Radar Velocity Resolution via Segmented Integration
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Solution Overview
Problem
Radar systems face challenges in determining object velocity with high resolution without increasing computational complexity, as longer integration intervals improve resolution but increase processing requirements and computation time.
Innovation Solution
The method involves partitioning the integration interval into time segments, performing a first integration using a low-resolution set of velocity hypotheses within each segment, and then a second integration using a higher-resolution set of hypotheses, with interpolation, to determine object velocity efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the integration interval is increased to improve velocity resolution, then the velocity resolution is improved, but the computational complexity and processing time increase
Solution Approach 1:
The integration interval is divided into multiple time segments, and the velocity estimation is performed in stages. First, a coarse velocity estimate is obtained by integrating over individual time segments with lower computational complexity. Then, a refined velocity estimate is obtained by integrating over the entire interval using the coarse estimate as an initial condition. This segmentation reduces the computational burden while maintaining high velocity resolution.
Solution Approach 2:
A preliminary integration is performed over individual time segments to obtain coarse velocity estimates before performing the final refined integration over the entire interval. This preliminary action reduces the computational complexity of the subsequent integration by providing an initial velocity estimate that guides the refined processing.
2Measurement precision
If the integration interval is increased to improve velocity resolution, then the velocity resolution is improved, but the processing time increases
Solution Approach 1:
The integration process is segmented into multiple stages: first integrating over individual time segments to obtain coarse estimates, then integrating over the entire interval to refine the velocity estimate. This segmentation allows the system to process data in manageable chunks, reducing overall processing time while achieving high velocity resolution through the combined effect of both integration stages.
Solution Approach 2:
The preliminary integration over time segments provides coarse velocity estimates that serve as initial conditions for the final refined integration. This preliminary processing reduces the computational burden of the final integration step, thereby reducing overall processing time while maintaining high velocity resolution.
3Measurement precision
If the number of velocity hypotheses is increased to improve resolution, then the velocity resolution is improved, but the computational complexity increases
Solution Approach 1:
The velocity hypotheses are processed in stages: first, a coarse set of velocity hypotheses is tested by integrating over individual time segments. Then, a refined set of velocity hypotheses is tested by integrating over the entire interval. This segmentation allows the system to evaluate velocity hypotheses efficiently, improving resolution without proportionally increasing computational complexity.
Solution Approach 2:
A preliminary testing of velocity hypotheses is performed over individual time segments to identify candidate velocities before performing the final refined testing over the entire interval. This preliminary action filters out incorrect velocity hypotheses early, reducing the computational complexity of the final velocity determination.
Data Source
AI summary
A vehicle, system, and method of determining a velocity of an object. The system includes a radar system and a processor. The radar system is configured to obtain a radar signal with respect to the object over an integration interval, the radar signal including a plurality of velocity samples. The processor is configured to partition the integration interval into a plurality of time segments, each time segment including a subset of the velocity samples, perform a first integration of the subset of the velocity samples within a selected time segment using a first set of velocity of hypotheses to obtain a first stage integration value for the time segment, perform a second integration using the first stage integration value using a second set of velocity hypotheses to obtain a second stage integration value over the integration interval, and determine the velocity of the object from the second stage integration value.