced-Order Model (FF-RRP ROM) that abstracts radar antennas and frequency sampling, allowing for a compact database of radar scattering effects for multiple radar sensors and waveforms, employing Fast Fourier Transforms (FFTs) for interpolation to match frequency sampling, enabling real-time dynamic simulation with enhanced realism and memory efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional interpolation schemes are used to adapt the model database to different radar sensors, then the model can be used with multiple radar sensors, but significant range (time-domain) artifacts are introduced that degrade simulation results
Solution Approach 1:
The patent applies parameter changes by transforming the interpolation approach from time-domain to frequency-domain. By performing interpolation in the frequency domain and then transforming back to time-domain, the method avoids introducing range artifacts while maintaining compatibility across different radar sensors. This is achieved by changing the domain in which interpolation operations are performed, thereby preserving simulation accuracy.
2Manufacturing precision
If higher frequency sampling density is used in the database to improve interpolation accuracy, then simulation results are more accurate, but database storage and synthesis time increase by roughly an order of magnitude
Solution Approach 1:
The patent substitutes the mechanical approach of storing high-density frequency samples with a mathematical transformation approach. Instead of increasing the quantity of stored data, the method uses FFT-based interpolation in the frequency domain to achieve high accuracy results. This replacement of direct storage with transformation-based computation dramatically reduces database storage requirements while maintaining simulation accuracy.
3Manufacturing precision
If the radar model database is rebuilt for each sensor design change, then the model accurately reflects the specific sensor characteristics, but the process is time-consuming and inefficient
Solution Approach 1:
The patent implements universality by creating a single model database that can be adapted to multiple different radar sensor designs through frequency-domain interpolation. The FFT-based approach allows the same database to serve multiple sensor configurations accurately, eliminating the need for repeated database rebuilding while maintaining model accuracy for each specific sensor.
4Speed
If simplified radar models are used to achieve real-time prediction capability, then simulation speed is improved, but real-world physics and realism of predictions are sacrificed
Solution Approach 1:
The patent introduces frequency-domain transformation as an intermediary step that bridges the gap between simplified real-time computation and physically accurate predictions. By performing interpolation in the frequency domain and then transforming back to time-domain, the method enables real-time performance while preserving physical realism that would be lost in direct time-domain simplifications.
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
Enables real-time prediction of radar responses for diverse radar sensors and placements, reducing computational burden and artifacts, and allowing for a single database to be reused across various radar configurations, improving simulation accuracy and efficiency.
Implementation Method 1
In one embodiment, a pre-processing operation before the dynamic simulation performs fast Fourier Transforms (FFTs) to interpolate the object frequency responses from the database to the particular frequency samplings of the radar sensors used in the dynamic simulation
Implementation Method 2
The coherent RCS of an object being the phasor quantity representing the characteristic scattering response of the object to an incident electromagnetic plane wave for a particular combination of incidence angle, observation angle, incident polarization, observation polarization, and frequency
Data Source
AI summary
A method for building a coherent radar cross-section (RCS) model database for real-time dynamic simulation of range-Doppler radars is disclosed. The database may be used with radar sensors that employ different waveforms. A pre-processing operation before the dynamic simulation performs fast Fourier Transforms (FFTs) to interpolate the target frequency responses from the database to match the frequency samplings of the radar used in the dynamic simulation. The method determines the frequency responses of the targets to a reference chirp in a coherent processing interval (CPI) and the radial velocities of the targets relative to the radar at the time of the reference chirp. The method extrapolates, using FFTs, the frequency responses of the targets to the reference chirp across the velocity dimension based on the relative radial velocities to determine the frequency responses of the targets to the other chirps across the CPI, reducing the computational burden for the simulation.