Radar Chirp Extrapolation for Unambiguous Velocity Determination
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Solution Overview
Problem
Existing automotive radar systems face challenges in real-time velocity disambiguation, particularly in time-division-multiplexed radar systems like TDM-MIMO, due to limitations in pulse repetition interval (PRI) reduction and signal processing capabilities.
Innovation Solution
An apparatus that processes FMCW radar signals by dividing radar frames into groups with distinct pulse repetition intervals and applying extrapolation techniques to generate interleaved chirps, reducing the effective PRI and enabling more accurate velocity determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the pulse repetition interval is reduced to improve velocity disambiguation, then the unambiguous velocity determination is improved, but the time required for signal processing and the complexity of the system increases
Solution Approach 1:
The patent applies extrapolation techniques to predict and generate missing chirp signals before they are actually received. By using autoregressive models to extrapolate chirp sequences from partially received groups, the system prepares complete signal sets in advance, reducing the need for complex real-time processing and allowing faster velocity determination without increasing system complexity
Solution Approach 2:
The patent creates virtual copies of chirp signals through extrapolation. By generating synthetic chirp sequences that replicate the characteristics of missing or incomplete groups using autoregressive parameter estimation, the system effectively copies the necessary signal patterns to achieve complete velocity information without requiring additional physical measurements or increasing processing complexity
2Measurement precision
If the pulse repetition interval is reduced to improve velocity disambiguation, then the unambiguous velocity determination is improved, but the processing time increases
Solution Approach 1:
The patent performs extrapolation operations on received chirp groups to generate complete signal sets before final velocity processing. By using autoregressive models to predict missing chirps in advance, the system eliminates the need for time-consuming iterative processing or waiting for complete signal groups, thereby reducing overall processing time while maintaining accurate velocity determination
Solution Approach 2:
The patent enables the system to skip waiting for complete chirp groups by using extrapolation to fill in missing data. The autoregressive parameter estimation allows the system to rush through the processing by generating plausible signal values for incomplete groups, avoiding time loss from waiting for full signal acquisition while still achieving accurate velocity measurements
Data Source
AI summary
An apparatus for processing radar signals is configured to receive a radar signal that includes a radar frame of a plurality of chirps, where the plurality of chirps includes at least a first group with a first pulse repetition interval, and a second group with a second pulse repetition interval. The groups are separated by a group separation time interval between a final chirp in the first group and a first chirp in the second group, where the group separation time interval is different than one or both of the first pulse repetition interval and the second pulse repetition interval. The apparatus further generates a modified received radar frame by performing a first extrapolation, based on temporal positions of the chirps in the first group of the received radar frame, to generate at least one extrapolated chirp in the modified received radar frame.